PGSQL on PIGSTY

Cluster / Instance

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Choose the appropriate instance and cluster types based on your requirements to configure PostgreSQL database clusters that meet your needs.

You can define different types of instances and clusters. Here are several common PostgreSQL instance/cluster types in Pigsty:

Primary: Define a single instance cluster.
Replica: Define a basic HA cluster with one primary and one replica.
Offline: Define an instance dedicated to OLAP/ETL/interactive queries
Sync Standby: Enable synchronous commit to ensure no data loss.
Quorum Commit: Use quorum sync commit for a higher consistency level.
Standby Cluster: Clone an existing cluster and follow it
Delayed Cluster: Clone an existing cluster for emergency data recovery
Citus Cluster: Define a Citus distributed database cluster

Primary

We start with the simplest case: a single instance cluster consisting of one primary:

Managing PostgreSQL Clusters

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Quick Reference

Action	Command	Description
Create Cluster	`bin/pgsql-add <cls>`	Create a new PostgreSQL cluster
Expand Cluster	`bin/pgsql-add <cls> <ip...>`	Add replica to existing cluster
Shrink Cluster	`bin/pgsql-rm <cls> <ip...>`	Remove instance from cluster
Remove Cluster	`bin/pgsql-rm <cls>`	Destroy entire PostgreSQL cluster
Reload Service	`bin/pgsql-svc <cls> [ip...]`	Reload cluster load balancer config
Reload HBA	`bin/pgsql-hba <cls> [ip...]`	Reload cluster HBA access rules
Clone Cluster	-	Clone via standby cluster or PITR

For other management tasks, see: HA Management, Manage Users, Manage Databases.

Model of Patroni Passive Failure

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RTO Timeline

Failure Model

Phase	Best	Worst	Average	Description
Lease Expiration	`ttl - loop`	`ttl`	`ttl - loop/2`	Best: crash just before refresh Worst: crash right after refresh
Replica Detect	`0`	`loop`	`loop / 2`	Best: exactly at check point Worst: just missed check point
Election Promote	`0`	`2`	`1`	Best: direct lock and promote Worst: API timeout + Promote
HAProxy Check	`(rise-1) × fastinter`	`(rise-1) × fastinter + inter`	`(rise-1) × fastinter + inter/2`	Best: state change before check Worst: state change right after check

Key Difference Between Passive and Active Failover:

Parameter Optimization Policy

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Pigsty provides four scenario-based parameter templates by default, which can be specified and used through the pg_conf parameter.

tiny.yml: Optimized for small nodes, VMs, and small demos (1-8 cores, 1-16GB)
oltp.yml: Optimized for OLTP workloads and latency-sensitive applications (4C8GB+) (default template)
olap.yml: Optimized for OLAP workloads and throughput (4C8G+)
crit.yml: Optimized for data consistency and critical applications (4C8G+)

Pigsty adopts different parameter optimization strategies for these four default scenarios, as shown below:

RPO Trade-offs

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RPO (Recovery Point Objective) defines the maximum amount of data loss allowed when the primary fails.

For scenarios where data integrity is critical, such as financial transactions, RPO = 0 is typically required, meaning no data loss is allowed.

However, stricter RPO targets come at a cost: higher write latency, reduced system throughput, and the risk that replica failures may cause primary unavailability. For typical scenarios, some data loss is acceptable (e.g., up to 1MB) in exchange for higher availability and performance.

Model of Patroni Active Failure

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RTO Timeline

Failure Model

Item	Best	Worst	Average	Description
Crash Found	`0`	`loop`	`loop/2`	Best: PG crashes right before check Worst: PG crashes right after check
Restart Timeout	`0`	`start`	`start`	Best: PG recovers instantly Worst: Wait full start timeout before releasing lease
Replica Detect	`0`	`loop`	`loop/2`	Best: Right at check point Worst: Just missed check point
Elect Promote	`0`	`2`	`1`	Best: Acquire lock and promote directly Worst: API timeout + Promote
HAProxy Check	`(rise-1) × fastinter`	`(rise-1) × fastinter + inter`	`(rise-1) × fastinter + inter/2`	Best: State changes before check Worst: State changes right after check

Key Difference Between Active and Passive Failure:

Kernel Version

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Choosing a “kernel” in Pigsty means determining the PostgreSQL major version, mode/distribution, packages to install, and tuning templates to load.

Pigsty v4.3 currently supports PostgreSQL 14-18 and uses 18 by default. The following content shows how to make these choices through configuration files.

Major Version and Packages

pg_version: Specify the PostgreSQL major version (default 18). Pigsty will automatically map to the correct package name prefix based on the version.
pg_packages: Define the core package set to install, supports using package aliases (default pgsql-main pgsql-common, includes kernel + patroni/pgbouncer/pgbackrest and other common tools).
pg_extensions: List of additional extension packages to install, also supports aliases; defaults to empty meaning only core dependencies are installed.

all:
 vars:
 pg_version: 18
 pg_packages: [ pgsql-main pgsql-common ]
 pg_extensions: [ postgis, timescaledb, pgvector, pgml ]

Effect: Ansible will pull packages corresponding to pg_version=18 during installation, pre-install extensions to the system, and database initialization scripts can then directly CREATE EXTENSION.

OLTP Template

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oltp.yml is Pigsty’s default config template, optimized for online transaction processing (OLTP). Designed for 4-128 core CPUs with high concurrency, low latency, and high throughput.

Pair with node_tune = oltp for OS-level tuning.

Use Cases

OLTP template is ideal for:

E-commerce: Order processing, inventory, user transactions
Social apps: User feeds, messaging, following relationships
Gaming backends: Player data, leaderboards, game state
SaaS applications: Multi-tenant business systems
Web apps: CRUD-intensive workloads

Workload characteristics:

E-R Model of PostgreSQL Cluster

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The PGSQL module organizes PostgreSQL in production as clusters—logical entities composed of a group of database instances associated by primary-replica relationships.

Each cluster is an autonomous business unit consisting of at least one primary instance, exposing capabilities through services.

There are four core entities in Pigsty’s PGSQL module:

Cluster: An autonomous PostgreSQL business unit serving as the top-level namespace for other entities.
Service: A named abstraction that exposes capabilities, routes traffic, and exposes services using node ports.
Instance: A single PostgreSQL server consisting of running processes and database files on a single node.
Node: A hardware resource abstraction running Linux + Systemd environment—can be bare metal, VM, container, or Pod.

Along with two business entities—“Database” and “Role”—these form the complete logical view as shown below:

Managing PostgreSQL Users

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Quick Start

Pigsty uses declarative management: first define users in the inventory, then use bin/pgsql-user <cls> <username> to create or modify.

pg-meta:
 hosts: { 10.10.10.10: { pg_seq: 1, pg_role: primary } }
 vars:
 pg_cluster: pg-meta
 pg_users: [{ name: dbuser_app, password: 'DBUser.App', pgbouncer: true }] # <--- Define user list here!

bin/pgsql-user <cls> <username> # Create/modify <username> user on <cls> cluster

./pgsql-user.yml -l pg-meta -e username=dbuser_app # Use playbook to create/modify user

bin/pgsql-user pg-meta dbuser_app # Create/modify dbuser_app user on pg-meta cluster

For complete user definition reference, see User Configuration. For access permissions, see ACL: Role Privileges.

Managing PostgreSQL Databases

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Quick Start

Pigsty uses declarative management: first define databases in the inventory, then use bin/pgsql-db <cls> <dbname> to create or modify.

pg-meta:
 hosts: { 10.10.10.10: { pg_seq: 1, pg_role: primary } }
 vars:
 pg_cluster: pg-meta
 pg_databases: [{ name: some_db }]  # <--- Define database list here!

bin/pgsql-db <cls> <dbname> # Create/modify <dbname> database on <cls> cluster

./pgsql-db.yml -l pg-meta -e dbname=some_db # Use playbook to create/modify database

bin/pgsql-db pg-meta some_db # Create/modify some_db database on pg-meta cluster

For complete database definition reference, see Database Configuration. For access permissions, see ACL: Database Privileges.

Failure Model

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Patroni failures can be classified into 10 categories by failure target, and further consolidated into five categories based on detection path, which are detailed in this section.

#	Failure Scenario	Description	Final Path
1	PG process crash	crash, OOM killed	Active Detection
2	PG connection refused	max_connections	Active Detection
3	PG zombie	Process alive but unresponsive	Active Detection (timeout)
4	Patroni process crash	kill -9, OOM	Passive Detection
5	Patroni zombie	Process alive but stuck	Watchdog
6	Node down	Power outage, hardware failure	Passive Detection
7	Node zombie	IO hang, CPU starvation	Watchdog
8	Primary ↔ DCS network failure	Firewall, switch failure	Network Partition
9	Storage failure	Disk failure, disk full, mount failure	Active Detection or Watchdog
10	Manual switchover	Switchover/Failover	Manual Trigger

However, for RTO calculation purposes, all failures ultimately converge to two paths. This section explores the upper bound, lower bound, and average RTO for these two scenarios.

OLAP Template

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olap.yml is optimized for online analytical processing (OLAP). Designed for 4-128 core CPUs with support for large queries, high parallelism, relaxed timeouts, and aggressive vacuum.

Pair with node_tune = olap for OS-level tuning.

Use Cases

OLAP template is ideal for:

Data warehouses: Historical data storage, multidimensional analysis
BI reports: Complex report queries, dashboard data sources
ETL processing: Data extraction, transformation, loading
Data analysis: Ad-hoc queries, data exploration
HTAP mixed workloads: Analytical replicas

Workload characteristics:

Package Alias

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PostgreSQL package naming conventions vary significantly across different operating systems:

EL systems (RHEL/Rocky/Alma/…) use formats like pgvector_18, postgis36_18*
Debian/Ubuntu systems use formats like postgresql-18-pgvector, postgresql-18-postgis-3

This difference adds cognitive burden to users: you need to remember different package name rules for different systems, and handle the embedding of PostgreSQL version numbers.

Package Alias

Pigsty solves this problem through the Package Alias mechanism: you only need to use unified aliases, and Pigsty will handle all the details:

CRIT Template

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crit.yml is optimized for critical/financial workloads. Designed for 4-128 core CPUs with forced sync replication, data checksums, full audit logging, and strict security. Trades performance for maximum data safety.

Pair with node_tune = crit for OS-level tuning, optimizing dirty page management.

Use Cases

CRIT template is ideal for:

Financial transactions: Bank transfers, payment settlement, securities trading
Core accounting: General ledger systems, accounting systems
Compliance audit: Businesses requiring complete operation records
Critical business: Any scenario that cannot tolerate data loss

Requirements:

Patroni HA Management

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Overview

Pigsty uses Patroni to manage PostgreSQL clusters. It handles config changes, status checks, switchover, restart, reinit replicas, and more.

To use Patroni for management, you need one of the following identities:

From INFRA node as admin user, managing all clusters in the environment.
From PGSQL node as pg_dbsu (default postgres), managing the current cluster only.

Patroni provides patronictl CLI for management. Pigsty provides a wrapper alias pg to simplify operations.

Using patronictl via pg alias

pg ()
{
 local patroni_conf="/infra/conf/patronictl.yml";
 if [ ! -r ${patroni_conf} ]; then
 patroni_conf="/etc/patroni/patroni.yml";
 if [ ! -r ${patroni_conf} ]; then
 echo "error: patronictl config not found";
 return 1;
 fi;
 fi;
 patronictl -c ${patroni_conf} "$@"
}

Available Commands

Command	Function	Description
`edit-config`	Edit Config	Interactively edit cluster Patroni/PostgreSQL config
`list`	List Status	List cluster members and their status
`switchover`	Switchover	Switch primary role to specified replica (planned)
`failover`	Failover	Force failover to specified replica (emergency)
`restart`	Restart	Restart PostgreSQL instance to apply restart-required params
`reload`	Reload	Reload Patroni config (no restart needed)
`reinit`	Reinit Replica	Reinitialize replica (wipe data and re-clone)
`pause`	Pause Auto-Failover	Pause Patroni automatic failover
`resume`	Resume Auto-Failover	Resume Patroni automatic failover
`history`	View History	Show cluster failover history
`show-config`	Show Config	Display current cluster config (read-only)
`query`	Execute Query	Execute SQL query on cluster members
`topology`	View Topology	Display cluster replication topology
`version`	View Version	Display Patroni version info
`remove`	Remove Member	Remove cluster member from DCS (dangerous)

Edit Config

Use edit-config to interactively edit cluster Patroni and PostgreSQL config. This opens an editor to modify config stored in DCS, automatically applying changes to all members. You can change Patroni params (ttl, loop_wait, synchronous_mode, etc.) and PostgreSQL params in postgresql.parameters.

User/Role

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In this document, “user” refers to a logical object within a database cluster created with CREATE USER/ROLE.

In PostgreSQL, users belong directly to the database cluster rather than a specific database. Therefore, when creating business databases and users, follow the principle of “users first, databases later”.

Pigsty defines roles and users through two config parameters:

pg_default_roles: Define globally shared roles and users
pg_users: Define business users and roles at cluster level

The former defines roles/users shared across the entire environment; the latter defines business roles/users specific to a single cluster. Both have the same format as arrays of user definition objects. Users/roles are created sequentially in array order, so later users can belong to roles defined earlier.

Database

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In this document, “database” refers to a logical object within a database cluster created with CREATE DATABASE.

A PostgreSQL cluster can serve multiple databases simultaneously. In Pigsty, you can define required databases in cluster configuration.

Pigsty customizes the template1 template database - creating default schemas, installing default extensions, configuring default privileges. Newly created databases inherit these settings from template1. You can also specify other template databases via template for instant database cloning.

By default, all business databases are 1:1 added to Pgbouncer connection pool; pg_exporter auto-discovers all business databases for in-database object monitoring. All databases are also registered as PostgreSQL datasources in Grafana on all INFRA nodes for PGCAT dashboards.

Pgbouncer Connection Pooling

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Overview

Pigsty uses Pgbouncer as PostgreSQL connection pooling middleware, listening on port 6432 by default, proxying access to local PostgreSQL on port 5432.

This is an optional component. If you don’t have massive connections or need transaction pooling and query metrics, you can disable it, connect directly to the database, or keep it unused.

User & Database Management

Pgbouncer users and databases are auto-managed by Pigsty, applying database config and user config when creating databases and creating users.

TINY Template

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tiny.yml is optimized for micro instances and resource-constrained environments. Designed for 1-3 core CPUs with minimal resource usage, conservative memory allocation, and disabled parallel queries.

Pair with node_tune = tiny for OS-level tuning.

Use Cases

TINY template is ideal for:

Dev/test: Local development, CI/CD testing
Low-spec VMs: 1-2 core CPU, 1-4GB RAM cloud instances
Edge computing: Raspberry Pi, embedded devices
Demos: Quick Pigsty experience
Personal projects: Resource-limited blogs, small apps

Resource constraints:

HBA Rules

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Overview

HBA (Host-Based Authentication) controls “who can connect to the database from where and how”. Pigsty manages HBA rules declaratively through pg_default_hba_rules and pg_hba_rules.

Pigsty renders the following config files during cluster init or HBA refresh:

Config File	Path	Description
PostgreSQL HBA	`/pg/data/pg_hba.conf`	PostgreSQL server HBA rules
Pgbouncer HBA	`/etc/pgbouncer/pgb_hba.conf`	Connection pool HBA rules

HBA rules are controlled by these parameters:

Parameter	Level	Description
`pg_default_hba_rules`	G	PostgreSQL global default HBA
`pg_hba_rules`	G/C/I	PostgreSQL cluster/instance add
`pgb_default_hba_rules`	G	Pgbouncer global default HBA
`pgb_hba_rules`	G/C/I	Pgbouncer cluster/instance add

Rule features:

Access Control

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Access control is determined by the combination of “role system + privilege templates + HBA”. This section focuses on how to declare roles and object privileges through configuration parameters.

Pigsty provides a streamlined ACL model, fully described by the following parameters:

pg_default_roles: System roles and system users.
pg_users: Business users and roles.
pg_default_privileges: Default privileges for objects created by administrators/owners.
pg_revoke_public, pg_default_schemas, pg_default_extensions: Control the default behavior of template1.

After understanding these parameters, you can write fully reproducible privilege configurations.

Managing PostgreSQL Component Services

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Overview

Pigsty’s PGSQL module consists of multiple components, each running as a systemd service on nodes. (pgbackrest is an exception)

Understanding these components and their management is essential for maintaining production PostgreSQL clusters.

Component	Port	Service Name	Description
Patroni	`8008`	`patroni`	HA manager, manages PostgreSQL lifecycle
PostgreSQL	`5432`	`postgres`	Placeholder service, not used, for emergency
Pgbouncer	`6432`	`pgbouncer`	Connection pooling middleware, traffic entry
PgBackRest	-	-	pgBackRest has no daemon service
HAProxy	`543x`	`haproxy`	Load balancer, exposes database services
pg_exporter	`9630`	`pg_exporter`	PostgreSQL metrics exporter
pgbouncer_exporter	`9631`	`pgbouncer_exporter`	Pgbouncer metrics exporter
vip-manager	-	`vip-manager`	Optional, manages L2 VIP address floating

Important

Do NOT use systemctl directly to manage PostgreSQL service. PostgreSQL is managed by Patroni - use patronictl commands instead. Direct PostgreSQL operations may cause Patroni state inconsistency and trigger unexpected failover. The postgres service is an emergency escape hatch when Patroni fails.

Parameters

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PostgreSQL parameters can be configured at multiple levels with different scopes and precedence. Pigsty supports four configuration levels, from global to local:

Level	Scope	Configuration Method	Storage Location
Cluster	All instances in cluster	Patroni DCS / Tuning Templates	etcd + `postgresql.conf`
Instance	Single PG instance	`pg_parameters` / `ALTER SYSTEM`	`postgresql.auto.conf`
Database	All sessions in a DB	`pg_databases[].parameters`	`pg_db_role_setting`
User	All sessions of a user	`pg_users[].parameters`	`pg_db_role_setting`

Priority from low to high: Cluster < Instance < Database < User < Session (SET command). Higher priority settings override lower ones.

Manage PostgreSQL Cron Jobs

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Pigsty uses crontab to manage scheduled tasks for routine backups, freezing aging transactions, and reorganizing bloated tables and indexes.

Quick Reference

Operation	Quick Command	Description
Configure Cron Jobs	`./pgsql.yml -t pg_crontab -l <cls>`	Apply pg_crontab config
View Cron Jobs	`crontab -l`	View as postgres user
Physical Backup	`pg-backup [full\|diff\|incr]`	Execute backup with pgBackRest
Transaction Freeze	`pg-vacuum [database...]`	Freeze aging transactions, prevent XID wraparound
Bloat Maintenance	`pg-repack [database...]`	Online reorganize bloated tables and indexes

For other management tasks, see: Backup Management, Monitoring System, HA Management.

Managing PostgreSQL Extensions

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Quick Start

Pigsty provides 510 extensions. Using extensions involves four steps: Download, Install, Configure, Enable.

pg-meta:
 hosts: { 10.10.10.10: { pg_seq: 1, pg_role: primary } }
 vars:
 pg_cluster: pg-meta
 pg_extensions: [ postgis, timescaledb, pgvector ]  # <--- Install extension packages
 pg_libs: 'timescaledb, pg_stat_statements, auto_explain' # <--- Configure preload extensions
 pg_databases:
 - name: meta
 extensions: [ postgis, timescaledb, vector ]  # <--- Enable in database

bin/pgsql-ext <cls> # Install extensions defined in config on <cls> cluster
bin/pgsql-ext <cls> [ext...] # Install extensions specified on command line

./pgsql.yml -l pg-meta -t pg_ext # Use playbook to install extensions

bin/pgsql-ext pg-meta # Install defined extensions on pg-meta cluster
bin/pgsql-ext pg-meta pg_duckdb pg_mooncake # Install specified extensions

For complete extension reference, see Extensions. For available extensions, see Extension Catalog.

Upgrading PostgreSQL Major/Minor Versions

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Quick Start

PostgreSQL version upgrades fall into two types: minor version upgrade and major version upgrade, with very different risk and complexity.

Type	Example	Downtime	Data Compatibility	Risk
Minor upgrade	17.2 → 17.3	Seconds (rolling)	Fully compatible	Low
Major upgrade	17 → 18	Minutes	Requires data dir upgrade	Medium

# Rolling upgrade: replicas first, then primary
ansible <cls> -b -a 'yum upgrade -y postgresql17*'
pg restart --role replica --force <cls>
pg switchover <cls>
pg restart <cls> <old-primary> --force

# Recommended: Logical replication migration
bin/pgsql-add pg-new # Create new version cluster
# Configure logical replication to sync data...
# Switch traffic to new cluster

ansible <cls> -b -a 'yum upgrade -y postgis36_17*'
psql -c 'ALTER EXTENSION postgis UPDATE;'

For detailed online migration process, see Online Migration documentation.

High Availability

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Overview

Pigsty’s PostgreSQL clusters come with out-of-the-box high availability, powered by Patroni, Etcd, and HAProxy.

When your PostgreSQL cluster has two or more instances, you automatically have self-healing database high availability without any additional configuration — as long as any instance in the cluster survives, the cluster can provide complete service. Clients only need to connect to any node in the cluster to get full service without worrying about primary-replica topology changes.

With default configuration, the primary failure Recovery Time Objective (RTO) ≈ 45s, and Recovery Point Objective (RPO) < 1MB; for replica failures, RPO = 0 and RTO ≈ 0 (brief interruption). In consistency-first mode, failover can guarantee zero data loss: RPO = 0. All these metrics can be configured as needed based on your actual hardware conditions and reliability requirements.

PGSQL Arch

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The PGSQL module organizes PostgreSQL in production as clusters—logical entities composed of a group of database instances associated by primary-replica relationships.

Overview

The PGSQL module includes the following components, working together to provide production-grade PostgreSQL HA cluster services:

Component	Type	Description
`postgres`	Database	The world’s most advanced open-source relational database, PGSQL core
`patroni`	HA	Manages PostgreSQL, coordinates failover, leader election, config changes
`pgbouncer`	Pool	Lightweight connection pooling middleware, reduces overhead, adds flexibility
`pgbackrest`	Backup	Full/incremental backup and WAL archiving, supports local and object storage
`pg_exporter`	Metrics	Exports PostgreSQL monitoring metrics for Prometheus scraping
`pgbouncer_exporter`	Metrics	Exports Pgbouncer connection pool metrics
`pgbackrest_exporter`	Metrics	Exports backup status metrics
`vip-manager`	VIP	Binds L2 VIP to current primary node for transparent failover [Optional]

The vip-manager is an on-demand component. Additionally, PGSQL uses components from other modules:

Point-in-Time Recovery

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When you accidentally delete data, tables, or even the entire database, PITR lets you return to any point in time and avoid data loss from software defects and human error.

— This “magic” once reserved for senior DBAs is now available out of the box to everyone.

Overview

Pigsty’s PostgreSQL clusters come with auto-configured Point-in-Time Recovery (PITR) capability, powered by the backup component pgBackRest and optional object storage repository MinIO.

High availability solutions can address hardware failures but are powerless against data deletion/overwriting/database drops caused by software defects and human errors. For such situations, Pigsty provides out-of-the-box Point-in-Time Recovery (PITR) capability, enabled by default without additional configuration.

RTO Trade-offs

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RTO (Recovery Time Objective) defines the maximum time required for the system to restore write capability when the primary fails.

For critical transaction systems where availability is paramount, the shortest possible RTO is typically required, such as under one minute.

However, shorter RTO comes at a cost: increased false failover risk. Network jitter may be misinterpreted as a failure, leading to unnecessary failovers. For cross-datacenter/cross-region deployments, RTO requirements are typically relaxed (e.g., 1-2 minutes) to reduce false failover risk.

How PITR Works

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The core principle of PITR is: base backup + WAL archiving = recover to any point in time. In Pigsty, this is implemented by pgBackRest, running scheduled backups + WAL archiving automatically.

Three Elements

Element	Purpose	Pigsty Implementation
Base Backup	Provides a consistent physical snapshot, recovery starting point	`pg-backup` + `pgbackrest` + `pg_crontab`
WAL Archiving	Records all changes after backup, defines recovery path	`archive_mode=on` + `archive_command=pgbackrest ... archive-push`
Recovery Target	Specifies where to stop recovery	`pg_pitr` params / `pg-pitr` script / `pgbackrest restore`

Base Backup

Base backup is a physical snapshot at a point in time, the starting point of PITR. Pigsty uses pgBackRest and provides pg-backup wrapper for common ops.

PITR Architecture

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Pigsty uses pgBackRest as the PostgreSQL backup and recovery engine, providing out-of-the-box Point-in-Time Recovery (PITR).

This page explains the architecture: who runs backups, where data flows, how repositories are organized, and how continuity is kept after failover.

Overview

PITR architecture has three main pipelines: backup execution, WAL archiving, restore execution.

Pipeline	Entry	Engine	Destination
Backup	`pg-backup` + `pg_crontab`	`pgbackrest backup`	repo `backup/`
WAL Archive	PostgreSQL `archive_command`	`pgbackrest archive-push`	repo `archive/`
Restore	`pg_pitr` / `pg-pitr` / `pgsql-pitr.yml`	`pgbackrest restore`	target data directory

See Backup Mechanism and Restore Operations for details.

PITR Tradeoffs

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When designing a PITR strategy, the core tradeoffs are: backup repository location, recovery window length, and restore speed vs storage cost.

This page helps you make practical choices across these dimensions.

Local vs Remote

Repository location is the first decision in PITR strategy.

Local Repository

Store backups on primary local disk (pgbackrest_method = local):

Pros

Simple, out-of-the-box
Fast restore (local I/O)
No external dependency

Cons

No geo-DR; backups may be lost with host
Limited by local disk capacity
Same failure domain as production data

Remote Repository

Store backups on MinIO / S3 (pgbackrest_method = minio|s3):

PITR Scenarios

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The value of PITR is not just “rolling back a database”, but turning irreversible human/software mistakes into recoverable problems. It covers cases from “drop one table” to “entire site down”, addressing logical errors and disaster recovery.

Overview

PITR addresses these scenarios:

Scenario Type	Typical Problem	Recommended Strategy	Recovery Target
Accidental DML	`DELETE/UPDATE` without `WHERE`, script mistake	Branch restore first	`time` / `xid`
DDL drops	`DROP TABLE/DATABASE`, bad migration	Branch restore	`time` / `name`
Batch errors / bad release	Buggy release pollutes data	Branch restore + verify	`time` / `xid`
Audit / investigation	Need to inspect historical state	Branch restore (read-only)	`time` / `lsn`
Site disaster / total loss	Hardware failure, ransomware, power outage	In-place or rebuild	`latest` / `time`

A Simple Rule of Thumb

If writes already caused business errors, consider PITR.
Need online verification or partial recovery → branch restore.
Need service restored ASAP → in-place restore (accept downtime).

flowchart TD
 A["Issue discovered"] --> B{"Downtime allowed?"}
 B -->|Yes| C["In-place restore<br/>shortest path"]
 B -->|No| D["Branch restore<br/>verify then switch"]
 C --> E["Rebuild backups after restore"]
 D --> F["Verify / export / cut traffic"]

Scenario Details

Accidental DML (Delete/Update)

Typical issues:

Service Access

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Split read and write operations, route traffic correctly, and deliver PostgreSQL cluster capabilities reliably.

Service is an abstraction: it represents the form in which database clusters expose their capabilities externally, encapsulating underlying cluster details.

Services are crucial for stable access in production environments, showing their value during automatic failover in high availability clusters. Personal users typically don’t need to worry about this concept.

Personal Users

The concept of “service” is for production environments. Personal users with single-node clusters can skip the complexity and directly use instance names or IP addresses to access the database.

Security and Compliance

Mon, 01 Jan 0001 00:00:00 +0000

Pigsty’s security goals are the CIA triad:

Confidentiality: prevent unauthorized access and leakage
Integrity: prevent tampering or silent corruption
Availability: prevent outages from failures

Pigsty’s security philosophy:

Secure by default: out-of-the-box baseline with minimal config and broad coverage.
Defense in depth: layered protections so one breach does not collapse the system.
Least privilege: roles and privileges enforce least-privilege by default.
Compliance-ready: security capabilities plus process can meet audits.

Default Security Baseline (What Problems It Solves)

Security Option	Default	Problems Solved
Password encryption	`pg_pwd_enc: scram-sha-256`	Prevent weak hashes and plaintext leakage
Data checksums	`pg_checksum: true`	Detect silent data corruption
HBA layering	Admin from internet must use `ssl`	Prevent plaintext access from the public network
Local CA	`ca_create: true`	Unified certificate trust chain
Backup & recovery	`pgbackrest_enabled: true`	Prevent data loss from mistakes
Nginx HTTPS	`nginx_sslmode: enable`	Prevent plaintext web ingress
MinIO HTTPS	`minio_https: true`	Prevent backup traffic snooping
OS baseline	SELinux `permissive`	Baseline for enforcing mode

Defaults prioritize usability and scalability. Production should be hardened to meet compliance needs.

Seven-Layer Security Model

Mon, 01 Jan 0001 00:00:00 +0000

Security is not a wall, but a city. Pigsty adopts a defense-in-depth strategy and builds multiple protections across seven layers. Even if one layer is breached, other layers still protect the system.

This layered approach addresses three core risks:

Perimeter breach: reduce the chance that one breach compromises everything.
Internal abuse: even if an internal account is compromised, least privilege limits damage.
Unpredictable failures: hardware, software, and human errors all get multi-layer fallbacks.

Overview

L1 Physical and Media Security

When the physical layer falls, the only defense is the data itself.

Authentication

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Authentication answers three core questions:

Who you are: is the identity unique and recognizable?
How you prove it: are passwords/certs strong enough?
Where you come from: is the source controlled?

Pigsty uses HBA rules + password/certificates for authentication, with SCRAM as the default password hash.

Authentication Flow

flowchart LR
 C[Client] --> HBA[HBA Rules]
 HBA --> A1[Password SCRAM]
 HBA --> A2[Certificate Auth]
 HBA --> A3[Local ident/peer]
 A1 --> RBAC[Roles and Privileges]
 A2 --> RBAC
 A3 --> RBAC

HBA decides “who can come from where”, and the auth method decides “how identity is proven”.

Access Control

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Access control answers two core questions:

What you can do: boundaries for read/write/DDL
What data you can access: isolation across databases and schemas

Pigsty enforces least privilege with RBAC roles + default privileges.

Four-Tier Role Model

flowchart TB
 subgraph Admin["dbrole_admin (Admin)"]
 A1["Can run DDL / CREATE / ALTER"]
 A2["Inherits dbrole_readwrite"]
 end
 subgraph RW["dbrole_readwrite (Read-Write)"]
 RW1["Can INSERT/UPDATE/DELETE"]
 RW2["Inherits dbrole_readonly"]
 end
 subgraph RO["dbrole_readonly (Read-Only)"]
 RO1["Can SELECT all tables"]
 end
 subgraph Offline["dbrole_offline (Offline)"]
 OFF1["Only for offline instances"]
 end

 Admin --> RW --> RO

Problems solved

Encrypted Communication and Local CA

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Encrypted communication solves three problems:

Eavesdropping: prevent plaintext traffic sniffing
Tampering: prevent MITM modification
Impersonation: prevent fake servers/clients

Pigsty uses a local CA + TLS to provide a unified trust root for databases and infrastructure components.

Role of the Local CA

Pigsty generates a self-signed CA on the admin node by default:

files/pki/ca/ca.key # CA private key (must be protected)
files/pki/ca/ca.crt # CA root certificate (distributable)

Default values in source:

ca_create: true: auto-generate if CA not found.
ca_cn: pigsty-ca: CA certificate CN fixed to pigsty-ca.
Root cert validity about 100 years (self-signed).
Server/client cert validity cert_validity: 7300d (20 years).

Certificate Coverage

The local CA issues certs for multiple components with a unified trust chain:

Data Security

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Data security focuses on three things: integrity, recoverability, confidentiality. Pigsty enables key capabilities by default and supports further hardening.

Data Integrity

Problems solved

Silent corruption from bad disks or memory errors
Accidental writes causing data pollution

Pigsty support

Data checksums: default pg_checksum: true, enables data-checksums at init.
Replica fallback: recover bad blocks from replicas (with HA).

Recoverability (Backup and PITR)

Problems solved

Accidental deletion or modification
Disaster-level data loss

Pigsty support

Compliance Checklist

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Compliance is not a switch, but a combination of configuration + process + evidence:

Configuration: are security capabilities enabled (HBA/TLS/audit/backup)?
Process: access management, change control, backup drills
Evidence: logs, config snapshots, backup reports, monitoring alerts

This page uses SOC2 and MLPS Level 3 as entry points to map Pigsty’s security capabilities and compliance evidence.

Default Credentials Checklist (Must Change)

From source defaults:

Component	Default Username	Default Password
PostgreSQL Admin	`dbuser_dba`	`DBUser.DBA`
PostgreSQL Monitor	`dbuser_monitor`	`DBUser.Monitor`
PostgreSQL Replication	`replicator`	`DBUser.Replicator`
Patroni API	`postgres`	`Patroni.API`
HAProxy Admin	`admin`	`pigsty`
Grafana Admin	`admin`	`pigsty`
MinIO Root	`minioadmin`	`S3User.MinIO`
etcd Root	`root`	`Etcd.Root`

Must change all defaults in production.

Getting Started with PostgreSQL

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PostgreSQL (abbreviated as PG) is the world’s most advanced and popular open-source relational database. Use it to store and retrieve multi-modal data.

This guide is for developers with basic Linux CLI experience but not very familiar with PostgreSQL, helping you quickly get started with PG in Pigsty.

We assume you’re a personal user deploying in the default single-node mode. For prod multi-node HA cluster access, refer to Prod Service Access.

Basics

In the default single-node installation template, you’ll create a PostgreSQL database cluster named pg-meta on the current node, with only one primary instance.

Extensions

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Pigsty extension data is synchronized from ~/pgsty/pgext/content/list/ext.md and ~/pgsty/pgext/db/extension.csv. For full details, see PGEXT.CLOUD.

There are currently 510 available PostgreSQL extensions.

TIME

Extension	Version	Category	Description
timescaledb	`2.25.2`	`TIME`	Enables scalable inserts and complex queries for time-series data
timescaledb_toolkit	`1.22.0`	`TIME`	Library of analytical hyperfunctions, time-series pipelining, and other SQL utilities
timeseries	`0.2.0`	`TIME`	Convenience API for time series stack
periods	`1.2.3`	`TIME`	Provide Standard SQL functionality for PERIODs and SYSTEM VERSIONING
temporal_tables	`1.2.2`	`TIME`	temporal tables
emaj	`4.7.1`	`TIME`	Enables fine-grained write logging and time travel on subsets of the database.
table_version	`1.11.1`	`TIME`	PostgreSQL table versioning extension
pg_cron	`1.6.7`	`TIME`	Job scheduler for PostgreSQL
pg_task	`1.0.0`	`TIME`	execute any sql command at any specific time at background
pg_later	`0.4.0`	`TIME`	Run queries now and get results later
pg_background	`1.8`	`TIME`	Run SQL queries in the background

GIS

Extension	Version	Category	Description
postgis	`3.6.2`	`GIS`	PostGIS geometry and geography spatial types and functions
postgis_topology	`3.6.2`	`GIS`	PostGIS topology spatial types and functions
postgis_raster	`3.6.2`	`GIS`	PostGIS raster types and functions
postgis_sfcgal	`3.6.2`	`GIS`	PostGIS SFCGAL functions
postgis_tiger_geocoder	`3.6.2`	`GIS`	PostGIS tiger geocoder and reverse geocoder
address_standardizer	`3.6.2`	`GIS`	Used to parse an address into constituent elements. Generally used to support geocoding address normalization step.
address_standardizer_data_us	`3.6.2`	`GIS`	Address Standardizer US dataset example
pgrouting	`4.0.1`	`GIS`	pgRouting Extension
pointcloud	`1.2.5`	`GIS`	data type for lidar point clouds
pointcloud_postgis	`1.2.5`	`GIS`	integration for pointcloud LIDAR data and PostGIS geometry data
h3	`4.2.3`	`GIS`	H3 bindings for PostgreSQL
h3_postgis	`4.2.3`	`GIS`	H3 PostGIS integration
q3c	`2.0.2`	`GIS`	q3c sky indexing plugin
ogr_fdw	`1.1.7`	`GIS`	foreign-data wrapper for GIS data access
geoip	`0.3.0`	`GIS`	IP-based geolocation query
pg_polyline	`0.0.1`	`GIS`	Fast Google Encoded Polyline encoding & decoding for postgres
pg_eviltransform	`0.0.2`	`GIS`	BD09/GCJ02 coordinate transformation based on PostGIS ST_Transform
pg_geohash	`1.0`	`GIS`	Handle geohash based functionality for spatial coordinates
mobilitydb	`1.3.0`	`GIS`	MobilityDB geospatial trajectory data management & analysis platform
mobilitydb_datagen	`1.3.0`	`GIS`	MobilityDB random data generator functions
tzf	`0.2.3`	`GIS`	Fast lookup timezone name by GPS coordinates
earthdistance	`1.2`	`GIS`	calculate great-circle distances on the surface of the Earth

RAG

Extension	Version	Category	Description
vector	`0.8.2`	`RAG`	vector data type and ivfflat and hnsw access methods
vchord	`1.1.1`	`RAG`	Vector database plugin for Postgres, written in Rust
vectorscale	`0.9.0`	`RAG`	Advanced indexing for vector data with DiskANN
vectorize	`0.26.0`	`RAG`	The simplest way to do vector search on Postgres
pg_similarity	`1.0`	`RAG`	support similarity queries
smlar	`1.0`	`RAG`	Effective similarity search
pg_summarize	`0.0.1`	`RAG`	Text Summarization using LLMs. Built using pgrx
pg_tiktoken	`0.0.1`	`RAG`	tiktoken tokenizer for use with OpenAI models in postgres
pg4ml	`2.0`	`RAG`	Machine learning framework for PostgreSQL
pgml	`2.10.0`	`RAG`	Run AL/ML workloads with SQL interface

FTS

Extension	Version	Category	Description
pg_search	`0.21.12`	`FTS`	Full text search for PostgreSQL using BM25
pgroonga	`4.0.4`	`FTS`	Use Groonga as index, fast full text search platform for all languages!
pgroonga_database	`4.0.4`	`FTS`	PGroonga database management module
pg_bigm	`1.2`	`FTS`	create 2-gram (bigram) index for faster full text search.
zhparser	`2.3`	`FTS`	a parser for full-text search of Chinese
pg_bestmatch	`0.0.2`	`FTS`	Generate BM25 sparse vector inside PostgreSQL
vchord_bm25	`0.3.0`	`FTS`	A postgresql extension for bm25 ranking algorithm
pg_tokenizer	`0.1.1`	`FTS`	Tokenizers for full-text search
biscuit	`2.2.2`	`FTS`	IAM-LIKE pattern matching with bitmap indexing
pg_textsearch	`0.5.0`	`FTS`	Full-text search with BM25 ranking
pg_pinyin	`0.0.2`	`FTS`	PostgreSQL Pinyin transliteration and search extension
hunspell_cs_cz	`1.0`	`FTS`	Czech Hunspell Dictionary
hunspell_de_de	`1.0`	`FTS`	German Hunspell Dictionary
hunspell_en_us	`1.0`	`FTS`	en_US Hunspell Dictionary
hunspell_fr	`1.0`	`FTS`	French Hunspell Dictionary
hunspell_ne_np	`1.0`	`FTS`	Nepali Hunspell Dictionary
hunspell_nl_nl	`1.0`	`FTS`	Dutch Hunspell Dictionary
hunspell_nn_no	`1.0`	`FTS`	Norwegian (norsk) Hunspell Dictionary
hunspell_pt_pt	`1.0`	`FTS`	Portuguese Hunspell Dictionary
hunspell_ru_ru	`1.0`	`FTS`	Russian Hunspell Dictionary
hunspell_ru_ru_aot	`1.0`	`FTS`	Russian Hunspell Dictionary (from AOT.ru group)
fuzzystrmatch	`1.2`	`FTS`	determine similarities and distance between strings
pg_trgm	`1.6`	`FTS`	text similarity measurement and index searching based on trigrams

OLAP

Extension	Version	Category	Description
citus	`14.0.0`	`OLAP`	Distributed PostgreSQL as an extension
citus_columnar	`14.0.0`	`OLAP`	Citus columnar storage engine
columnar	`1.1.2`	`OLAP`	Hydra Columnar extension
pg_analytics	`0.3.7`	`OLAP`	Postgres for analytics, powered by DuckDB
pg_duckdb	`1.1.1`	`OLAP`	DuckDB Embedded in Postgres
pg_mooncake	`0.2.0`	`OLAP`	Columnstore Table in Postgres
pg_clickhouse	`0.1.4`	`OLAP`	Interfaces to query ClickHouse databases from PostgreSQL
duckdb_fdw	`1.1.2`	`OLAP`	DuckDB Foreign Data Wrapper
pg_parquet	`0.5.1`	`OLAP`	copy data between Postgres and Parquet
pg_fkpart	`1.7.0`	`OLAP`	Table partitioning by foreign key utility
pg_partman	`5.4.2`	`OLAP`	Extension to manage partitioned tables by time or ID
plproxy	`2.11.0`	`OLAP`	Database partitioning implemented as procedural language
pg_strom	`6.1`	`OLAP`	PG-Strom - big-data processing acceleration using GPU and NVME
tablefunc	`1.0`	`OLAP`	functions that manipulate whole tables, including crosstab

FEAT

Extension	Version	Category	Description
age	`1.7.0`	`FEAT`	AGE graph database extension
hll	`2.19`	`FEAT`	type for storing hyperloglog data
rum	`1.3.15`	`FEAT`	RUM index access method
pg_ai_query	`0.1.1`	`FEAT`	AI-powered SQL query generation for PostgreSQL
pg_ttl_index	`2.0.0`	`FEAT`	Automatic data expiration with TTL indexes
pg_graphql	`1.5.12`	`FEAT`	Add in-database GraphQL support
pg_jsonschema	`0.3.4`	`FEAT`	PostgreSQL extension providing JSON Schema validation
jsquery	`1.2`	`FEAT`	data type for jsonb inspection
pg_hint_plan	`1.8.0`	`FEAT`	Give PostgreSQL ability to manually force some decisions in execution plans.
hypopg	`1.4.2`	`FEAT`	Hypothetical indexes for PostgreSQL
index_advisor	`0.2.0`	`FEAT`	Query index advisor
plan_filter	`0.0.1`	`FEAT`	filter statements by their execution plans.
imgsmlr	`1.0`	`FEAT`	Image similarity with haar
pg_ivm	`1.13`	`FEAT`	incremental view maintenance on PostgreSQL
pg_incremental	`1.4.1`	`FEAT`	Incremental Processing by Crunchy Data
pgmb	`1.0.0`	`FEAT`	A simple PostgreSQL Message Broker system
pgmq	`1.11.0`	`FEAT`	A lightweight message queue. Like AWS SQS and RSMQ but on Postgres.
pgq	`3.5.1`	`FEAT`	Generic queue for PostgreSQL
orioledb	`1.6`	`FEAT`	OrioleDB, the next generation transactional engine
pg_cardano	`1.1.1`	`FEAT`	A suite of Cardano-related tools
rdkit	`202503.1`	`FEAT`	Cheminformatics functionality for PostgreSQL.
omni	`0.2.14`	`FEAT`	Advanced adapter for Postgres extensions
omni_auth	`0.1.3`	`FEAT`	Basic session management
omni_aws	`0.1.2`	`FEAT`	Amazon Web Services APIs (S3)
omni_cloudevents	`0.1.0`	`FEAT`	CloudEvents support
omni_containers	`0.2.0`	`FEAT`	Docker container management
omni_credentials	`0.2.0`	`FEAT`	Application credential management
omni_csv	`0.1.1`	`FEAT`	CSV toolkit
omni_datasets	`0.1.0`	`FEAT`	Dataset provisioning
omni_email	`0.1.0`	`FEAT`	E-mail framework
omni_http	`0.1.0`	`FEAT`	Basic HTTP types
omni_httpc	`0.1.10`	`FEAT`	HTTP client
omni_httpd	`0.4.11`	`FEAT`	HTTP server
omni_id	`0.4.3`	`FEAT`	Identity types
omni_json	`0.1.1`	`FEAT`	JSON toolkit
omni_kube	`0.4.2`	`FEAT`	Kubernetes (k8s) integration
omni_ledger	`0.1.3`	`FEAT`	Financial ledger
omni_manifest	`0.1.2`	`FEAT`	Package installation manifests
omni_mimetypes	`0.1.0`	`FEAT`	MIME types
omni_os	`0.1.1`	`FEAT`	Operating system integration
omni_polyfill	`0.2.2`	`FEAT`	Postgres API polyfills
omni_python	`0.1.1`	`FEAT`	First-class Python support
omni_regex	`0.1.0`	`FEAT`	PCRE-compatible regular expressions
omni_rest	`0.1.1`	`FEAT`	REST API toolkit (with PostgREST support)
omni_schema	`0.3.0`	`FEAT`	Advanced schema management tooling
omni_seq	`0.1.1`	`FEAT`	Distributed integer sequences
omni_service	`0.1.0`	`FEAT`	Service management
omni_session	`0.2.0`	`FEAT`	Session management
omni_shmem	`0.1.0`	`FEAT`	Shared Memory Management
omni_sql	`0.5.3`	`FEAT`	Programmatic SQL manipulation
omni_sqlite	`0.2.2`	`FEAT`	Embedded SQLite
omni_test	`0.4.0`	`FEAT`	Testing framework
omni_txn	`0.5.0`	`FEAT`	Transaction management
omni_types	`0.3.6`	`FEAT`	Advanced types
omni_var	`0.3.0`	`FEAT`	Scoped variables
omni_vfs	`0.2.2`	`FEAT`	Virtual File System
omni_vfs_types_v1	`0.1.0`	`FEAT`	Virtual File System types (v1)
omni_web	`0.3.0`	`FEAT`	Common web stack primitives
omni_worker	`0.2.1`	`FEAT`	Generalized worker pool
omni_xml	`0.1.2`	`FEAT`	XML toolkit
omni_yaml	`0.1.0`	`FEAT`	YAML toolkit
bloom	`1.0`	`FEAT`	bloom access method - signature file based index

LANG

Extension	Version	Category	Description
pg_tle	`1.5.2`	`LANG`	Trusted Language Extensions for PostgreSQL
plv8	`3.2.4`	`LANG`	PL/JavaScript (v8) trusted procedural language
pljs	`1.0.5`	`LANG`	PL/JS trusted procedural language
pllua	`2.0.12`	`LANG`	Lua as a procedural language
hstore_pllua	`2.0.12`	`LANG`	Hstore transform for Lua
plluau	`2.0.12`	`LANG`	Lua as an untrusted procedural language
hstore_plluau	`2.0.12`	`LANG`	Hstore transform for untrusted Lua
plprql	`18.0.1`	`LANG`	Use PRQL in PostgreSQL - Pipelined Relational Query Language
pldbgapi	`1.9`	`LANG`	server-side support for debugging PL/pgSQL functions
plpgsql_check	`2.8.11`	`LANG`	extended check for plpgsql functions
plprofiler	`4.2.5`	`LANG`	server-side support for profiling PL/pgSQL functions
plsh	`1.20220917`	`LANG`	PL/sh procedural language
pljava	`1.6.10`	`LANG`	PL/Java procedural language
plr	`8.4.8`	`LANG`	load R interpreter and execute R script from within a database
plxslt	`0.20140221`	`LANG`	XSLT procedural language for PostgreSQL
pgtap	`1.3.4`	`LANG`	Unit testing for PostgreSQL
faker	`0.5.3`	`LANG`	Wrapper for the Faker Python library
dbt2	`0.61.7`	`LANG`	OSDL-DBT-2 test kit
pltcl	`1.0`	`LANG`	PL/Tcl procedural language
pltclu	`1.0`	`LANG`	PL/TclU untrusted procedural language
plperl	`1.0`	`LANG`	PL/Perl procedural language
bool_plperl	`1.0`	`LANG`	transform between bool and plperl
hstore_plperl	`1.0`	`LANG`	transform between hstore and plperl
jsonb_plperl	`1.0`	`LANG`	transform between jsonb and plperl
plperlu	`1.0`	`LANG`	PL/PerlU untrusted procedural language
bool_plperlu	`1.0`	`LANG`	transform between bool and plperlu
jsonb_plperlu	`1.0`	`LANG`	transform between jsonb and plperlu
hstore_plperlu	`1.0`	`LANG`	transform between hstore and plperlu
plpgsql	`1.0`	`LANG`	PL/pgSQL procedural language
plpython3u	`1.0`	`LANG`	PL/Python3U untrusted procedural language
jsonb_plpython3u	`1.0`	`LANG`	transform between jsonb and plpython3u
ltree_plpython3u	`1.0`	`LANG`	transform between ltree and plpython3u
hstore_plpython3u	`1.0`	`LANG`	transform between hstore and plpython3u

TYPE

Extension	Version	Category	Description
prefix	`1.2.10`	`TYPE`	Prefix Range module for PostgreSQL
semver	`0.41.0`	`TYPE`	Semantic version data type
unit	`7.10`	`TYPE`	SI units extension
pgpdf	`0.1.0`	`TYPE`	PDF type with meta admin & Full-Text Search
pglite_fusion	`0.0.6`	`TYPE`	Embed an SQLite database in your PostgreSQL table
md5hash	`1.0.1`	`TYPE`	type for storing 128-bit binary data inline
asn1oid	`1.6`	`TYPE`	asn1oid extension
roaringbitmap	`1.1.0`	`TYPE`	support for Roaring Bitmaps
pgfaceting	`0.2.0`	`TYPE`	fast faceting queries using an inverted index
pg_sphere	`1.5.2`	`TYPE`	spherical objects with useful functions, operators and index support
country	`0.0.3`	`TYPE`	Country data type, ISO 3166-1
pg_xenophile	`0.8.3`	`TYPE`	More than the bare necessities for PostgreSQL i18n and l10n.
l10n_table_dependent_extension	`0.8.3`	`TYPE`	PostgreSQL l10n toolbox
currency	`0.0.3`	`TYPE`	Custom PostgreSQL currency type in 1Byte
collection	`1.1.1`	`TYPE`	Memory optimized data type to be used inside of plpglsql func
pgmp	`1.0.5`	`TYPE`	Multiple Precision Arithmetic extension
numeral	`1.3`	`TYPE`	numeral datatypes extension
pg_rational	`0.0.2`	`TYPE`	bigint fractions
uint	`1.20250815`	`TYPE`	unsigned integer types
uint128	`1.2.0`	`TYPE`	Native uint128 type
hashtypes	`0.1.5`	`TYPE`	sha1, md5 and other data types for PostgreSQL
ip4r	`2.4.2`	`TYPE`	IPv4/v6 and IPv4/v6 range index type for PostgreSQL
pg_duration	`1.0.2`	`TYPE`	data type for representing durations
uri	`1.20251029`	`TYPE`	URI Data type for PostgreSQL
emailaddr	`0`	`TYPE`	Email address type for PostgreSQL
acl	`1.0.4`	`TYPE`	ACL Data type
debversion	`1.2.0`	`TYPE`	Debian version number data type
pg_rrule	`0.3.0`	`TYPE`	RRULE field type for PostgreSQL
timestamp9	`1.4.0`	`TYPE`	timestamp nanosecond resolution
chkpass	`1.0`	`TYPE`	data type for auto-encrypted passwords
isn	`1.2`	`TYPE`	data types for international product numbering standards
seg	`1.4`	`TYPE`	data type for representing line segments or floating-point intervals
cube	`1.5`	`TYPE`	data type for multidimensional cubes
ltree	`1.3`	`TYPE`	data type for hierarchical tree-like structures
hstore	`1.8`	`TYPE`	data type for storing sets of (key, value) pairs
citext	`1.6`	`TYPE`	data type for case-insensitive character strings
xml2	`1.1`	`TYPE`	XPath querying and XSLT

UTIL

Extension	Version	Category	Description
gzip	`1.0.0`	`UTIL`	gzip and gunzip functions.
bzip	`1.0.0`	`UTIL`	Bzip compression and decompression
zstd	`1.1.2`	`UTIL`	Zstandard compression algorithm implementation in PostgreSQL
http	`1.7.0`	`UTIL`	HTTP client for PostgreSQL, allows web page retrieval inside the database.
pg_net	`0.20.2`	`UTIL`	Async HTTP Requests
pg_curl	`2.4.5`	`UTIL`	Run curl actions for data transfer in URL syntax
pg_retry	`1.0.0`	`UTIL`	Retry SQL statements on transient errors with exponential backoff
pgjq	`0.1.0`	`UTIL`	Use jq in Postgres
pgjwt	`0.2.0`	`UTIL`	JSON Web Token API for Postgresql
pg_smtp_client	`0.2.1`	`UTIL`	PostgreSQL extension to send email using SMTP
pg_html5_email_address	`1.2.3`	`UTIL`	PostgreSQL email validation that is consistent with the HTML5 spec
url_encode	`1.2.5`	`UTIL`	url_encode, url_decode functions
pgsql_tweaks	`1.0.2`	`UTIL`	Some functions and views for daily usage
pg_extra_time	`2.0.0`	`UTIL`	Some date time functions and operators that,
pgpcre	`0.20190509`	`UTIL`	Perl Compatible Regular Expression functions
icu_ext	`1.10.0`	`UTIL`	Access ICU functions
pgqr	`1.0`	`UTIL`	QR Code generator from PostgreSQL
pg_protobuf	`1.0`	`UTIL`	Protobuf support for PostgreSQL
envvar	`1.0.1`	`UTIL`	Fetch the value of an environment variable
floatfile	`1.3.1`	`UTIL`	Simple file storage for arrays of floats
pg_render	`0.1.3`	`UTIL`	Render HTML in SQL
pg_readme	`0.7.0`	`UTIL`	Generate a README.md document for a database extension or schema
pg_readme_test_extension	`0.7.0`	`UTIL`	Test generating a README.md document for extension or schema
ddl_historization	`0.0.7`	`UTIL`	Historize the ddl changes inside PostgreSQL database
data_historization	`1.1.0`	`UTIL`	PLPGSQL Script to historize data in partitioned table
schedoc	`0.0.1`	`UTIL`	Cross documentation between Django and DBT projects
hashlib	`1.1`	`UTIL`	Stable hash functions for Postgres
xxhash	`0.0.1`	`UTIL`	xxhash functions for PostgreSQL
shacrypt	`1.1`	`UTIL`	Implements SHA256-CRYPT and SHA512-CRYPT password encryption schemes
cryptint	`1.0.0`	`UTIL`	Encryption functions for int and bigint values
pguecc	`1.0`	`UTIL`	uECC bindings for Postgres
sparql	`1.0`	`UTIL`	Query SPARQL datasource with SQL

FUNC

Extension	Version	Category	Description
pg_idkit	`0.4.0`	`FUNC`	multi-tool for generating new/niche universally unique identifiers (ex. UUIDv6, ULID, KSUID)
pgx_ulid	`0.2.2`	`FUNC`	ulid type and methods
pg_uuidv7	`1.7.0`	`FUNC`	Create UUIDv7 values in postgres
permuteseq	`1.2.2`	`FUNC`	Pseudo-randomly permute sequences with a format-preserving encryption on elements
pg_hashids	`1.3`	`FUNC`	Short unique id generator for PostgreSQL, using hashids
sequential_uuids	`1.0.3`	`FUNC`	generator of sequential UUIDs
typeid	`0.3.0`	`FUNC`	Allows to use TypeIDs in Postgres natively
snowflake	`2.4`	`FUNC`	Snowflake-style 64-bit ID generation and sequence utilities
topn	`2.7.0`	`FUNC`	type for top-n JSONB
quantile	`1.1.8`	`FUNC`	Quantile aggregation function
lower_quantile	`1.0.3`	`FUNC`	Lower quantile aggregate function
count_distinct	`3.0.2`	`FUNC`	An alternative to COUNT(DISTINCT …) aggregate, usable with HashAggregate
omnisketch	`1.0.2`	`FUNC`	data structure for on-line agg of data into approximate sketch
ddsketch	`1.0.1`	`FUNC`	Provides ddsketch aggregate function
vasco	`0.1.0`	`FUNC`	discover hidden correlations in your data with MIC
xicor	`0.1.0`	`FUNC`	XI Correlation Coefficient in Postgres
weighted_statistics	`1.0.0`	`FUNC`	High-performance weighted statistics functions for sparse data
tdigest	`1.4.3`	`FUNC`	Provides tdigest aggregate function.
first_last_agg	`0.1.4`	`FUNC`	first() and last() aggregate functions
extra_window_functions	`1.0`	`FUNC`	Extra Window Functions for PostgreSQL
floatvec	`1.1.1`	`FUNC`	Math for vectors (arrays) of numbers
aggs_for_vecs	`1.4.1`	`FUNC`	Aggregate functions for array inputs
aggs_for_arrays	`1.3.3`	`FUNC`	Various functions for computing statistics on arrays of numbers
pg_csv	`1.0.1`	`FUNC`	Flexible CSV processing for Postgres
arraymath	`1.1`	`FUNC`	Array math and operators that work element by element on the contents of arrays
pg_math	`1.1.0`	`FUNC`	GSL statistical functions for postgresql
random	`2.0.0`	`FUNC`	random data generator
base36	`1.0.0`	`FUNC`	Integer Base36 types
base62	`0.0.1`	`FUNC`	Base62 extension for PostgreSQL
pg_base58	`0.0.1`	`FUNC`	Base58 Encoder/Decoder Extension for PostgreSQL
financial	`1.0.1`	`FUNC`	Financial aggregate functions
convert	`0.1.0`	`FUNC`	conversion functions for spatial, routing and other specialized uses
refint	`1.0`	`FUNC`	functions for implementing referential integrity (obsolete)
autoinc	`1.0`	`FUNC`	functions for autoincrementing fields
insert_username	`1.0`	`FUNC`	functions for tracking who changed a table
moddatetime	`1.0`	`FUNC`	functions for tracking last modification time
tsm_system_time	`1.0`	`FUNC`	TABLESAMPLE method which accepts time in milliseconds as a limit
dict_xsyn	`1.0`	`FUNC`	text search dictionary template for extended synonym processing
tsm_system_rows	`1.0`	`FUNC`	TABLESAMPLE method which accepts number of rows as a limit
tcn	`1.0`	`FUNC`	Triggered change notifications
uuid-ossp	`1.1`	`FUNC`	generate universally unique identifiers (UUIDs)
btree_gist	`1.7`	`FUNC`	support for indexing common datatypes in GiST
btree_gin	`1.3`	`FUNC`	support for indexing common datatypes in GIN
intarray	`1.5`	`FUNC`	functions, operators, and index support for 1-D arrays of integers
intagg	`1.1`	`FUNC`	integer aggregator and enumerator (obsolete)
dict_int	`1.0`	`FUNC`	text search dictionary template for integers
unaccent	`1.1`	`FUNC`	text search dictionary that removes accents

ADMIN

Extension	Version	Category	Description
pg_repack	`1.5.3`	`ADMIN`	Reorganize tables in PostgreSQL databases with minimal locks
pg_rewrite	`2.1.0`	`ADMIN`	Tool allows read write to the table during the rewriting
pg_squeeze	`1.9.1`	`ADMIN`	A tool to remove unused space from a relation.
pg_dirtyread	`2.7`	`ADMIN`	Read dead but unvacuumed rows from table
pgfincore	`1.3.1`	`ADMIN`	examine and manage the os buffer cache
pg_cooldown	`0.1`	`ADMIN`	remove buffered pages for specific relations
ddlx	`0.30`	`ADMIN`	DDL eXtractor functions
pglinter	`1.1.1`	`ADMIN`	PostgreSQL Linting and Analysis Extension
prioritize	`1.0.4`	`ADMIN`	get and set the priority of PostgreSQL backends
pg_checksums	`1.3`	`ADMIN`	Activate/deactivate/verify checksums in offline Postgres clusters
pg_readonly	`1.0.4`	`ADMIN`	cluster database read only
pgdd	`0.6.1`	`ADMIN`	Introspect pg data dictionary via standard SQL
pg_permissions	`1.4`	`ADMIN`	view object permissions and compare them with the desired state
pgautofailover	`2.2`	`ADMIN`	pg_auto_failover
pg_catcheck	`1.6.0`	`ADMIN`	Diagnosing system catalog corruption
pre_prepare	`0.9`	`ADMIN`	Pre Prepare your Statement server side
pg_upless	`0.0.3`	`ADMIN`	Detect Useless UPDATE
pgcozy	`1.0`	`ADMIN`	Pre-warming shared buffers according to previous pg_buffercache snapshots for PostgreSQL.
pg_orphaned	`1.0`	`ADMIN`	Deal with orphaned files
pg_crash	`1.0`	`ADMIN`	Send random signals to random processes
pg_cheat_funcs	`1.0`	`ADMIN`	Provides cheat (but useful) functions
fio	`1.0`	`ADMIN`	PostgreSQL File I/O Functions
qos	`1.0`	`ADMIN`	PostgreSQL QoS resource governance extension (session & query throttling/isolation)
pg_savior	`0.0.1`	`ADMIN`	Postgres extension to save OOPS mistakes
safeupdate	`1.5`	`ADMIN`	Require criteria for UPDATE and DELETE
pg_strict	`1.0.2`	`ADMIN`	Prevent dangerous UPDATE and DELETE without WHERE clause
pg_drop_events	`0.1.0`	`ADMIN`	logs transaction ids of drop table, drop column, drop materialized view statements
table_log	`0.6.4`	`ADMIN`	record table modification logs and PITR for table/row
pgagent	`4.2.3`	`ADMIN`	A PostgreSQL job scheduler
pg_prewarm	`1.2`	`ADMIN`	prewarm relation data
pgpool_adm	`4.7.1`	`ADMIN`	Administrative functions for pgPool
pgpool_recovery	`4.7.1`	`ADMIN`	recovery functions for pgpool-II for V4.3
pgpool_regclass	`4.7.1`	`ADMIN`	replacement for regclass
lo	`1.1`	`ADMIN`	Large Object maintenance
basic_archive	`-`	`ADMIN`	an example of an archive module
basebackup_to_shell	`-`	`ADMIN`	adds a custom basebackup target called shell
old_snapshot	`1.0`	`ADMIN`	utilities in support of old_snapshot_threshold
adminpack	`2.1`	`ADMIN`	administrative functions for PostgreSQL
amcheck	`1.4`	`ADMIN`	functions for verifying relation integrity
pg_surgery	`1.0`	`ADMIN`	extension to perform surgery on a damaged relation

STAT

Extension	Version	Category	Description
pg_profile	`4.11`	`STAT`	PostgreSQL load profile repository and report builder
pg_tracing	`0.1.3`	`STAT`	Distributed Tracing for PostgreSQL
pg_show_plans	`2.1.7`	`STAT`	show query plans of all currently running SQL statements
pg_stat_kcache	`2.3.1`	`STAT`	Kernel statistics gathering
pg_stat_monitor	`2.3.2`	`STAT`	The pg_stat_monitor is a PostgreSQL Query Performance Monitoring tool, based on PostgreSQL contrib module pg_stat_statements. pg_stat_monitor provides aggregated statistics, client information, plan details including plan, and histogram information.
pg_qualstats	`2.1.3`	`STAT`	An extension collecting statistics about quals
pg_store_plans	`1.9`	`STAT`	track plan statistics of all SQL statements executed
pg_track_settings	`2.1.2`	`STAT`	Track settings changes
pg_track_optimizer	`0.9.1`	`STAT`	Track planning decisions in comparison with execution reality
pg_wait_sampling	`1.1.9`	`STAT`	sampling based statistics of wait events
pgsentinel	`1.4.0`	`STAT`	active session history
system_stats	`3.2`	`STAT`	EnterpriseDB system statistics for PostgreSQL
meta	`0.4.0`	`STAT`	Normalized, friendlier system catalog for PostgreSQL
pgnodemx	`1.7`	`STAT`	Capture node OS metrics via SQL queries
pg_proctab	`1.7`	`STAT`	PostgreSQL extension to access the OS process table
pg_sqlog	`1.6`	`STAT`	Provide SQL interface to logs
bgw_replstatus	`1.0.8`	`STAT`	Small PostgreSQL background worker to report whether a node is a replication master or standby
pgmeminfo	`1.0.0`	`STAT`	show memory usage
toastinfo	`1.5`	`STAT`	show details on toasted datums
explain_ui	`0.0.2`	`STAT`	easily jump into a visual plan UI for any SQL query
pg_relusage	`0.0.1`	`STAT`	Log all the queries that reference a particular column
pagevis	`0.1`	`STAT`	Visualise database pages in ascii code
powa	`5.1.1`	`STAT`	PostgreSQL Workload Analyser-core
pg_overexplain	`1.0`	`STAT`	Allow EXPLAIN to dump even more details
pg_logicalinspect	`1.0`	`STAT`	Logical decoding components inspection
pageinspect	`1.12`	`STAT`	inspect the contents of database pages at a low level
pgrowlocks	`1.2`	`STAT`	show row-level locking information
sslinfo	`1.2`	`STAT`	information about SSL certificates
pg_buffercache	`1.5`	`STAT`	examine the shared buffer cache
pg_walinspect	`1.1`	`STAT`	functions to inspect contents of PostgreSQL Write-Ahead Log
pg_freespacemap	`1.2`	`STAT`	examine the free space map (FSM)
pg_visibility	`1.2`	`STAT`	examine the visibility map (VM) and page-level visibility info
pgstattuple	`1.5`	`STAT`	show tuple-level statistics
auto_explain	`-`	`STAT`	Provides a means for logging execution plans of slow statements automatically
pg_stat_statements	`1.11`	`STAT`	track planning and execution statistics of all SQL statements executed

SEC

Extension	Version	Category	Description
passwordcheck_cracklib	`3.1.0`	`SEC`	Strengthen PostgreSQL user password checks with cracklib
supautils	`3.1.0`	`SEC`	Extension that secures a cluster on a cloud environment
pgsodium	`3.1.9`	`SEC`	Postgres extension for libsodium functions
supabase_vault	`0.3.1`	`SEC`	Supabase Vault Extension
pg_session_jwt	`0.4.0`	`SEC`	Manage authentication sessions using JWTs
anon	`3.0.1`	`SEC`	PostgreSQL Anonymizer (anon) extension
pgsmcrypto	`0.1.1`	`SEC`	PostgreSQL SM Algorithm Extension
pg_enigma	`0.5.0`	`SEC`	Encrypted postgres data type
pgaudit	`18.0`	`SEC`	provides auditing functionality
pgauditlogtofile	`1.8.0`	`SEC`	pgAudit addon to redirect audit log to an independent file
pg_auditor	`0.2`	`SEC`	Audit data changes and provide flashback ability
logerrors	`2.1.5`	`SEC`	Function for collecting statistics about messages in logfile
pg_auth_mon	`3.0`	`SEC`	monitor connection attempts per user
pg_jobmon	`1.4.1`	`SEC`	Extension for logging and monitoring functions in PostgreSQL
credcheck	`4.6`	`SEC`	credcheck - postgresql plain text credential checker
pgcryptokey	`0.85`	`SEC`	cryptographic key management
pg_pwhash	`1.0`	`SEC`	Advanced password hashing methods for PostgreSQL
login_hook	`1.7`	`SEC`	login_hook - hook to execute login_hook.login() at login time
set_user	`4.2.0`	`SEC`	similar to SET ROLE but with added logging
pg_snakeoil	`1.4`	`SEC`	The PostgreSQL Antivirus
pgextwlist	`1.19`	`SEC`	PostgreSQL Extension Whitelisting
sslutils	`1.4`	`SEC`	A Postgres extension for managing SSL certificates through SQL
noset	`0.3.0`	`SEC`	Module for blocking SET variables for non-super users.
pg_tde	`2.1`	`SEC`	Percona pg_tde access method
sepgsql	`-`	`SEC`	label-based mandatory access control (MAC) based on SELinux security policy.
auth_delay	`-`	`SEC`	pause briefly before reporting authentication failure
pgcrypto	`1.3`	`SEC`	cryptographic functions
passwordcheck	`-`	`SEC`	checks user passwords and reject weak password

FDW

Extension	Version	Category	Description
wrappers	`0.5.7`	`FDW`	Foreign data wrappers developed by Supabase
multicorn	`3.2`	`FDW`	Fetch foreign data in Python in your PostgreSQL server.
odbc_fdw	`0.5.1`	`FDW`	Foreign data wrapper for accessing remote databases using ODBC
jdbc_fdw	`0.4.0`	`FDW`	foreign-data wrapper for remote servers available over JDBC
pgspider_ext	`1.3.0`	`FDW`	foreign-data wrapper for remote PGSpider servers
mysql_fdw	`2.9.3`	`FDW`	Foreign data wrapper for querying a MySQL server
oracle_fdw	`2.8.0`	`FDW`	foreign data wrapper for Oracle access
tds_fdw	`2.0.5`	`FDW`	Foreign data wrapper for querying a TDS database (Sybase or Microsoft SQL Server)
db2_fdw	`18.1.1`	`FDW`	foreign data wrapper for DB2 access
sqlite_fdw	`2.5.0`	`FDW`	SQLite Foreign Data Wrapper
pgbouncer_fdw	`1.4.0`	`FDW`	Extension for querying PgBouncer stats from normal SQL views & running pgbouncer commands from normal SQL functions
etcd_fdw	`0.0.0`	`FDW`	Foreign data wrapper for etcd
informix_fdw	`0.6.3`	`FDW`	Foreign data wrapper for Informix access
nominatim_fdw	`1.1.0`	`FDW`	Nominatim Foreign Data Wrapper for PostgreSQL
mongo_fdw	`5.5.3`	`FDW`	foreign data wrapper for MongoDB access
redis_fdw	`1.0`	`FDW`	Foreign data wrapper for querying a Redis server
redis	`0.0.1`	`FDW`	Send redis pub/sub messages to Redis from PostgreSQL Directly
kafka_fdw	`0.0.3`	`FDW`	kafka Foreign Data Wrapper for CSV formatted messages
hdfs_fdw	`2.3.3`	`FDW`	foreign-data wrapper for remote hdfs servers
firebird_fdw	`1.4.1`	`FDW`	Foreign data wrapper for Firebird
aws_s3	`0.0.1`	`FDW`	aws_s3 postgres extension to import/export data from/to s3
log_fdw	`1.4`	`FDW`	foreign-data wrapper for Postgres log file access
dblink	`1.2`	`FDW`	connect to other PostgreSQL databases from within a database
file_fdw	`1.0`	`FDW`	foreign-data wrapper for flat file access
postgres_fdw	`1.1`	`FDW`	foreign-data wrapper for remote PostgreSQL servers

SIM

Extension	Version	Category	Description
documentdb	`0.109`	`SIM`	API surface for DocumentDB for PostgreSQL
documentdb_core	`0.109`	`SIM`	Core API surface for DocumentDB for PostgreSQL
documentdb_distributed	`0.109`	`SIM`	Multi-Node API surface for DocumentDB
documentdb_extended_rum	`0.109`	`SIM`	DocumentDB Extended RUM index access method
orafce	`4.16.4`	`SIM`	Functions and operators that emulate a subset of functions and packages from the Oracle RDBMS
pgtt	`4.4`	`SIM`	Extension to add Global Temporary Tables feature to PostgreSQL
session_variable	`3.4`	`SIM`	Registration and manipulation of session variables and constants
pg_statement_rollback	`1.5`	`SIM`	Server side rollback at statement level for PostgreSQL like Oracle or DB2
ivorysql_ora	`1.0`	`SIM`	Oracle compatibility extension
ora_btree_gin	`1.0`	`SIM`	GIN index support for Oracle data types
ora_btree_gist	`1.0`	`SIM`	GiST index support for Oracle data types
pg_get_functiondef	`1.0`	`SIM`	Get function definition
plisql	`1.0`	`SIM`	PL/iSQL procedural language
gb18030_2022	`1.0`	`SIM`	Support GB18030-2022 to UTF-8 encoding conversion
pg_dbms_metadata	`1.0.0`	`SIM`	Extension to add Oracle DBMS_METADATA compatibility to PostgreSQL
pg_dbms_lock	`1.0`	`SIM`	Extension to add Oracle DBMS_LOCK full compatibility to PostgreSQL
pg_dbms_job	`1.5`	`SIM`	Extension to add Oracle DBMS_JOB full compatibility to PostgreSQL
pg_dbms_errlog	`2.2`	`SIM`	Emulate DBMS_ERRLOG Oracle module to log DML errors in a dedicated table.
pg_utl_smtp	`1.0.0`	`SIM`	Oracle UTL_SMTP compatibility extension for PostgreSQL
babelfishpg_common	`5.5.0`	`SIM`	SQL Server Transact SQL Datatype Support
babelfishpg_tsql	`5.5.0`	`SIM`	SQL Server Transact SQL compatibility
babelfishpg_tds	`1.0.0`	`SIM`	SQL Server TDS protocol extension
babelfishpg_money	`1.1.0`	`SIM`	SQL Server Money Data Type
spat	`0.1.0a4`	`SIM`	Redis-like In-Memory DB Embedded in Postgres
pgmemcache	`2.3.0`	`SIM`	memcached interface
aux_mysql	`1.5`	`SIM`	MySQL compatibility auxiliary extension module

ETL

Extension	Version	Category	Description
pglogical	`2.4.6`	`ETL`	PostgreSQL Logical Replication
pglogical_origin	`2.4.6`	`ETL`	Dummy extension for compatibility when upgrading from Postgres 9.4
pglogical_ticker	`1.4.1`	`ETL`	Have an accurate view on pglogical replication delay
pgl_ddl_deploy	`2.2.1`	`ETL`	automated ddl deployment using pglogical
pg_failover_slots	`1.2.0`	`ETL`	PG Failover Slots extension
db_migrator	`1.0.0`	`ETL`	Tools to migrate other databases to PostgreSQL
pgactive	`2.1.7`	`ETL`	Active-Active Replication Extension for PostgreSQL
spock	`5.0.5`	`ETL`	Multi-master logical replication extension for PostgreSQL
lolor	`1.2.2`	`ETL`	Extension to make PostgreSQL large objects compatible with logical replication
wal2json	`2.6`	`ETL`	Changing data capture in JSON format
wal2mongo	`1.0.7`	`ETL`	PostgreSQL logical decoding output plugin for MongoDB
decoderbufs	`3.4.1`	`ETL`	Logical decoding plugin that delivers WAL stream changes using a Protocol Buffer format
decoder_raw	`1.0`	`ETL`	Output plugin for logical replication in Raw SQL format
mimeo	`1.5.1`	`ETL`	Extension for specialized, per-table replication between PostgreSQL instances
repmgr	`5.5.0`	`ETL`	Replication manager for PostgreSQL
pg_fact_loader	`2.0.1`	`ETL`	build fact tables with Postgres
pg_bulkload	`3.1.23`	`ETL`	pg_bulkload is a high speed data loading utility for PostgreSQL
test_decoding	`-`	`ETL`	SQL-based test/example module for WAL logical decoding
pgoutput	`-`	`ETL`	Logical Replication output plugin

Module: PGSQL

Mon, 01 Jan 0001 00:00:00 +0000

The world’s most advanced open-source relational database!

Pigsty brings it to full potential: batteries-included, reliable, observable, maintainable, and scalable! Config | Admin | Playbooks | Dashboards | Parameters

Overview

Learn key topics and concepts about PostgreSQL.

Config

Describe your desired PostgreSQL cluster

Identity Params: Define identity params for a PostgreSQL cluster
Primary Instance: Create single-instance “cluster” with one primary
Replica Instance: Create basic HA cluster with one primary and one replica
Offline Instance: Create special read-only instance for OLAP/ETL/interactive queries
Sync Standby: Enable sync commit to ensure zero data loss
Quorum Commit: Use quorum sync commit for higher consistency level
Standby Cluster: Clone existing cluster and keep in sync (DR cluster)
Delayed Cluster: Clone existing cluster with delayed replay for emergency recovery
Citus Cluster: Define and create Citus distributed database cluster
Major Version: Deploy cluster with different PostgreSQL major version

Admin

Manage your PostgreSQL clusters.

Core Concepts

Mon, 01 Jan 0001 00:00:00 +0000

Core concepts and architecture design

Configuration

Mon, 01 Jan 0001 00:00:00 +0000

Pigsty is a “configuration-driven” PostgreSQL platform: all behaviors come from the combination of inventory files in ~/pigsty/conf/*.yml and PGSQL parameters. Once you’ve written the configuration, you can replicate a customized cluster with instances, users, databases, access control, extensions, and tuning policies in just a few minutes.

Configuration Entry

Prepare Inventory: Copy a pigsty/conf/*.yml template or write an Ansible Inventory from scratch, placing cluster groups (all.children.<cls>.hosts) and global variables (all.vars) in the same file.
Define Parameters: Override the required PGSQL parameters in the vars block. The override order from global → cluster → host determines the final value.
Apply Configuration: Run ./configure -c <conf> or bin/pgsql-add <cls> and other playbooks to apply the configuration. Pigsty will generate the configuration files needed for Patroni/pgbouncer/pgbackrest based on the parameters.

Pigsty’s default demo inventory conf/pgsql.yml is a minimal example: one pg-meta cluster, global pg_version: 18, and a few business user and database definitions. You can expand with more clusters from this base.

Service/Access

Mon, 01 Jan 0001 00:00:00 +0000

Split read and write operations, route traffic correctly, and reliably deliver PostgreSQL cluster capabilities.

Service is an abstraction: it is the form in which database clusters provide capabilities externally, encapsulating the details of the underlying cluster.

Service is critical for stable access in production environments, showing its value during high availability cluster automatic failovers. Personal users typically don’t need to worry about this concept.

Personal User

The concept of “service” is for production environments. Personal users/single-machine clusters can skip the complexity and directly access the database using instance names/IP addresses.

Access Control

Mon, 01 Jan 0001 00:00:00 +0000

Pigsty provides a battery-included access control model based on role system and privilege system.

Access control is crucial, yet many users struggle to implement it properly. Therefore, Pigsty provides a streamlined, battery-included access control model to provide a safety net for your cluster security.

Role System

Pigsty’s default role system includes four default roles and four default users:

Role Name	Attributes	Member of	Description
`dbrole_readonly`	`NOLOGIN`		role for global read-only access
`dbrole_readwrite`	`NOLOGIN`	dbrole_readonly	role for global read-write access
`dbrole_admin`	`NOLOGIN`	pg_monitor,dbrole_readwrite	role for admin/object creation
`dbrole_offline`	`NOLOGIN`		role for restricted read-only access
`postgres`	`SUPERUSER`		system superuser
`replicator`	`REPLICATION`	pg_monitor,dbrole_readonly	system replicator
`dbuser_dba`	`SUPERUSER`	dbrole_admin	pgsql admin user
`dbuser_monitor`		pg_monitor	pgsql monitor user

The detailed definitions of these roles and users are as follows:

Service / Access

Mon, 01 Jan 0001 00:00:00 +0000

Separate read and write operations, route traffic correctly, and deliver PostgreSQL cluster capabilities reliably.

Service is an abstraction: it is the form in which database clusters provide capabilities to the outside world and encapsulates the details of the underlying cluster.

Services are critical for stable access in production environments and show their value when high availability clusters automatically fail over. Single-node users typically don’t need to worry about this concept.

Single-Node Users

The concept of “service” is for production environments. Personal users/single-node clusters can simply access the database directly using instance name/IP address.

Administration

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Database administration and operation tasks

Administration

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User / Role

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In this context, users refer to logical objects within a database cluster created using the SQL commands CREATE USER/ROLE.

In PostgreSQL, users belong directly to the database cluster rather than to a specific database. Therefore, when creating business databases and business users, you should follow the principle of “users first, then databases.”

Defining Users

Pigsty defines roles and users in database clusters through two configuration parameters:

pg_default_roles: Defines globally unified roles and users
pg_users: Defines business users and roles at the database cluster level

The former defines roles and users shared across the entire environment, while the latter defines business roles and users specific to individual clusters. Both have the same format and are arrays of user definition objects.

Database

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In this context, Database refers to the logical object created using the SQL command CREATE DATABASE within a database cluster.

A PostgreSQL server can serve multiple databases simultaneously. In Pigsty, you can define the required databases in the cluster configuration.

Pigsty will modify and customize the default template database template1, creating default schemas, installing default extensions, and configuring default privileges. Newly created databases will inherit these settings from template1 by default.

Authentication / HBA

Mon, 01 Jan 0001 00:00:00 +0000

Detailed explanation of Host-Based Authentication (HBA) in Pigsty.

Authentication is the foundation of Access Control and the Privilege System. PostgreSQL has multiple authentication methods.

Here we mainly introduce HBA: Host Based Authentication. HBA rules define which users can access which databases from which locations and in which ways.

Client Authentication

To connect to a PostgreSQL database, users must first be authenticated (password is used by default).

You can provide the password in the connection string (not secure), or pass it using the PGPASSWORD environment variable or .pgpass file. Refer to the psql documentation and PostgreSQL Connection Strings for more details.

Access Control

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Pigsty provides a battery-included access control model based on a role system and privilege system.

Access control is important, but many users don’t do it well. Therefore, Pigsty provides a simplified, ready-to-use access control model to provide a security baseline for your cluster.

Role System

Pigsty’s default role system includes four default roles and four default users:

Role Name	Attributes	Member of	Description
`dbrole_readonly`	`NOLOGIN`		role for global read-only access
`dbrole_readwrite`	`NOLOGIN`	dbrole_readonly	role for global read-write access
`dbrole_admin`	`NOLOGIN`	pg_monitor,dbrole_readwrite	role for object creation
`dbrole_offline`	`NOLOGIN`		role for restricted read-only access
`postgres`	`SUPERUSER`		system superuser
`replicator`	`REPLICATION`	pg_monitor,dbrole_readonly	system replicator
`dbuser_dba`	`SUPERUSER`	dbrole_admin	pgsql admin user
`dbuser_monitor`		pg_monitor	pgsql monitor user

The detailed definitions of these roles and users are as follows:

Troubleshooting

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This document lists potential failures in PostgreSQL and Pigsty, as well as SOPs for locating, handling, and analyzing issues.

Disk Space Exhausted

Disk space exhaustion is the most common type of failure.

Symptoms

When the disk space where the database resides is exhausted, PostgreSQL will not work normally and may exhibit the following symptoms: database logs repeatedly report “no space left on device” errors, new data cannot be written, and PostgreSQL may even trigger a PANIC and force shutdown.

Data Migration

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Pigsty includes a built-in playbook pgsql-migration.yml that implements online database migration based on logical replication.

With pre-generated automation scripts, application downtime can be reduced to just a few seconds. However, note that logical replication requires PostgreSQL 10 or later to work.

Of course, if you have sufficient downtime budget, you can always use the pg_dump | psql approach for offline migration.

Defining Migration Tasks

To use Pigsty’s online migration playbook, you need to create a definition file that describes the migration task details.

Tutorials

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This section provides step-by-step tutorials for common PostgreSQL tasks and scenarios.

Citus Cluster: Deploy and manage Citus distributed clusters
Disaster Drill: Emergency recovery when 2 of 3 nodes fail
PG VIP: Configure L2 VIP for PostgreSQL clusters

Reference

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Parameters and reference documentation

Monitoring

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This document introduces Pigsty’s monitoring system architecture, including metrics, logs, and target management. It also covers how to monitor existing PG clusters and remote RDS services.

Monitoring Overview

Pigsty uses a modern observability stack for PostgreSQL monitoring:

Grafana for metrics visualization and PostgreSQL datasource
VictoriaMetrics for collecting metrics from PostgreSQL / Pgbouncer / Patroni / HAProxy / Node
VictoriaLogs for logging PostgreSQL / Pgbouncer / Patroni / pgBackRest and host component logs
Battery-included Grafana dashboards showcasing all aspects of PostgreSQL

Metrics

Dashboard

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Pigsty provides numerous out-of-the-box Grafana monitoring dashboards for PostgreSQL: Demo & Gallery.

Pigsty has 26 PostgreSQL-related monitoring dashboards, organized by hierarchy into Overview, Cluster, Instance, and Database categories, and by data source into PGSQL, PGCAT, and PGLOG categories.

Overview

Overview	Cluster	Instance	Database
PGSQL Overview	PGSQL Cluster	PGSQL Instance	PGSQL Database
PGSQL Alert	PGRDS Cluster	PGRDS Instance	PGCAT Database
PGSQL Shard	PGSQL Activity	PGCAT Instance	PGSQL Tables
	PGSQL Replication	PGSQL Persist	PGSQL Table
	PGSQL Service	PGSQL Proxy	PGCAT Table
	PGSQL Databases	PGSQL Pgbouncer	PGSQL Query
	PGSQL Patroni	PGSQL Session	PGCAT Query
	PGSQL PITR	PGSQL Xacts	PGCAT Locks
		PGSQL Exporter	PGCAT Schema

Overview

Dashboards

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Pigsty provides many out-of-the-box Grafana monitoring dashboards for PostgreSQL: Demo & Gallery.

There are 26 PostgreSQL-related monitoring dashboards in Pigsty, organized hierarchically into Overview, Cluster, Instance, and Database categories, and by data source into PGSQL, PGCAT, and PGLOG categories.

Overview

Overview	Cluster	Instance	Database
PGSQL Overview	PGSQL Cluster	PGSQL Instance	PGSQL Database
PGSQL Alert	PGRDS Cluster	PGRDS Instance	PGCAT Database
PGSQL Shard	PGSQL Activity	PGCAT Instance	PGSQL Tables
	PGSQL Replication	PGSQL Persist	PGSQL Table
	PGSQL Service	PGSQL Proxy	PGCAT Table
	PGSQL Databases	PGSQL Pgbouncer	PGSQL Query
	PGSQL Patroni	PGSQL Session	PGCAT Query
	PGSQL PITR	PGSQL Xacts	PGCAT Locks
		PGSQL Exporter	PGCAT Schema

Overview

Metrics

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The PGSQL module provides 638 available monitoring metrics.

Metric Name	Type	Labels	Description
ALERTS	Unknown	`category`, `job`, `level`, `ins`, `severity`, `ip`, `alertname`, `alertstate`, `instance`, `cls`	N/A
ALERTS_FOR_STATE	Unknown	`category`, `job`, `level`, `ins`, `severity`, `ip`, `alertname`, `instance`, `cls`	N/A
cls:pressure1	Unknown	`job`, `cls`	N/A
cls:pressure15	Unknown	`job`, `cls`	N/A
cls:pressure5	Unknown	`job`, `cls`	N/A
go_gc_duration_seconds	summary	`job`, `ins`, `ip`, `instance`, `quantile`, `cls`	A summary of the pause duration of garbage collection cycles.
go_gc_duration_seconds_count	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
go_gc_duration_seconds_sum	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
go_goroutines	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of goroutines that currently exist.
go_info	gauge	`version`, `job`, `ins`, `ip`, `instance`, `cls`	Information about the Go environment.
go_memstats_alloc_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes allocated and still in use.
go_memstats_alloc_bytes_total	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total number of bytes allocated, even if freed.
go_memstats_buck_hash_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes used by the profiling bucket hash table.
go_memstats_frees_total	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total number of frees.
go_memstats_gc_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes used for garbage collection system metadata.
go_memstats_heap_alloc_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of heap bytes allocated and still in use.
go_memstats_heap_idle_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of heap bytes waiting to be used.
go_memstats_heap_inuse_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of heap bytes that are in use.
go_memstats_heap_objects	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of allocated objects.
go_memstats_heap_released_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of heap bytes released to OS.
go_memstats_heap_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of heap bytes obtained from system.
go_memstats_last_gc_time_seconds	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of seconds since 1970 of last garbage collection.
go_memstats_lookups_total	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total number of pointer lookups.
go_memstats_mallocs_total	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total number of mallocs.
go_memstats_mcache_inuse_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes in use by mcache structures.
go_memstats_mcache_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes used for mcache structures obtained from system.
go_memstats_mspan_inuse_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes in use by mspan structures.
go_memstats_mspan_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes used for mspan structures obtained from system.
go_memstats_next_gc_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of heap bytes when next garbage collection will take place.
go_memstats_other_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes used for other system allocations.
go_memstats_stack_inuse_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes in use by the stack allocator.
go_memstats_stack_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes obtained from system for stack allocator.
go_memstats_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes obtained from system.
go_threads	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of OS threads created.
ins:pressure1	Unknown	`job`, `ins`, `ip`, `cls`	N/A
ins:pressure15	Unknown	`job`, `ins`, `ip`, `cls`	N/A
ins:pressure5	Unknown	`job`, `ins`, `ip`, `cls`	N/A
patroni_cluster_unlocked	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if the cluster is unlocked, 0 if locked.
patroni_dcs_last_seen	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Epoch timestamp when DCS was last contacted successfully by Patroni.
patroni_failsafe_mode_is_active	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if failsafe mode is active, 0 if inactive.
patroni_is_paused	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if auto failover is disabled, 0 otherwise.
patroni_master	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if this node is the leader, 0 otherwise.
patroni_pending_restart	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if the node needs a restart, 0 otherwise.
patroni_postgres_in_archive_recovery	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if Postgres is replicating from archive, 0 otherwise.
patroni_postgres_running	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if Postgres is running, 0 otherwise.
patroni_postgres_server_version	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Version of Postgres (if running), 0 otherwise.
patroni_postgres_streaming	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if Postgres is streaming, 0 otherwise.
patroni_postgres_timeline	counter	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Postgres timeline of this node (if running), 0 otherwise.
patroni_postmaster_start_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Epoch seconds since Postgres started.
patroni_primary	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if this node is the leader, 0 otherwise.
patroni_replica	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if this node is a replica, 0 otherwise.
patroni_standby_leader	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if this node is the standby_leader, 0 otherwise.
patroni_sync_standby	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if this node is a sync standby replica, 0 otherwise.
patroni_up	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
patroni_version	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Patroni semver without periods.
patroni_xlog_location	counter	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Current location of the Postgres transaction log, 0 if this node is not the leader.
patroni_xlog_paused	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if the Postgres xlog is paused, 0 otherwise.
patroni_xlog_received_location	counter	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Current location of the received Postgres transaction log, 0 if this node is not a replica.
patroni_xlog_replayed_location	counter	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Current location of the replayed Postgres transaction log, 0 if this node is not a replica.
patroni_xlog_replayed_timestamp	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Current timestamp of the replayed Postgres transaction log, 0 if null.
pg:cls:active_backends	Unknown	`job`, `cls`	N/A
pg:cls:active_time_rate15m	Unknown	`job`, `cls`	N/A
pg:cls:active_time_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:active_time_rate5m	Unknown	`job`, `cls`	N/A
pg:cls:age	Unknown	`job`, `cls`	N/A
pg:cls:buf_alloc_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:buf_clean_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:buf_flush_backend_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:buf_flush_checkpoint_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:cpu_count	Unknown	`job`, `cls`	N/A
pg:cls:cpu_usage	Unknown	`job`, `cls`	N/A
pg:cls:cpu_usage_15m	Unknown	`job`, `cls`	N/A
pg:cls:cpu_usage_1m	Unknown	`job`, `cls`	N/A
pg:cls:cpu_usage_5m	Unknown	`job`, `cls`	N/A
pg:cls:db_size	Unknown	`job`, `cls`	N/A
pg:cls:file_size	Unknown	`job`, `cls`	N/A
pg:cls:ixact_backends	Unknown	`job`, `cls`	N/A
pg:cls:ixact_time_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:lag_bytes	Unknown	`job`, `cls`	N/A
pg:cls:lag_seconds	Unknown	`job`, `cls`	N/A
pg:cls:leader	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:cls:load1	Unknown	`job`, `cls`	N/A
pg:cls:load15	Unknown	`job`, `cls`	N/A
pg:cls:load5	Unknown	`job`, `cls`	N/A
pg:cls:lock_count	Unknown	`job`, `cls`	N/A
pg:cls:locks	Unknown	`job`, `cls`, `mode`	N/A
pg:cls:log_size	Unknown	`job`, `cls`	N/A
pg:cls:lsn_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:members	Unknown	`job`, `ins`, `ip`, `cls`	N/A
pg:cls:num_backends	Unknown	`job`, `cls`	N/A
pg:cls:partition	Unknown	`job`, `cls`	N/A
pg:cls:receiver	Unknown	`state`, `slot_name`, `job`, `appname`, `ip`, `cls`, `sender_host`, `sender_port`	N/A
pg:cls:rlock_count	Unknown	`job`, `cls`	N/A
pg:cls:saturation1	Unknown	`job`, `cls`	N/A
pg:cls:saturation15	Unknown	`job`, `cls`	N/A
pg:cls:saturation5	Unknown	`job`, `cls`	N/A
pg:cls:sender	Unknown	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `cls`	N/A
pg:cls:session_time_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:size	Unknown	`job`, `cls`	N/A
pg:cls:slot_count	Unknown	`job`, `cls`	N/A
pg:cls:slot_retained_bytes	Unknown	`job`, `cls`	N/A
pg:cls:standby_count	Unknown	`job`, `cls`	N/A
pg:cls:sync_state	Unknown	`job`, `cls`	N/A
pg:cls:timeline	Unknown	`job`, `cls`	N/A
pg:cls:tup_deleted_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:tup_fetched_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:tup_inserted_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:tup_modified_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:tup_returned_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:wal_size	Unknown	`job`, `cls`	N/A
pg:cls:xact_commit_rate15m	Unknown	`job`, `cls`	N/A
pg:cls:xact_commit_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:xact_commit_rate5m	Unknown	`job`, `cls`	N/A
pg:cls:xact_rollback_rate15m	Unknown	`job`, `cls`	N/A
pg:cls:xact_rollback_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:xact_rollback_rate5m	Unknown	`job`, `cls`	N/A
pg:cls:xact_total_rate15m	Unknown	`job`, `cls`	N/A
pg:cls:xact_total_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:xact_total_sigma15m	Unknown	`job`, `cls`	N/A
pg:cls:xlock_count	Unknown	`job`, `cls`	N/A
pg:db:active_backends	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:active_time_rate15m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:active_time_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:active_time_rate5m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:age	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:age_deriv1h	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:age_exhaust	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blk_io_time_seconds_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blk_read_time_seconds_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blk_write_time_seconds_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blks_access_1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blks_hit_1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blks_hit_ratio1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blks_read_1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:conn_limit	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:conn_usage	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:db_size	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:ixact_backends	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:ixact_time_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:lock_count	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:num_backends	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:rlock_count	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:session_time_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:temp_bytes_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:temp_files_1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:tup_deleted_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:tup_fetched_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:tup_inserted_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:tup_modified_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:tup_returned_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:wlock_count	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_commit_rate15m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_commit_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_commit_rate5m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_rollback_rate15m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_rollback_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_rollback_rate5m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_total_rate15m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_total_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_total_rate5m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_total_sigma15m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xlock_count	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:env:active_backends	Unknown	`job`	N/A
pg:env:active_time_rate15m	Unknown	`job`	N/A
pg:env:active_time_rate1m	Unknown	`job`	N/A
pg:env:active_time_rate5m	Unknown	`job`	N/A
pg:env:age	Unknown	`job`	N/A
pg:env:cpu_count	Unknown	`job`	N/A
pg:env:cpu_usage	Unknown	`job`	N/A
pg:env:cpu_usage_15m	Unknown	`job`	N/A
pg:env:cpu_usage_1m	Unknown	`job`	N/A
pg:env:cpu_usage_5m	Unknown	`job`	N/A
pg:env:ixact_backends	Unknown	`job`	N/A
pg:env:ixact_time_rate1m	Unknown	`job`	N/A
pg:env:lag_bytes	Unknown	`job`	N/A
pg:env:lag_seconds	Unknown	`job`	N/A
pg:env:lsn_rate1m	Unknown	`job`	N/A
pg:env:session_time_rate1m	Unknown	`job`	N/A
pg:env:tup_deleted_rate1m	Unknown	`job`	N/A
pg:env:tup_fetched_rate1m	Unknown	`job`	N/A
pg:env:tup_inserted_rate1m	Unknown	`job`	N/A
pg:env:tup_modified_rate1m	Unknown	`job`	N/A
pg:env:tup_returned_rate1m	Unknown	`job`	N/A
pg:env:xact_commit_rate15m	Unknown	`job`	N/A
pg:env:xact_commit_rate1m	Unknown	`job`	N/A
pg:env:xact_commit_rate5m	Unknown	`job`	N/A
pg:env:xact_rollback_rate15m	Unknown	`job`	N/A
pg:env:xact_rollback_rate1m	Unknown	`job`	N/A
pg:env:xact_rollback_rate5m	Unknown	`job`	N/A
pg:env:xact_total_rate15m	Unknown	`job`	N/A
pg:env:xact_total_rate1m	Unknown	`job`	N/A
pg:env:xact_total_sigma15m	Unknown	`job`	N/A
pg:ins:active_backends	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:active_time_rate15m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:active_time_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:active_time_rate5m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:age	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:blks_hit_ratio1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:buf_alloc_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:buf_clean_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:buf_flush_backend_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:buf_flush_checkpoint_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:ckpt_1h	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:ckpt_req_1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:ckpt_timed_1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:conn_limit	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:conn_usage	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:cpu_count	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:cpu_usage	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:cpu_usage_15m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:cpu_usage_1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:cpu_usage_5m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:db_size	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:file_size	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:fs_size	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:is_leader	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:ixact_backends	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:ixact_time_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:lag_bytes	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:lag_seconds	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:load1	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:load15	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:load5	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:lock_count	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:locks	Unknown	`job`, `ins`, `ip`, `mode`, `instance`, `cls`	N/A
pg:ins:log_size	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:lsn_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:mem_size	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:num_backends	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:rlock_count	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:saturation1	Unknown	`job`, `ins`, `ip`, `cls`	N/A
pg:ins:saturation15	Unknown	`job`, `ins`, `ip`, `cls`	N/A
pg:ins:saturation5	Unknown	`job`, `ins`, `ip`, `cls`	N/A
pg:ins:session_time_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:slot_retained_bytes	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:space_usage	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:status	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:sync_state	Unknown	`job`, `ins`, `instance`, `cls`	N/A
pg:ins:target_count	Unknown	`job`, `cls`, `ins`	N/A
pg:ins:timeline	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:tup_deleted_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:tup_fetched_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:tup_inserted_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:tup_modified_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:tup_returned_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:wal_size	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:wlock_count	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_commit_rate15m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_commit_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_commit_rate5m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_rollback_rate15m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_rollback_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_rollback_rate5m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_total_rate15m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_total_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_total_rate5m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_total_sigma15m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xlock_count	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:query:call_rate1m	Unknown	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:query:rt_1m	Unknown	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:table:scan_rate1m	Unknown	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg_activity_count	gauge	`datname`, `state`, `job`, `ins`, `ip`, `instance`, `cls`	Count of connection among (datname,state)
pg_activity_max_conn_duration	gauge	`datname`, `state`, `job`, `ins`, `ip`, `instance`, `cls`	Max backend session duration since state change among (datname, state)
pg_activity_max_duration	gauge	`datname`, `state`, `job`, `ins`, `ip`, `instance`, `cls`	Max duration since last state change among (datname, state)
pg_activity_max_tx_duration	gauge	`datname`, `state`, `job`, `ins`, `ip`, `instance`, `cls`	Max transaction duration since state change among (datname, state)
pg_archiver_failed_count	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of failed attempts for archiving WAL files
pg_archiver_finish_count	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of WAL files that have been successfully archived
pg_archiver_last_failed_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Time of the last failed archival operation
pg_archiver_last_finish_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Time of the last successful archive operation
pg_archiver_reset_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Time at which archive statistics were last reset
pg_backend_count	gauge	`type`, `job`, `ins`, `ip`, `instance`, `cls`	Database backend process count by backend_type
pg_bgwriter_buffers_alloc	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of buffers allocated
pg_bgwriter_buffers_backend	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of buffers written directly by a backend
pg_bgwriter_buffers_backend_fsync	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of times a backend had to execute its own fsync call
pg_bgwriter_buffers_checkpoint	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of buffers written during checkpoints
pg_bgwriter_buffers_clean	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of buffers written by the background writer
pg_bgwriter_checkpoint_sync_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total amount of time that has been spent in the portion of checkpoint processing where files are synchronized to disk, in seconds
pg_bgwriter_checkpoint_write_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total amount of time that has been spent in the portion of checkpoint processing where files are written to disk, in seconds
pg_bgwriter_checkpoints_req	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of requested checkpoints that have been performed
pg_bgwriter_checkpoints_timed	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of scheduled checkpoints that have been performed
pg_bgwriter_maxwritten_clean	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of times the background writer stopped a cleaning scan because it had written too many buffers
pg_bgwriter_reset_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Time at which bgwriter statistics were last reset
pg_boot_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`	unix timestamp when postmaster boot
pg_checkpoint_checkpoint_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint location
pg_checkpoint_elapse	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Seconds elapsed since latest checkpoint in seconds
pg_checkpoint_full_page_writes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s full_page_writes enabled
pg_checkpoint_newest_commit_ts_xid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s newestCommitTsXid
pg_checkpoint_next_multi_offset	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s NextMultiOffset
pg_checkpoint_next_multixact_id	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s NextMultiXactId
pg_checkpoint_next_oid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s NextOID
pg_checkpoint_next_xid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s NextXID xid
pg_checkpoint_next_xid_epoch	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s NextXID epoch
pg_checkpoint_oldest_active_xid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s oldestActiveXID
pg_checkpoint_oldest_commit_ts_xid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s oldestCommitTsXid
pg_checkpoint_oldest_multi_dbid	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s oldestMulti’s DB OID
pg_checkpoint_oldest_multi_xid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s oldestMultiXid
pg_checkpoint_oldest_xid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s oldestXID
pg_checkpoint_oldest_xid_dbid	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s oldestXID’s DB OID
pg_checkpoint_prev_tli	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s PrevTimeLineID
pg_checkpoint_redo_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s REDO location
pg_checkpoint_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Time of latest checkpoint
pg_checkpoint_tli	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s TimeLineID
pg_conf_reload_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds since last configuration reload
pg_db_active_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent executing SQL statements in this database, in seconds
pg_db_age	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Age of database calculated from datfrozenxid
pg_db_allow_conn	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	If false(0) then no one can connect to this database.
pg_db_blk_read_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent reading data file blocks by backends in this database, in seconds
pg_db_blk_write_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent writing data file blocks by backends in this database, in seconds
pg_db_blks_access	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times disk blocks that accessed read+hit
pg_db_blks_hit	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times disk blocks were found already in the buffer cache
pg_db_blks_read	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of disk blocks read in this database
pg_db_cks_fail_time	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time at which the last data page checksum failure was detected in this database
pg_db_cks_fails	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of data page checksum failures detected in this database, -1 for not enabled
pg_db_confl_confl_bufferpin	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of queries in this database that have been canceled due to pinned buffers
pg_db_confl_confl_deadlock	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of queries in this database that have been canceled due to deadlocks
pg_db_confl_confl_lock	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of queries in this database that have been canceled due to lock timeouts
pg_db_confl_confl_snapshot	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of queries in this database that have been canceled due to old snapshots
pg_db_confl_confl_tablespace	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of queries in this database that have been canceled due to dropped tablespaces
pg_db_conflicts	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of queries canceled due to conflicts with recovery in this database
pg_db_conn_limit	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Sets maximum number of concurrent connections that can be made to this database. -1 means no limit.
pg_db_datid	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	OID of the database
pg_db_deadlocks	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of deadlocks detected in this database
pg_db_frozen_xid	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	All transaction IDs before this one have been frozened
pg_db_is_template	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	If true(1), then this database can be cloned by any user with CREATEDB privileges
pg_db_ixact_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent idling while in a transaction in this database, in seconds
pg_db_numbackends	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of backends currently connected to this database
pg_db_reset_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time at which database statistics were last reset
pg_db_session_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent by database sessions in this database, in seconds
pg_db_sessions	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of sessions established to this database
pg_db_sessions_abandoned	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of database sessions to this database that were terminated because connection to the client was lost
pg_db_sessions_fatal	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of database sessions to this database that were terminated by fatal errors
pg_db_sessions_killed	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of database sessions to this database that were terminated by operator intervention
pg_db_temp_bytes	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total amount of data written to temporary files by queries in this database.
pg_db_temp_files	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of temporary files created by queries in this database
pg_db_tup_deleted	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows deleted by queries in this database
pg_db_tup_fetched	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows fetched by queries in this database
pg_db_tup_inserted	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows inserted by queries in this database
pg_db_tup_modified	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows modified by queries in this database
pg_db_tup_returned	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows returned by queries in this database
pg_db_tup_updated	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows updated by queries in this database
pg_db_xact_commit	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of transactions in this database that have been committed
pg_db_xact_rollback	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of transactions in this database that have been rolled back
pg_db_xact_total	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of transactions in this database
pg_downstream_count	gauge	`state`, `job`, `ins`, `ip`, `instance`, `cls`	Count of corresponding state
pg_exporter_agent_up	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg_exporter_last_scrape_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds exporter spending on scrapping
pg_exporter_query_cache_ttl	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	times to live of query cache
pg_exporter_query_scrape_duration	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	seconds query spending on scrapping
pg_exporter_query_scrape_error_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	times the query failed
pg_exporter_query_scrape_hit_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	numbers been scrapped from this query
pg_exporter_query_scrape_metric_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	numbers of metrics been scrapped from this query
pg_exporter_query_scrape_total_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	times exporter server was scraped for metrics
pg_exporter_scrape_duration	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds exporter spending on scrapping
pg_exporter_scrape_error_count	counter	`job`, `ins`, `ip`, `instance`, `cls`	times exporter was scraped for metrics and failed
pg_exporter_scrape_total_count	counter	`job`, `ins`, `ip`, `instance`, `cls`	times exporter was scraped for metrics
pg_exporter_server_scrape_duration	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	seconds exporter server spending on scrapping
pg_exporter_server_scrape_error_count	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg_exporter_server_scrape_total_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	times exporter server was scraped for metrics
pg_exporter_server_scrape_total_seconds	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	seconds exporter server spending on scrapping
pg_exporter_up	gauge	`job`, `ins`, `ip`, `instance`, `cls`	always be 1 if your could retrieve metrics
pg_exporter_uptime	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds since exporter primary server inited
pg_flush_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	primary only, location of current wal syncing
pg_func_calls	counter	`datname`, `funcname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times this function has been called
pg_func_self_time	counter	`datname`, `funcname`, `job`, `ins`, `ip`, `instance`, `cls`	Total time spent in this function itself, not including other functions called by it, in ms
pg_func_total_time	counter	`datname`, `funcname`, `job`, `ins`, `ip`, `instance`, `cls`	Total time spent in this function and all other functions called by it, in ms
pg_in_recovery	gauge	`job`, `ins`, `ip`, `instance`, `cls`	server is in recovery mode? 1 for yes 0 for no
pg_index_idx_blks_hit	counter	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Number of buffer hits in this index
pg_index_idx_blks_read	counter	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Number of disk blocks read from this index
pg_index_idx_scan	counter	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Number of index scans initiated on this index
pg_index_idx_tup_fetch	counter	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Number of live table rows fetched by simple index scans using this index
pg_index_idx_tup_read	counter	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Number of index entries returned by scans on this index
pg_index_relpages	gauge	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Size of the on-disk representation of this index in pages
pg_index_reltuples	gauge	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Estimate relation tuples
pg_insert_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	primary only, location of current wal inserting
pg_io_evictions	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Number of times a block has been written out from a shared or local buffer
pg_io_extend_time	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Time spent in extend operations in seconds
pg_io_extends	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Number of relation extend operations, each of the size specified in op_bytes.
pg_io_fsync_time	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Time spent in fsync operations in seconds
pg_io_fsyncs	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Number of fsync calls. These are only tracked in context normal
pg_io_hits	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	The number of times a desired block was found in a shared buffer.
pg_io_op_bytes	gauge	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	The number of bytes per unit of I/O read, written, or extended. 8192 by default
pg_io_read_time	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Time spent in read operations in seconds
pg_io_reads	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Number of read operations, each of the size specified in op_bytes.
pg_io_reset_time	gauge	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Timestamp at which these statistics were last reset
pg_io_reuses	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	The number of times an existing buffer in reused
pg_io_write_time	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Time spent in write operations in seconds
pg_io_writeback_time	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Time spent in writeback operations in seconds
pg_io_writebacks	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Number of units of size op_bytes which the process requested the kernel write out to permanent storage.
pg_io_writes	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Number of write operations, each of the size specified in op_bytes.
pg_is_in_recovery	gauge	`job`, `ins`, `ip`, `instance`, `cls`	1 if in recovery mode
pg_is_wal_replay_paused	gauge	`job`, `ins`, `ip`, `instance`, `cls`	1 if wal play paused
pg_lag	gauge	`job`, `ins`, `ip`, `instance`, `cls`	replica only, replication lag in seconds
pg_last_replay_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`	time when last transaction been replayed
pg_lock_count	gauge	`datname`, `job`, `ins`, `ip`, `mode`, `instance`, `cls`	Number of locks of corresponding mode and database
pg_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	log sequence number, current write location
pg_meta_info	gauge	`cls`, `extensions`, `version`, `job`, `ins`, `primary_conninfo`, `conf_path`, `hba_path`, `ip`, `cluster_id`, `instance`, `listen_port`, `wal_level`, `ver_num`, `cluster_name`, `data_dir`	constant 1
pg_query_calls	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times the statement was executed
pg_query_exec_time	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total time spent executing the statement, in seconds
pg_query_io_time	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total time the statement spent reading and writing blocks, in seconds
pg_query_rows	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of rows retrieved or affected by the statement
pg_query_sblk_dirtied	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of shared blocks dirtied by the statement
pg_query_sblk_hit	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of shared block cache hits by the statement
pg_query_sblk_read	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of shared blocks read by the statement
pg_query_sblk_written	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of shared blocks written by the statement
pg_query_wal_bytes	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total amount of WAL bytes generated by the statement
pg_receive_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	replica only, location of wal synced to disk
pg_recovery_backup_end_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	Backup end location
pg_recovery_backup_start_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	Backup start location
pg_recovery_min_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	Minimum recovery ending location
pg_recovery_min_timeline	counter	`job`, `ins`, `ip`, `instance`, `cls`	Min recovery ending loc’s timeline
pg_recovery_prefetch_block_distance	gauge	`job`, `ins`, `ip`, `instance`, `cls`	How many blocks ahead the prefetcher is looking
pg_recovery_prefetch_hit	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks not prefetched because they were already in the buffer pool
pg_recovery_prefetch_io_depth	gauge	`job`, `ins`, `ip`, `instance`, `cls`	How many prefetches have been initiated but are not yet known to have completed
pg_recovery_prefetch_prefetch	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks prefetched because they were not in the buffer pool
pg_recovery_prefetch_reset_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Time at which these recovery prefetch statistics were last reset
pg_recovery_prefetch_skip_fpw	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks not prefetched because a full page image was included in the WAL
pg_recovery_prefetch_skip_init	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks not prefetched because they would be zero-initialized
pg_recovery_prefetch_skip_new	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks not prefetched because they didn’t exist yet
pg_recovery_prefetch_skip_rep	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks not prefetched because they were already recently prefetched
pg_recovery_prefetch_wal_distance	gauge	`job`, `ins`, `ip`, `instance`, `cls`	How many bytes ahead the prefetcher is looking
pg_recovery_require_record	gauge	`job`, `ins`, `ip`, `instance`, `cls`	End-of-backup record required
pg_recv_flush_lsn	counter	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Last write-ahead log location already received and flushed to disk
pg_recv_flush_tli	counter	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Timeline number of last write-ahead log location received and flushed to disk
pg_recv_init_lsn	counter	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	First write-ahead log location used when WAL receiver is started
pg_recv_init_tli	counter	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	First timeline number used when WAL receiver is started
pg_recv_msg_recv_time	gauge	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Receipt time of last message received from origin WAL sender
pg_recv_msg_send_time	gauge	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Send time of last message received from origin WAL sender
pg_recv_pid	gauge	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Process ID of the WAL receiver process
pg_recv_reported_lsn	counter	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Last write-ahead log location reported to origin WAL sender
pg_recv_reported_time	gauge	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Time of last write-ahead log location reported to origin WAL sender
pg_recv_time	gauge	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Time of current snapshot
pg_recv_write_lsn	counter	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Last write-ahead log location already received and written to disk, but not flushed.
pg_relkind_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`, `relkind`	Number of relations of corresponding relkind
pg_repl_backend_xmin	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	This standby’s xmin horizon reported by hot_standby_feedback.
pg_repl_client_port	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	TCP port number that the client is using for communication with this WAL sender, or -1 if a Unix socket is used
pg_repl_flush_diff	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last log position flushed to disk by this standby server diff with current lsn
pg_repl_flush_lag	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Time elapsed between flushing recent WAL locally and receiving notification that this standby server has written and flushed it
pg_repl_flush_lsn	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last write-ahead log location flushed to disk by this standby server
pg_repl_launch_time	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Time when this process was started, i.e., when the client connected to this WAL sender
pg_repl_lsn	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Current log position on this server
pg_repl_replay_diff	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last log position replayed into the database on this standby server diff with current lsn
pg_repl_replay_lag	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Time elapsed between flushing recent WAL locally and receiving notification that this standby server has written, flushed and applied it
pg_repl_replay_lsn	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last write-ahead log location replayed into the database on this standby server
pg_repl_reply_time	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Send time of last reply message received from standby server
pg_repl_sent_diff	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last log position sent to this standby server diff with current lsn
pg_repl_sent_lsn	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last write-ahead log location sent on this connection
pg_repl_state	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Current WAL sender encoded state 0-4 for streaming startup catchup backup stopping
pg_repl_sync_priority	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Priority of this standby server for being chosen as the synchronous standby
pg_repl_sync_state	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Encoded synchronous state of this standby server, 0-3 for async potential sync quorum
pg_repl_time	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Current timestamp in unix epoch
pg_repl_write_diff	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last log position written to disk by this standby server diff with current lsn
pg_repl_write_lag	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Time elapsed between flushing recent WAL locally and receiving notification that this standby server has written it
pg_repl_write_lsn	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last write-ahead log location written to disk by this standby server
pg_replay_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	replica only, location of wal applied
pg_seq_blks_hit	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`, `seqname`	Number of buffer hits in this sequence
pg_seq_blks_read	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`, `seqname`	Number of disk blocks read from this sequence
pg_seq_last_value	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`, `seqname`	The last sequence value written to disk
pg_setting_block_size	gauge	`job`, `ins`, `ip`, `instance`, `cls`	pg page block size, 8192 by default
pg_setting_data_checksums	gauge	`job`, `ins`, `ip`, `instance`, `cls`	whether data checksum is enabled, 1 enabled 0 disabled
pg_setting_max_connections	gauge	`job`, `ins`, `ip`, `instance`, `cls`	number of concurrent connections to the database server
pg_setting_max_locks_per_transaction	gauge	`job`, `ins`, `ip`, `instance`, `cls`	no more than this many distinct objects can be locked at any one time
pg_setting_max_prepared_transactions	gauge	`job`, `ins`, `ip`, `instance`, `cls`	maximum number of transactions that can be in the prepared state simultaneously
pg_setting_max_replication_slots	gauge	`job`, `ins`, `ip`, `instance`, `cls`	maximum number of replication slots
pg_setting_max_wal_senders	gauge	`job`, `ins`, `ip`, `instance`, `cls`	maximum number of concurrent connections from standby servers
pg_setting_max_worker_processes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	maximum number of background processes that the system can support
pg_setting_wal_log_hints	gauge	`job`, `ins`, `ip`, `instance`, `cls`	whether wal_log_hints is enabled, 1 enabled 0 disabled
pg_size_bytes	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	File size in bytes
pg_slot_active	gauge	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	True(1) if this slot is currently actively being used
pg_slot_catalog_xmin	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	The oldest transaction affecting the system catalogs that this slot needs the database to retain.
pg_slot_confirm_lsn	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	The address (LSN) up to which the logical slot’s consumer has confirmed receiving data.
pg_slot_reset_time	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	When statistics were last reset
pg_slot_restart_lsn	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	The address (LSN) of oldest WAL which still might be required by the consumer of this slot
pg_slot_retained_bytes	gauge	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Size of bytes that retained for this slot
pg_slot_safe_wal_size	gauge	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	bytes that can be written to WAL which will not make slot into lost
pg_slot_spill_bytes	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Bytes that spilled to disk due to logical decode mem exceeding
pg_slot_spill_count	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Xacts that spilled to disk due to logical decode mem exceeding (a xact can be spilled multiple times)
pg_slot_spill_txns	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Xacts that spilled to disk due to logical decode mem exceeding (subtrans included)
pg_slot_stream_bytes	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Bytes that streamed to decoding output plugin after mem exceed
pg_slot_stream_count	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Xacts that streamed to decoding output plugin after mem exceed (a xact can be streamed multiple times)
pg_slot_stream_txns	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Xacts that streamed to decoding output plugin after mem exceed
pg_slot_temporary	gauge	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	True(1) if this is a temporary replication slot.
pg_slot_total_bytes	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Number of decoded bytes sent to the decoding output plugin for this slot
pg_slot_total_txns	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Number of decoded xacts sent to the decoding output plugin for this slot
pg_slot_wal_status	gauge	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	WAL reserve status 0-3 means reserved,extended,unreserved,lost, -1 means other
pg_slot_xmin	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	The oldest transaction that this slot needs the database to retain.
pg_slru_blks_exists	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks checked for existence for this SLRU
pg_slru_blks_hit	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of times disk blocks were found already in the SLRU, so that a read was not necessary
pg_slru_blks_read	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of disk blocks read for this SLRU
pg_slru_blks_written	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of disk blocks written for this SLRU
pg_slru_blks_zeroed	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks zeroed during initializations
pg_slru_flushes	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of flushes of dirty data for this SLRU
pg_slru_reset_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Time at which these statistics were last reset
pg_slru_truncates	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of truncates for this SLRU
pg_ssl_disabled	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of client connection that does not use ssl
pg_ssl_enabled	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of client connection that use ssl
pg_sync_standby_enabled	gauge	`job`, `ins`, `ip`, `names`, `instance`, `cls`	Synchronous commit enabled, 1 if enabled, 0 if disabled
pg_table_age	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Age of this table in vacuum cycles
pg_table_analyze_count	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times this table has been manually analyzed
pg_table_autoanalyze_count	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times this table has been analyzed by the autovacuum daemon
pg_table_autovacuum_count	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times this table has been vacuumed by the autovacuum daemon
pg_table_frozenxid	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	All txid before this have been frozen on this table
pg_table_heap_blks_hit	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of buffer hits in this table
pg_table_heap_blks_read	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of disk blocks read from this table
pg_table_idx_blks_hit	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of buffer hits in all indexes on this table
pg_table_idx_blks_read	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of disk blocks read from all indexes on this table
pg_table_idx_scan	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of index scans initiated on this table
pg_table_idx_tup_fetch	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of live rows fetched by index scans
pg_table_kind	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Relation kind r/table/114
pg_table_n_dead_tup	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Estimated number of dead rows
pg_table_n_ins_since_vacuum	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Estimated number of rows inserted since this table was last vacuumed
pg_table_n_live_tup	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Estimated number of live rows
pg_table_n_mod_since_analyze	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Estimated number of rows modified since this table was last analyzed
pg_table_n_tup_del	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows deleted
pg_table_n_tup_hot_upd	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows HOT updated (i.e with no separate index update required)
pg_table_n_tup_ins	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows inserted
pg_table_n_tup_mod	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows modified (insert + update + delete)
pg_table_n_tup_newpage_upd	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows updated where the successor version goes onto a new heap page
pg_table_n_tup_upd	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows updated (includes HOT updated rows)
pg_table_ncols	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of columns in the table
pg_table_pages	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Size of the on-disk representation of this table in pages
pg_table_relid	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Relation oid of this table
pg_table_seq_scan	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of sequential scans initiated on this table
pg_table_seq_tup_read	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of live rows fetched by sequential scans
pg_table_size_bytes	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Total bytes of this table (including toast, index, toast index)
pg_table_size_indexsize	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Bytes of all related indexes of this table
pg_table_size_relsize	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Bytes of this table itself (main, vm, fsm)
pg_table_size_toastsize	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Bytes of toast tables of this table
pg_table_tbl_scan	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of scans initiated on this table
pg_table_tup_read	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of live rows fetched by scans
pg_table_tuples	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	All txid before this have been frozen on this table
pg_table_vacuum_count	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times this table has been manually vacuumed (not counting VACUUM FULL)
pg_timestamp	gauge	`job`, `ins`, `ip`, `instance`, `cls`	database current timestamp
pg_up	gauge	`job`, `ins`, `ip`, `instance`, `cls`	last scrape was able to connect to the server: 1 for yes, 0 for no
pg_uptime	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds since postmaster start
pg_version	gauge	`job`, `ins`, `ip`, `instance`, `cls`	server version number
pg_wait_count	gauge	`datname`, `job`, `ins`, `event`, `ip`, `instance`, `cls`	Count of WaitEvent on target database
pg_wal_buffers_full	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of times WAL data was written to disk because WAL buffers became full
pg_wal_bytes	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total amount of WAL generated in bytes
pg_wal_fpi	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total number of WAL full page images generated
pg_wal_records	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total number of WAL records generated
pg_wal_reset_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	When statistics were last reset
pg_wal_sync	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of times WAL files were synced to disk via issue_xlog_fsync request
pg_wal_sync_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total amount of time spent syncing WAL files to disk via issue_xlog_fsync request, in seconds
pg_wal_write	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of times WAL buffers were written out to disk via XLogWrite request.
pg_wal_write_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total amount of time spent writing WAL buffers to disk via XLogWrite request in seconds
pg_write_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	primary only, location of current wal writing
pg_xact_xmax	counter	`job`, `ins`, `ip`, `instance`, `cls`	First as-yet-unassigned txid. txid >= this are invisible.
pg_xact_xmin	counter	`job`, `ins`, `ip`, `instance`, `cls`	Earliest txid that is still active
pg_xact_xnum	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Current active transaction count
pgbouncer:cls:load1	Unknown	`job`, `cls`	N/A
pgbouncer:cls:load15	Unknown	`job`, `cls`	N/A
pgbouncer:cls:load5	Unknown	`job`, `cls`	N/A
pgbouncer:db:conn_usage	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:conn_usage_reserve	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:pool_current_conn	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:pool_disabled	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:pool_max_conn	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:pool_paused	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:pool_reserve_size	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:pool_size	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:ins:free_clients	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:free_servers	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:load1	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:load15	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:load5	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:login_clients	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:pool_databases	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:pool_users	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:pools	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:used_clients	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer_database_current_connections	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	Current number of connections for this database
pgbouncer_database_disabled	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	True(1) if this database is currently disabled, else 0
pgbouncer_database_max_connections	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	Maximum number of allowed connections for this database
pgbouncer_database_min_pool_size	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	Minimum number of server connections
pgbouncer_database_paused	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	True(1) if this database is currently paused, else 0
pgbouncer_database_pool_size	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	Maximum number of server connections
pgbouncer_database_reserve_pool	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	Maximum number of additional connections for this database
pgbouncer_exporter_agent_up	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer_exporter_last_scrape_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds exporter spending on scrapping
pgbouncer_exporter_query_cache_ttl	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	times to live of query cache
pgbouncer_exporter_query_scrape_duration	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	seconds query spending on scrapping
pgbouncer_exporter_query_scrape_error_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	times the query failed
pgbouncer_exporter_query_scrape_hit_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	numbers been scrapped from this query
pgbouncer_exporter_query_scrape_metric_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	numbers of metrics been scrapped from this query
pgbouncer_exporter_query_scrape_total_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	times exporter server was scraped for metrics
pgbouncer_exporter_scrape_duration	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds exporter spending on scrapping
pgbouncer_exporter_scrape_error_count	counter	`job`, `ins`, `ip`, `instance`, `cls`	times exporter was scraped for metrics and failed
pgbouncer_exporter_scrape_total_count	counter	`job`, `ins`, `ip`, `instance`, `cls`	times exporter was scraped for metrics
pgbouncer_exporter_server_scrape_duration	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	seconds exporter server spending on scrapping
pgbouncer_exporter_server_scrape_total_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	times exporter server was scraped for metrics
pgbouncer_exporter_server_scrape_total_seconds	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	seconds exporter server spending on scrapping
pgbouncer_exporter_up	gauge	`job`, `ins`, `ip`, `instance`, `cls`	always be 1 if your could retrieve metrics
pgbouncer_exporter_uptime	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds since exporter primary server inited
pgbouncer_in_recovery	gauge	`job`, `ins`, `ip`, `instance`, `cls`	server is in recovery mode? 1 for yes 0 for no
pgbouncer_list_items	gauge	`job`, `ins`, `ip`, `instance`, `list`, `cls`	Number of corresponding pgbouncer object
pgbouncer_pool_active_cancel_clients	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Client connections that have forwarded query cancellations to the server and are waiting for the server response.
pgbouncer_pool_active_cancel_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Server connections that are currently forwarding a cancel request
pgbouncer_pool_active_clients	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Client connections that are linked to server connection and can process queries
pgbouncer_pool_active_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Server connections that are linked to a client
pgbouncer_pool_cancel_clients	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Client connections that have not forwarded query cancellations to the server yet.
pgbouncer_pool_cancel_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	cancel requests have completed that were sent to cancel a query on this server
pgbouncer_pool_idle_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Server connections that are unused and immediately usable for client queries
pgbouncer_pool_login_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Server connections currently in the process of logging in
pgbouncer_pool_maxwait	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	How long the first(oldest) client in the queue has waited, in seconds, key metric
pgbouncer_pool_maxwait_us	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Microsecond part of the maximum waiting time.
pgbouncer_pool_tested_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Server connections that are currently running reset or check query
pgbouncer_pool_used_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Server connections that have been idle for more than server_check_delay (means have to run check query)
pgbouncer_pool_waiting_clients	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Client connections that have sent queries but have not yet got a server connection
pgbouncer_stat_avg_query_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Average queries per second in last stat period
pgbouncer_stat_avg_query_time	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Average query duration, in seconds
pgbouncer_stat_avg_recv	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Average received (from clients) bytes per second
pgbouncer_stat_avg_sent	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Average sent (to clients) bytes per second
pgbouncer_stat_avg_wait_time	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent by clients waiting for a server, in seconds (average per second).
pgbouncer_stat_avg_xact_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Average transactions per second in last stat period
pgbouncer_stat_avg_xact_time	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Average transaction duration, in seconds
pgbouncer_stat_total_query_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of SQL queries pooled by pgbouncer
pgbouncer_stat_total_query_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of seconds spent when executing queries
pgbouncer_stat_total_received	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total volume in bytes of network traffic received by pgbouncer
pgbouncer_stat_total_sent	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total volume in bytes of network traffic sent by pgbouncer
pgbouncer_stat_total_wait_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent by clients waiting for a server, in seconds
pgbouncer_stat_total_xact_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of SQL transactions pooled by pgbouncer
pgbouncer_stat_total_xact_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of seconds spent when in a transaction
pgbouncer_up	gauge	`job`, `ins`, `ip`, `instance`, `cls`	last scrape was able to connect to the server: 1 for yes, 0 for no
pgbouncer_version	gauge	`job`, `ins`, `ip`, `instance`, `cls`	server version number
process_cpu_seconds_total	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total user and system CPU time spent in seconds.
process_max_fds	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Maximum number of open file descriptors.
process_open_fds	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of open file descriptors.
process_resident_memory_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Resident memory size in bytes.
process_start_time_seconds	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Start time of the process since unix epoch in seconds.
process_virtual_memory_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Virtual memory size in bytes.
process_virtual_memory_max_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Maximum amount of virtual memory available in bytes.
promhttp_metric_handler_requests_in_flight	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Current number of scrapes being served.
promhttp_metric_handler_requests_total	counter	`code`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of scrapes by HTTP status code.
scrape_duration_seconds	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
scrape_samples_post_metric_relabeling	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
scrape_samples_scraped	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
scrape_series_added	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
up	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A

Metrics List

Mon, 01 Jan 0001 00:00:00 +0000

The PGSQL module contains 638 types of available monitoring metrics.

Metric Name	Type	Labels	Description
ALERTS	Unknown	`category`, `job`, `level`, `ins`, `severity`, `ip`, `alertname`, `alertstate`, `instance`, `cls`	N/A
ALERTS_FOR_STATE	Unknown	`category`, `job`, `level`, `ins`, `severity`, `ip`, `alertname`, `instance`, `cls`	N/A
cls:pressure1	Unknown	`job`, `cls`	N/A
cls:pressure15	Unknown	`job`, `cls`	N/A
cls:pressure5	Unknown	`job`, `cls`	N/A
go_gc_duration_seconds	summary	`job`, `ins`, `ip`, `instance`, `quantile`, `cls`	A summary of the pause duration of garbage collection cycles.
go_gc_duration_seconds_count	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
go_gc_duration_seconds_sum	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
go_goroutines	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of goroutines that currently exist.
go_info	gauge	`version`, `job`, `ins`, `ip`, `instance`, `cls`	Information about the Go environment.
go_memstats_alloc_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes allocated and still in use.
go_memstats_alloc_bytes_total	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total number of bytes allocated, even if freed.
go_memstats_buck_hash_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes used by the profiling bucket hash table.
go_memstats_frees_total	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total number of frees.
go_memstats_gc_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes used for garbage collection system metadata.
go_memstats_heap_alloc_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of heap bytes allocated and still in use.
go_memstats_heap_idle_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of heap bytes waiting to be used.
go_memstats_heap_inuse_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of heap bytes that are in use.
go_memstats_heap_objects	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of allocated objects.
go_memstats_heap_released_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of heap bytes released to OS.
go_memstats_heap_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of heap bytes obtained from system.
go_memstats_last_gc_time_seconds	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of seconds since 1970 of last garbage collection.
go_memstats_lookups_total	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total number of pointer lookups.
go_memstats_mallocs_total	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total number of mallocs.
go_memstats_mcache_inuse_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes in use by mcache structures.
go_memstats_mcache_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes used for mcache structures obtained from system.
go_memstats_mspan_inuse_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes in use by mspan structures.
go_memstats_mspan_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes used for mspan structures obtained from system.
go_memstats_next_gc_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of heap bytes when next garbage collection will take place.
go_memstats_other_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes used for other system allocations.
go_memstats_stack_inuse_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes in use by the stack allocator.
go_memstats_stack_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes obtained from system for stack allocator.
go_memstats_sys_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of bytes obtained from system.
go_threads	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of OS threads created.
ins:pressure1	Unknown	`job`, `ins`, `ip`, `cls`	N/A
ins:pressure15	Unknown	`job`, `ins`, `ip`, `cls`	N/A
ins:pressure5	Unknown	`job`, `ins`, `ip`, `cls`	N/A
patroni_cluster_unlocked	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if the cluster is unlocked, 0 if locked.
patroni_dcs_last_seen	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Epoch timestamp when DCS was last contacted successfully by Patroni.
patroni_failsafe_mode_is_active	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if failsafe mode is active, 0 if inactive.
patroni_is_paused	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if auto failover is disabled, 0 otherwise.
patroni_master	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if this node is the leader, 0 otherwise.
patroni_pending_restart	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if the node needs a restart, 0 otherwise.
patroni_postgres_in_archive_recovery	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if Postgres is replicating from archive, 0 otherwise.
patroni_postgres_running	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if Postgres is running, 0 otherwise.
patroni_postgres_server_version	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Version of Postgres (if running), 0 otherwise.
patroni_postgres_streaming	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if Postgres is streaming, 0 otherwise.
patroni_postgres_timeline	counter	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Postgres timeline of this node (if running), 0 otherwise.
patroni_postmaster_start_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Epoch seconds since Postgres started.
patroni_primary	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if this node is the leader, 0 otherwise.
patroni_replica	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if this node is a replica, 0 otherwise.
patroni_standby_leader	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if this node is the standby_leader, 0 otherwise.
patroni_sync_standby	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if this node is a sync standby replica, 0 otherwise.
patroni_up	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
patroni_version	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Patroni semver without periods.
patroni_xlog_location	counter	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Current location of the Postgres transaction log, 0 if this node is not the leader.
patroni_xlog_paused	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Value is 1 if the Postgres xlog is paused, 0 otherwise.
patroni_xlog_received_location	counter	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Current location of the received Postgres transaction log, 0 if this node is not a replica.
patroni_xlog_replayed_location	counter	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Current location of the replayed Postgres transaction log, 0 if this node is not a replica.
patroni_xlog_replayed_timestamp	gauge	`job`, `ins`, `ip`, `instance`, `cls`, `scope`	Current timestamp of the replayed Postgres transaction log, 0 if null.
pg:cls:active_backends	Unknown	`job`, `cls`	N/A
pg:cls:active_time_rate15m	Unknown	`job`, `cls`	N/A
pg:cls:active_time_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:active_time_rate5m	Unknown	`job`, `cls`	N/A
pg:cls:age	Unknown	`job`, `cls`	N/A
pg:cls:buf_alloc_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:buf_clean_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:buf_flush_backend_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:buf_flush_checkpoint_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:cpu_count	Unknown	`job`, `cls`	N/A
pg:cls:cpu_usage	Unknown	`job`, `cls`	N/A
pg:cls:cpu_usage_15m	Unknown	`job`, `cls`	N/A
pg:cls:cpu_usage_1m	Unknown	`job`, `cls`	N/A
pg:cls:cpu_usage_5m	Unknown	`job`, `cls`	N/A
pg:cls:db_size	Unknown	`job`, `cls`	N/A
pg:cls:file_size	Unknown	`job`, `cls`	N/A
pg:cls:ixact_backends	Unknown	`job`, `cls`	N/A
pg:cls:ixact_time_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:lag_bytes	Unknown	`job`, `cls`	N/A
pg:cls:lag_seconds	Unknown	`job`, `cls`	N/A
pg:cls:leader	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:cls:load1	Unknown	`job`, `cls`	N/A
pg:cls:load15	Unknown	`job`, `cls`	N/A
pg:cls:load5	Unknown	`job`, `cls`	N/A
pg:cls:lock_count	Unknown	`job`, `cls`	N/A
pg:cls:locks	Unknown	`job`, `cls`, `mode`	N/A
pg:cls:log_size	Unknown	`job`, `cls`	N/A
pg:cls:lsn_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:members	Unknown	`job`, `ins`, `ip`, `cls`	N/A
pg:cls:num_backends	Unknown	`job`, `cls`	N/A
pg:cls:partition	Unknown	`job`, `cls`	N/A
pg:cls:receiver	Unknown	`state`, `slot_name`, `job`, `appname`, `ip`, `cls`, `sender_host`, `sender_port`	N/A
pg:cls:rlock_count	Unknown	`job`, `cls`	N/A
pg:cls:saturation1	Unknown	`job`, `cls`	N/A
pg:cls:saturation15	Unknown	`job`, `cls`	N/A
pg:cls:saturation5	Unknown	`job`, `cls`	N/A
pg:cls:sender	Unknown	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `cls`	N/A
pg:cls:session_time_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:size	Unknown	`job`, `cls`	N/A
pg:cls:slot_count	Unknown	`job`, `cls`	N/A
pg:cls:slot_retained_bytes	Unknown	`job`, `cls`	N/A
pg:cls:standby_count	Unknown	`job`, `cls`	N/A
pg:cls:sync_state	Unknown	`job`, `cls`	N/A
pg:cls:timeline	Unknown	`job`, `cls`	N/A
pg:cls:tup_deleted_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:tup_fetched_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:tup_inserted_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:tup_modified_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:tup_returned_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:wal_size	Unknown	`job`, `cls`	N/A
pg:cls:xact_commit_rate15m	Unknown	`job`, `cls`	N/A
pg:cls:xact_commit_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:xact_commit_rate5m	Unknown	`job`, `cls`	N/A
pg:cls:xact_rollback_rate15m	Unknown	`job`, `cls`	N/A
pg:cls:xact_rollback_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:xact_rollback_rate5m	Unknown	`job`, `cls`	N/A
pg:cls:xact_total_rate15m	Unknown	`job`, `cls`	N/A
pg:cls:xact_total_rate1m	Unknown	`job`, `cls`	N/A
pg:cls:xact_total_sigma15m	Unknown	`job`, `cls`	N/A
pg:cls:xlock_count	Unknown	`job`, `cls`	N/A
pg:db:active_backends	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:active_time_rate15m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:active_time_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:active_time_rate5m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:age	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:age_deriv1h	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:age_exhaust	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blk_io_time_seconds_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blk_read_time_seconds_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blk_write_time_seconds_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blks_access_1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blks_hit_1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blks_hit_ratio1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:blks_read_1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:conn_limit	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:conn_usage	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:db_size	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:ixact_backends	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:ixact_time_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:lock_count	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:num_backends	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:rlock_count	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:session_time_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:temp_bytes_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:temp_files_1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:tup_deleted_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:tup_fetched_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:tup_inserted_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:tup_modified_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:tup_returned_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:wlock_count	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_commit_rate15m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_commit_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_commit_rate5m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_rollback_rate15m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_rollback_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_rollback_rate5m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_total_rate15m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_total_rate1m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_total_rate5m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xact_total_sigma15m	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:db:xlock_count	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:env:active_backends	Unknown	`job`	N/A
pg:env:active_time_rate15m	Unknown	`job`	N/A
pg:env:active_time_rate1m	Unknown	`job`	N/A
pg:env:active_time_rate5m	Unknown	`job`	N/A
pg:env:age	Unknown	`job`	N/A
pg:env:cpu_count	Unknown	`job`	N/A
pg:env:cpu_usage	Unknown	`job`	N/A
pg:env:cpu_usage_15m	Unknown	`job`	N/A
pg:env:cpu_usage_1m	Unknown	`job`	N/A
pg:env:cpu_usage_5m	Unknown	`job`	N/A
pg:env:ixact_backends	Unknown	`job`	N/A
pg:env:ixact_time_rate1m	Unknown	`job`	N/A
pg:env:lag_bytes	Unknown	`job`	N/A
pg:env:lag_seconds	Unknown	`job`	N/A
pg:env:lsn_rate1m	Unknown	`job`	N/A
pg:env:session_time_rate1m	Unknown	`job`	N/A
pg:env:tup_deleted_rate1m	Unknown	`job`	N/A
pg:env:tup_fetched_rate1m	Unknown	`job`	N/A
pg:env:tup_inserted_rate1m	Unknown	`job`	N/A
pg:env:tup_modified_rate1m	Unknown	`job`	N/A
pg:env:tup_returned_rate1m	Unknown	`job`	N/A
pg:env:xact_commit_rate15m	Unknown	`job`	N/A
pg:env:xact_commit_rate1m	Unknown	`job`	N/A
pg:env:xact_commit_rate5m	Unknown	`job`	N/A
pg:env:xact_rollback_rate15m	Unknown	`job`	N/A
pg:env:xact_rollback_rate1m	Unknown	`job`	N/A
pg:env:xact_rollback_rate5m	Unknown	`job`	N/A
pg:env:xact_total_rate15m	Unknown	`job`	N/A
pg:env:xact_total_rate1m	Unknown	`job`	N/A
pg:env:xact_total_sigma15m	Unknown	`job`	N/A
pg:ins:active_backends	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:active_time_rate15m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:active_time_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:active_time_rate5m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:age	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:blks_hit_ratio1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:buf_alloc_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:buf_clean_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:buf_flush_backend_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:buf_flush_checkpoint_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:ckpt_1h	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:ckpt_req_1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:ckpt_timed_1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:conn_limit	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:conn_usage	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:cpu_count	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:cpu_usage	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:cpu_usage_15m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:cpu_usage_1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:cpu_usage_5m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:db_size	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:file_size	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:fs_size	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:is_leader	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:ixact_backends	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:ixact_time_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:lag_bytes	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:lag_seconds	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:load1	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:load15	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:load5	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:lock_count	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:locks	Unknown	`job`, `ins`, `ip`, `mode`, `instance`, `cls`	N/A
pg:ins:log_size	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:lsn_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:mem_size	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:num_backends	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:rlock_count	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:saturation1	Unknown	`job`, `ins`, `ip`, `cls`	N/A
pg:ins:saturation15	Unknown	`job`, `ins`, `ip`, `cls`	N/A
pg:ins:saturation5	Unknown	`job`, `ins`, `ip`, `cls`	N/A
pg:ins:session_time_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:slot_retained_bytes	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:space_usage	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:status	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:sync_state	Unknown	`job`, `ins`, `instance`, `cls`	N/A
pg:ins:target_count	Unknown	`job`, `cls`, `ins`	N/A
pg:ins:timeline	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:tup_deleted_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:tup_fetched_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:tup_inserted_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:tup_modified_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:tup_returned_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:wal_size	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:wlock_count	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_commit_rate15m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_commit_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_commit_rate5m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_rollback_rate15m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_rollback_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_rollback_rate5m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_total_rate15m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_total_rate1m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_total_rate5m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xact_total_sigma15m	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:ins:xlock_count	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:query:call_rate1m	Unknown	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:query:rt_1m	Unknown	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg:table:scan_rate1m	Unknown	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg_activity_count	gauge	`datname`, `state`, `job`, `ins`, `ip`, `instance`, `cls`	Count of connection among (datname,state)
pg_activity_max_conn_duration	gauge	`datname`, `state`, `job`, `ins`, `ip`, `instance`, `cls`	Max backend session duration since state change among (datname, state)
pg_activity_max_duration	gauge	`datname`, `state`, `job`, `ins`, `ip`, `instance`, `cls`	Max duration since last state change among (datname, state)
pg_activity_max_tx_duration	gauge	`datname`, `state`, `job`, `ins`, `ip`, `instance`, `cls`	Max transaction duration since state change among (datname, state)
pg_archiver_failed_count	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of failed attempts for archiving WAL files
pg_archiver_finish_count	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of WAL files that have been successfully archived
pg_archiver_last_failed_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Time of the last failed archival operation
pg_archiver_last_finish_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Time of the last successful archive operation
pg_archiver_reset_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Time at which archive statistics were last reset
pg_backend_count	gauge	`type`, `job`, `ins`, `ip`, `instance`, `cls`	Database backend process count by backend_type
pg_bgwriter_buffers_alloc	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of buffers allocated
pg_bgwriter_buffers_backend	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of buffers written directly by a backend
pg_bgwriter_buffers_backend_fsync	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of times a backend had to execute its own fsync call
pg_bgwriter_buffers_checkpoint	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of buffers written during checkpoints
pg_bgwriter_buffers_clean	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of buffers written by the background writer
pg_bgwriter_checkpoint_sync_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total amount of time that has been spent in the portion of checkpoint processing where files are synchronized to disk, in seconds
pg_bgwriter_checkpoint_write_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total amount of time that has been spent in the portion of checkpoint processing where files are written to disk, in seconds
pg_bgwriter_checkpoints_req	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of requested checkpoints that have been performed
pg_bgwriter_checkpoints_timed	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of scheduled checkpoints that have been performed
pg_bgwriter_maxwritten_clean	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of times the background writer stopped a cleaning scan because it had written too many buffers
pg_bgwriter_reset_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Time at which bgwriter statistics were last reset
pg_boot_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`	unix timestamp when postmaster boot
pg_checkpoint_checkpoint_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint location
pg_checkpoint_elapse	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Seconds elapsed since latest checkpoint in seconds
pg_checkpoint_full_page_writes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s full_page_writes enabled
pg_checkpoint_newest_commit_ts_xid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s newestCommitTsXid
pg_checkpoint_next_multi_offset	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s NextMultiOffset
pg_checkpoint_next_multixact_id	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s NextMultiXactId
pg_checkpoint_next_oid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s NextOID
pg_checkpoint_next_xid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s NextXID xid
pg_checkpoint_next_xid_epoch	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s NextXID epoch
pg_checkpoint_oldest_active_xid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s oldestActiveXID
pg_checkpoint_oldest_commit_ts_xid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s oldestCommitTsXid
pg_checkpoint_oldest_multi_dbid	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s oldestMulti’s DB OID
pg_checkpoint_oldest_multi_xid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s oldestMultiXid
pg_checkpoint_oldest_xid	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s oldestXID
pg_checkpoint_oldest_xid_dbid	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s oldestXID’s DB OID
pg_checkpoint_prev_tli	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s PrevTimeLineID
pg_checkpoint_redo_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s REDO location
pg_checkpoint_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Time of latest checkpoint
pg_checkpoint_tli	counter	`job`, `ins`, `ip`, `instance`, `cls`	Latest checkpoint’s TimeLineID
pg_conf_reload_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds since last configuration reload
pg_db_active_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent executing SQL statements in this database, in seconds
pg_db_age	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Age of database calculated from datfrozenxid
pg_db_allow_conn	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	If false(0) then no one can connect to this database.
pg_db_blk_read_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent reading data file blocks by backends in this database, in seconds
pg_db_blk_write_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent writing data file blocks by backends in this database, in seconds
pg_db_blks_access	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times disk blocks that accessed read+hit
pg_db_blks_hit	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times disk blocks were found already in the buffer cache
pg_db_blks_read	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of disk blocks read in this database
pg_db_cks_fail_time	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time at which the last data page checksum failure was detected in this database
pg_db_cks_fails	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of data page checksum failures detected in this database, -1 for not enabled
pg_db_confl_confl_bufferpin	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of queries in this database that have been canceled due to pinned buffers
pg_db_confl_confl_deadlock	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of queries in this database that have been canceled due to deadlocks
pg_db_confl_confl_lock	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of queries in this database that have been canceled due to lock timeouts
pg_db_confl_confl_snapshot	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of queries in this database that have been canceled due to old snapshots
pg_db_confl_confl_tablespace	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of queries in this database that have been canceled due to dropped tablespaces
pg_db_conflicts	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of queries canceled due to conflicts with recovery in this database
pg_db_conn_limit	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Sets maximum number of concurrent connections that can be made to this database. -1 means no limit.
pg_db_datid	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	OID of the database
pg_db_deadlocks	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of deadlocks detected in this database
pg_db_frozen_xid	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	All transaction IDs before this one have been frozened
pg_db_is_template	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	If true(1), then this database can be cloned by any user with CREATEDB privileges
pg_db_ixact_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent idling while in a transaction in this database, in seconds
pg_db_numbackends	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of backends currently connected to this database
pg_db_reset_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time at which database statistics were last reset
pg_db_session_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent by database sessions in this database, in seconds
pg_db_sessions	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of sessions established to this database
pg_db_sessions_abandoned	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of database sessions to this database that were terminated because connection to the client was lost
pg_db_sessions_fatal	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of database sessions to this database that were terminated by fatal errors
pg_db_sessions_killed	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of database sessions to this database that were terminated by operator intervention
pg_db_temp_bytes	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total amount of data written to temporary files by queries in this database.
pg_db_temp_files	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of temporary files created by queries in this database
pg_db_tup_deleted	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows deleted by queries in this database
pg_db_tup_fetched	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows fetched by queries in this database
pg_db_tup_inserted	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows inserted by queries in this database
pg_db_tup_modified	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows modified by queries in this database
pg_db_tup_returned	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows returned by queries in this database
pg_db_tup_updated	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows updated by queries in this database
pg_db_xact_commit	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of transactions in this database that have been committed
pg_db_xact_rollback	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of transactions in this database that have been rolled back
pg_db_xact_total	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of transactions in this database
pg_downstream_count	gauge	`state`, `job`, `ins`, `ip`, `instance`, `cls`	Count of corresponding state
pg_exporter_agent_up	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pg_exporter_last_scrape_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds exporter spending on scrapping
pg_exporter_query_cache_ttl	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	times to live of query cache
pg_exporter_query_scrape_duration	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	seconds query spending on scrapping
pg_exporter_query_scrape_error_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	times the query failed
pg_exporter_query_scrape_hit_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	numbers been scrapped from this query
pg_exporter_query_scrape_metric_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	numbers of metrics been scrapped from this query
pg_exporter_query_scrape_total_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	times exporter server was scraped for metrics
pg_exporter_scrape_duration	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds exporter spending on scrapping
pg_exporter_scrape_error_count	counter	`job`, `ins`, `ip`, `instance`, `cls`	times exporter was scraped for metrics and failed
pg_exporter_scrape_total_count	counter	`job`, `ins`, `ip`, `instance`, `cls`	times exporter was scraped for metrics
pg_exporter_server_scrape_duration	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	seconds exporter server spending on scrapping
pg_exporter_server_scrape_error_count	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	N/A
pg_exporter_server_scrape_total_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	times exporter server was scraped for metrics
pg_exporter_server_scrape_total_seconds	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	seconds exporter server spending on scrapping
pg_exporter_up	gauge	`job`, `ins`, `ip`, `instance`, `cls`	always be 1 if your could retrieve metrics
pg_exporter_uptime	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds since exporter primary server inited
pg_flush_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	primary only, location of current wal syncing
pg_func_calls	counter	`datname`, `funcname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times this function has been called
pg_func_self_time	counter	`datname`, `funcname`, `job`, `ins`, `ip`, `instance`, `cls`	Total time spent in this function itself, not including other functions called by it, in ms
pg_func_total_time	counter	`datname`, `funcname`, `job`, `ins`, `ip`, `instance`, `cls`	Total time spent in this function and all other functions called by it, in ms
pg_in_recovery	gauge	`job`, `ins`, `ip`, `instance`, `cls`	server is in recovery mode? 1 for yes 0 for no
pg_index_idx_blks_hit	counter	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Number of buffer hits in this index
pg_index_idx_blks_read	counter	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Number of disk blocks read from this index
pg_index_idx_scan	counter	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Number of index scans initiated on this index
pg_index_idx_tup_fetch	counter	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Number of live table rows fetched by simple index scans using this index
pg_index_idx_tup_read	counter	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Number of index entries returned by scans on this index
pg_index_relpages	gauge	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Size of the on-disk representation of this index in pages
pg_index_reltuples	gauge	`datname`, `relname`, `job`, `ins`, `relid`, `ip`, `instance`, `cls`, `idxname`	Estimate relation tuples
pg_insert_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	primary only, location of current wal inserting
pg_io_evictions	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Number of times a block has been written out from a shared or local buffer
pg_io_extend_time	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Time spent in extend operations in seconds
pg_io_extends	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Number of relation extend operations, each of the size specified in op_bytes.
pg_io_fsync_time	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Time spent in fsync operations in seconds
pg_io_fsyncs	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Number of fsync calls. These are only tracked in context normal
pg_io_hits	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	The number of times a desired block was found in a shared buffer.
pg_io_op_bytes	gauge	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	The number of bytes per unit of I/O read, written, or extended. 8192 by default
pg_io_read_time	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Time spent in read operations in seconds
pg_io_reads	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Number of read operations, each of the size specified in op_bytes.
pg_io_reset_time	gauge	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Timestamp at which these statistics were last reset
pg_io_reuses	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	The number of times an existing buffer in reused
pg_io_write_time	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Time spent in write operations in seconds
pg_io_writeback_time	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Time spent in writeback operations in seconds
pg_io_writebacks	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Number of units of size op_bytes which the process requested the kernel write out to permanent storage.
pg_io_writes	counter	`type`, `job`, `ins`, `object`, `ip`, `context`, `instance`, `cls`	Number of write operations, each of the size specified in op_bytes.
pg_is_in_recovery	gauge	`job`, `ins`, `ip`, `instance`, `cls`	1 if in recovery mode
pg_is_wal_replay_paused	gauge	`job`, `ins`, `ip`, `instance`, `cls`	1 if wal play paused
pg_lag	gauge	`job`, `ins`, `ip`, `instance`, `cls`	replica only, replication lag in seconds
pg_last_replay_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`	time when last transaction been replayed
pg_lock_count	gauge	`datname`, `job`, `ins`, `ip`, `mode`, `instance`, `cls`	Number of locks of corresponding mode and database
pg_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	log sequence number, current write location
pg_meta_info	gauge	`cls`, `extensions`, `version`, `job`, `ins`, `primary_conninfo`, `conf_path`, `hba_path`, `ip`, `cluster_id`, `instance`, `listen_port`, `wal_level`, `ver_num`, `cluster_name`, `data_dir`	constant 1
pg_query_calls	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times the statement was executed
pg_query_exec_time	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total time spent executing the statement, in seconds
pg_query_io_time	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total time the statement spent reading and writing blocks, in seconds
pg_query_rows	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of rows retrieved or affected by the statement
pg_query_sblk_dirtied	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of shared blocks dirtied by the statement
pg_query_sblk_hit	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of shared block cache hits by the statement
pg_query_sblk_read	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of shared blocks read by the statement
pg_query_sblk_written	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of shared blocks written by the statement
pg_query_wal_bytes	counter	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	Total amount of WAL bytes generated by the statement
pg_receive_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	replica only, location of wal synced to disk
pg_recovery_backup_end_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	Backup end location
pg_recovery_backup_start_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	Backup start location
pg_recovery_min_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	Minimum recovery ending location
pg_recovery_min_timeline	counter	`job`, `ins`, `ip`, `instance`, `cls`	Min recovery ending loc’s timeline
pg_recovery_prefetch_block_distance	gauge	`job`, `ins`, `ip`, `instance`, `cls`	How many blocks ahead the prefetcher is looking
pg_recovery_prefetch_hit	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks not prefetched because they were already in the buffer pool
pg_recovery_prefetch_io_depth	gauge	`job`, `ins`, `ip`, `instance`, `cls`	How many prefetches have been initiated but are not yet known to have completed
pg_recovery_prefetch_prefetch	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks prefetched because they were not in the buffer pool
pg_recovery_prefetch_reset_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Time at which these recovery prefetch statistics were last reset
pg_recovery_prefetch_skip_fpw	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks not prefetched because a full page image was included in the WAL
pg_recovery_prefetch_skip_init	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks not prefetched because they would be zero-initialized
pg_recovery_prefetch_skip_new	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks not prefetched because they didn’t exist yet
pg_recovery_prefetch_skip_rep	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks not prefetched because they were already recently prefetched
pg_recovery_prefetch_wal_distance	gauge	`job`, `ins`, `ip`, `instance`, `cls`	How many bytes ahead the prefetcher is looking
pg_recovery_require_record	gauge	`job`, `ins`, `ip`, `instance`, `cls`	End-of-backup record required
pg_recv_flush_lsn	counter	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Last write-ahead log location already received and flushed to disk
pg_recv_flush_tli	counter	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Timeline number of last write-ahead log location received and flushed to disk
pg_recv_init_lsn	counter	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	First write-ahead log location used when WAL receiver is started
pg_recv_init_tli	counter	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	First timeline number used when WAL receiver is started
pg_recv_msg_recv_time	gauge	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Receipt time of last message received from origin WAL sender
pg_recv_msg_send_time	gauge	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Send time of last message received from origin WAL sender
pg_recv_pid	gauge	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Process ID of the WAL receiver process
pg_recv_reported_lsn	counter	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Last write-ahead log location reported to origin WAL sender
pg_recv_reported_time	gauge	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Time of last write-ahead log location reported to origin WAL sender
pg_recv_time	gauge	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Time of current snapshot
pg_recv_write_lsn	counter	`state`, `slot_name`, `job`, `ins`, `ip`, `instance`, `cls`, `sender_host`, `sender_port`	Last write-ahead log location already received and written to disk, but not flushed.
pg_relkind_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`, `relkind`	Number of relations of corresponding relkind
pg_repl_backend_xmin	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	This standby’s xmin horizon reported by hot_standby_feedback.
pg_repl_client_port	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	TCP port number that the client is using for communication with this WAL sender, or -1 if a Unix socket is used
pg_repl_flush_diff	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last log position flushed to disk by this standby server diff with current lsn
pg_repl_flush_lag	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Time elapsed between flushing recent WAL locally and receiving notification that this standby server has written and flushed it
pg_repl_flush_lsn	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last write-ahead log location flushed to disk by this standby server
pg_repl_launch_time	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Time when this process was started, i.e., when the client connected to this WAL sender
pg_repl_lsn	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Current log position on this server
pg_repl_replay_diff	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last log position replayed into the database on this standby server diff with current lsn
pg_repl_replay_lag	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Time elapsed between flushing recent WAL locally and receiving notification that this standby server has written, flushed and applied it
pg_repl_replay_lsn	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last write-ahead log location replayed into the database on this standby server
pg_repl_reply_time	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Send time of last reply message received from standby server
pg_repl_sent_diff	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last log position sent to this standby server diff with current lsn
pg_repl_sent_lsn	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last write-ahead log location sent on this connection
pg_repl_state	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Current WAL sender encoded state 0-4 for streaming startup catchup backup stopping
pg_repl_sync_priority	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Priority of this standby server for being chosen as the synchronous standby
pg_repl_sync_state	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Encoded synchronous state of this standby server, 0-3 for async potential sync quorum
pg_repl_time	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Current timestamp in unix epoch
pg_repl_write_diff	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last log position written to disk by this standby server diff with current lsn
pg_repl_write_lag	gauge	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Time elapsed between flushing recent WAL locally and receiving notification that this standby server has written it
pg_repl_write_lsn	counter	`pid`, `usename`, `address`, `job`, `ins`, `appname`, `ip`, `instance`, `cls`	Last write-ahead log location written to disk by this standby server
pg_replay_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	replica only, location of wal applied
pg_seq_blks_hit	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`, `seqname`	Number of buffer hits in this sequence
pg_seq_blks_read	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`, `seqname`	Number of disk blocks read from this sequence
pg_seq_last_value	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`, `seqname`	The last sequence value written to disk
pg_setting_block_size	gauge	`job`, `ins`, `ip`, `instance`, `cls`	pg page block size, 8192 by default
pg_setting_data_checksums	gauge	`job`, `ins`, `ip`, `instance`, `cls`	whether data checksum is enabled, 1 enabled 0 disabled
pg_setting_max_connections	gauge	`job`, `ins`, `ip`, `instance`, `cls`	number of concurrent connections to the database server
pg_setting_max_locks_per_transaction	gauge	`job`, `ins`, `ip`, `instance`, `cls`	no more than this many distinct objects can be locked at any one time
pg_setting_max_prepared_transactions	gauge	`job`, `ins`, `ip`, `instance`, `cls`	maximum number of transactions that can be in the prepared state simultaneously
pg_setting_max_replication_slots	gauge	`job`, `ins`, `ip`, `instance`, `cls`	maximum number of replication slots
pg_setting_max_wal_senders	gauge	`job`, `ins`, `ip`, `instance`, `cls`	maximum number of concurrent connections from standby servers
pg_setting_max_worker_processes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	maximum number of background processes that the system can support
pg_setting_wal_log_hints	gauge	`job`, `ins`, `ip`, `instance`, `cls`	whether wal_log_hints is enabled, 1 enabled 0 disabled
pg_size_bytes	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	File size in bytes
pg_slot_active	gauge	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	True(1) if this slot is currently actively being used
pg_slot_catalog_xmin	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	The oldest transaction affecting the system catalogs that this slot needs the database to retain.
pg_slot_confirm_lsn	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	The address (LSN) up to which the logical slot’s consumer has confirmed receiving data.
pg_slot_reset_time	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	When statistics were last reset
pg_slot_restart_lsn	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	The address (LSN) of oldest WAL which still might be required by the consumer of this slot
pg_slot_retained_bytes	gauge	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Size of bytes that retained for this slot
pg_slot_safe_wal_size	gauge	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	bytes that can be written to WAL which will not make slot into lost
pg_slot_spill_bytes	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Bytes that spilled to disk due to logical decode mem exceeding
pg_slot_spill_count	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Xacts that spilled to disk due to logical decode mem exceeding (a xact can be spilled multiple times)
pg_slot_spill_txns	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Xacts that spilled to disk due to logical decode mem exceeding (subtrans included)
pg_slot_stream_bytes	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Bytes that streamed to decoding output plugin after mem exceed
pg_slot_stream_count	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Xacts that streamed to decoding output plugin after mem exceed (a xact can be streamed multiple times)
pg_slot_stream_txns	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Xacts that streamed to decoding output plugin after mem exceed
pg_slot_temporary	gauge	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	True(1) if this is a temporary replication slot.
pg_slot_total_bytes	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Number of decoded bytes sent to the decoding output plugin for this slot
pg_slot_total_txns	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	Number of decoded xacts sent to the decoding output plugin for this slot
pg_slot_wal_status	gauge	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	WAL reserve status 0-3 means reserved,extended,unreserved,lost, -1 means other
pg_slot_xmin	counter	`slot_name`, `job`, `ins`, `ip`, `instance`, `cls`	The oldest transaction that this slot needs the database to retain.
pg_slru_blks_exists	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks checked for existence for this SLRU
pg_slru_blks_hit	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of times disk blocks were found already in the SLRU, so that a read was not necessary
pg_slru_blks_read	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of disk blocks read for this SLRU
pg_slru_blks_written	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of disk blocks written for this SLRU
pg_slru_blks_zeroed	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of blocks zeroed during initializations
pg_slru_flushes	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of flushes of dirty data for this SLRU
pg_slru_reset_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Time at which these statistics were last reset
pg_slru_truncates	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of truncates for this SLRU
pg_ssl_disabled	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of client connection that does not use ssl
pg_ssl_enabled	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of client connection that use ssl
pg_sync_standby_enabled	gauge	`job`, `ins`, `ip`, `names`, `instance`, `cls`	Synchronous commit enabled, 1 if enabled, 0 if disabled
pg_table_age	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Age of this table in vacuum cycles
pg_table_analyze_count	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times this table has been manually analyzed
pg_table_autoanalyze_count	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times this table has been analyzed by the autovacuum daemon
pg_table_autovacuum_count	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times this table has been vacuumed by the autovacuum daemon
pg_table_frozenxid	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	All txid before this have been frozen on this table
pg_table_heap_blks_hit	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of buffer hits in this table
pg_table_heap_blks_read	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of disk blocks read from this table
pg_table_idx_blks_hit	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of buffer hits in all indexes on this table
pg_table_idx_blks_read	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of disk blocks read from all indexes on this table
pg_table_idx_scan	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of index scans initiated on this table
pg_table_idx_tup_fetch	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of live rows fetched by index scans
pg_table_kind	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Relation kind r/table/114
pg_table_n_dead_tup	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Estimated number of dead rows
pg_table_n_ins_since_vacuum	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Estimated number of rows inserted since this table was last vacuumed
pg_table_n_live_tup	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Estimated number of live rows
pg_table_n_mod_since_analyze	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Estimated number of rows modified since this table was last analyzed
pg_table_n_tup_del	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows deleted
pg_table_n_tup_hot_upd	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows HOT updated (i.e with no separate index update required)
pg_table_n_tup_ins	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows inserted
pg_table_n_tup_mod	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows modified (insert + update + delete)
pg_table_n_tup_newpage_upd	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows updated where the successor version goes onto a new heap page
pg_table_n_tup_upd	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of rows updated (includes HOT updated rows)
pg_table_ncols	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of columns in the table
pg_table_pages	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Size of the on-disk representation of this table in pages
pg_table_relid	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Relation oid of this table
pg_table_seq_scan	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of sequential scans initiated on this table
pg_table_seq_tup_read	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of live rows fetched by sequential scans
pg_table_size_bytes	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Total bytes of this table (including toast, index, toast index)
pg_table_size_indexsize	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Bytes of all related indexes of this table
pg_table_size_relsize	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Bytes of this table itself (main, vm, fsm)
pg_table_size_toastsize	gauge	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Bytes of toast tables of this table
pg_table_tbl_scan	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of scans initiated on this table
pg_table_tup_read	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of live rows fetched by scans
pg_table_tuples	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	All txid before this have been frozen on this table
pg_table_vacuum_count	counter	`datname`, `relname`, `job`, `ins`, `ip`, `instance`, `cls`	Number of times this table has been manually vacuumed (not counting VACUUM FULL)
pg_timestamp	gauge	`job`, `ins`, `ip`, `instance`, `cls`	database current timestamp
pg_up	gauge	`job`, `ins`, `ip`, `instance`, `cls`	last scrape was able to connect to the server: 1 for yes, 0 for no
pg_uptime	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds since postmaster start
pg_version	gauge	`job`, `ins`, `ip`, `instance`, `cls`	server version number
pg_wait_count	gauge	`datname`, `job`, `ins`, `event`, `ip`, `instance`, `cls`	Count of WaitEvent on target database
pg_wal_buffers_full	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of times WAL data was written to disk because WAL buffers became full
pg_wal_bytes	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total amount of WAL generated in bytes
pg_wal_fpi	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total number of WAL full page images generated
pg_wal_records	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total number of WAL records generated
pg_wal_reset_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	When statistics were last reset
pg_wal_sync	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of times WAL files were synced to disk via issue_xlog_fsync request
pg_wal_sync_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total amount of time spent syncing WAL files to disk via issue_xlog_fsync request, in seconds
pg_wal_write	counter	`job`, `ins`, `ip`, `instance`, `cls`	Number of times WAL buffers were written out to disk via XLogWrite request.
pg_wal_write_time	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total amount of time spent writing WAL buffers to disk via XLogWrite request in seconds
pg_write_lsn	counter	`job`, `ins`, `ip`, `instance`, `cls`	primary only, location of current wal writing
pg_xact_xmax	counter	`job`, `ins`, `ip`, `instance`, `cls`	First as-yet-unassigned txid. txid >= this are invisible.
pg_xact_xmin	counter	`job`, `ins`, `ip`, `instance`, `cls`	Earliest txid that is still active
pg_xact_xnum	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Current active transaction count
pgbouncer:cls:load1	Unknown	`job`, `cls`	N/A
pgbouncer:cls:load15	Unknown	`job`, `cls`	N/A
pgbouncer:cls:load5	Unknown	`job`, `cls`	N/A
pgbouncer:db:conn_usage	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:conn_usage_reserve	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:pool_current_conn	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:pool_disabled	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:pool_max_conn	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:pool_paused	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:pool_reserve_size	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:db:pool_size	Unknown	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	N/A
pgbouncer:ins:free_clients	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:free_servers	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:load1	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:load15	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:load5	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:login_clients	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:pool_databases	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:pool_users	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:pools	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer:ins:used_clients	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer_database_current_connections	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	Current number of connections for this database
pgbouncer_database_disabled	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	True(1) if this database is currently disabled, else 0
pgbouncer_database_max_connections	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	Maximum number of allowed connections for this database
pgbouncer_database_min_pool_size	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	Minimum number of server connections
pgbouncer_database_paused	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	True(1) if this database is currently paused, else 0
pgbouncer_database_pool_size	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	Maximum number of server connections
pgbouncer_database_reserve_pool	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `host`, `cls`, `real_datname`, `port`	Maximum number of additional connections for this database
pgbouncer_exporter_agent_up	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
pgbouncer_exporter_last_scrape_time	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds exporter spending on scrapping
pgbouncer_exporter_query_cache_ttl	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	times to live of query cache
pgbouncer_exporter_query_scrape_duration	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	seconds query spending on scrapping
pgbouncer_exporter_query_scrape_error_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	times the query failed
pgbouncer_exporter_query_scrape_hit_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	numbers been scrapped from this query
pgbouncer_exporter_query_scrape_metric_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	numbers of metrics been scrapped from this query
pgbouncer_exporter_query_scrape_total_count	gauge	`datname`, `query`, `job`, `ins`, `ip`, `instance`, `cls`	times exporter server was scraped for metrics
pgbouncer_exporter_scrape_duration	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds exporter spending on scrapping
pgbouncer_exporter_scrape_error_count	counter	`job`, `ins`, `ip`, `instance`, `cls`	times exporter was scraped for metrics and failed
pgbouncer_exporter_scrape_total_count	counter	`job`, `ins`, `ip`, `instance`, `cls`	times exporter was scraped for metrics
pgbouncer_exporter_server_scrape_duration	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	seconds exporter server spending on scrapping
pgbouncer_exporter_server_scrape_total_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	times exporter server was scraped for metrics
pgbouncer_exporter_server_scrape_total_seconds	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	seconds exporter server spending on scrapping
pgbouncer_exporter_up	gauge	`job`, `ins`, `ip`, `instance`, `cls`	always be 1 if your could retrieve metrics
pgbouncer_exporter_uptime	gauge	`job`, `ins`, `ip`, `instance`, `cls`	seconds since exporter primary server inited
pgbouncer_in_recovery	gauge	`job`, `ins`, `ip`, `instance`, `cls`	server is in recovery mode? 1 for yes 0 for no
pgbouncer_list_items	gauge	`job`, `ins`, `ip`, `instance`, `list`, `cls`	Number of corresponding pgbouncer object
pgbouncer_pool_active_cancel_clients	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Client connections that have forwarded query cancellations to the server and are waiting for the server response.
pgbouncer_pool_active_cancel_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Server connections that are currently forwarding a cancel request
pgbouncer_pool_active_clients	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Client connections that are linked to server connection and can process queries
pgbouncer_pool_active_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Server connections that are linked to a client
pgbouncer_pool_cancel_clients	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Client connections that have not forwarded query cancellations to the server yet.
pgbouncer_pool_cancel_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	cancel requests have completed that were sent to cancel a query on this server
pgbouncer_pool_idle_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Server connections that are unused and immediately usable for client queries
pgbouncer_pool_login_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Server connections currently in the process of logging in
pgbouncer_pool_maxwait	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	How long the first(oldest) client in the queue has waited, in seconds, key metric
pgbouncer_pool_maxwait_us	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Microsecond part of the maximum waiting time.
pgbouncer_pool_tested_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Server connections that are currently running reset or check query
pgbouncer_pool_used_servers	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Server connections that have been idle for more than server_check_delay (means have to run check query)
pgbouncer_pool_waiting_clients	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `user`, `cls`, `pool_mode`	Client connections that have sent queries but have not yet got a server connection
pgbouncer_stat_avg_query_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Average queries per second in last stat period
pgbouncer_stat_avg_query_time	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Average query duration, in seconds
pgbouncer_stat_avg_recv	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Average received (from clients) bytes per second
pgbouncer_stat_avg_sent	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Average sent (to clients) bytes per second
pgbouncer_stat_avg_wait_time	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent by clients waiting for a server, in seconds (average per second).
pgbouncer_stat_avg_xact_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Average transactions per second in last stat period
pgbouncer_stat_avg_xact_time	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Average transaction duration, in seconds
pgbouncer_stat_total_query_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of SQL queries pooled by pgbouncer
pgbouncer_stat_total_query_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of seconds spent when executing queries
pgbouncer_stat_total_received	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total volume in bytes of network traffic received by pgbouncer
pgbouncer_stat_total_sent	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total volume in bytes of network traffic sent by pgbouncer
pgbouncer_stat_total_wait_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Time spent by clients waiting for a server, in seconds
pgbouncer_stat_total_xact_count	gauge	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of SQL transactions pooled by pgbouncer
pgbouncer_stat_total_xact_time	counter	`datname`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of seconds spent when in a transaction
pgbouncer_up	gauge	`job`, `ins`, `ip`, `instance`, `cls`	last scrape was able to connect to the server: 1 for yes, 0 for no
pgbouncer_version	gauge	`job`, `ins`, `ip`, `instance`, `cls`	server version number
process_cpu_seconds_total	counter	`job`, `ins`, `ip`, `instance`, `cls`	Total user and system CPU time spent in seconds.
process_max_fds	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Maximum number of open file descriptors.
process_open_fds	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Number of open file descriptors.
process_resident_memory_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Resident memory size in bytes.
process_start_time_seconds	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Start time of the process since unix epoch in seconds.
process_virtual_memory_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Virtual memory size in bytes.
process_virtual_memory_max_bytes	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Maximum amount of virtual memory available in bytes.
promhttp_metric_handler_requests_in_flight	gauge	`job`, `ins`, `ip`, `instance`, `cls`	Current number of scrapes being served.
promhttp_metric_handler_requests_total	counter	`code`, `job`, `ins`, `ip`, `instance`, `cls`	Total number of scrapes by HTTP status code.
scrape_duration_seconds	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
scrape_samples_post_metric_relabeling	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
scrape_samples_scraped	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
scrape_series_added	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A
up	Unknown	`job`, `ins`, `ip`, `instance`, `cls`	N/A

Accidental Deletion

Mon, 01 Jan 0001 00:00:00 +0000

Accidental Data Deletion

If it’s a small-scale DELETE misoperation, you can consider using the pg_surgery or pg_dirtyread extension for in-place surgical recovery.

-- Immediately disable Auto Vacuum on this table and abort Auto Vacuum worker processes for this table
ALTER TABLE public.some_table SET (autovacuum_enabled = off, toast.autovacuum_enabled = off);

CREATE EXTENSION pg_dirtyread;
SELECT * FROM pg_dirtyread('tablename') AS t(col1 type1, col2 type2, ...);

If the deleted data has already been reclaimed by VACUUM, then use the general accidental deletion recovery process.

Playbook

Mon, 01 Jan 0001 00:00:00 +0000

Pigsty provides a series of playbooks for cluster provisioning, scaling, user/database management, monitoring, backup & recovery, and migration.

Playbook	Function
`pgsql.yml`	Initialize PostgreSQL cluster or add new replicas
`pgsql-rm.yml`	Remove PostgreSQL cluster or specific instances
`pgsql-user.yml`	Add new business user to existing PostgreSQL cluster
`pgsql-db.yml`	Add new business database to existing PostgreSQL cluster
`pgsql-monitor.yml`	Monitor remote PostgreSQL instances
`pgsql-migration.yml`	Generate migration manual and scripts for existing PostgreSQL
`pgsql-pitr.yml`	Perform Point-In-Time Recovery (PITR)

Safeguard

Be extra cautious when using PGSQL playbooks. Misuse of pgsql.yml and pgsql-rm.yml can lead to accidental database deletion!

Extensions

Mon, 01 Jan 0001 00:00:00 +0000

Pigsty provides 510 extensions, covering 16 major categories including time-series, geospatial, vector, full-text search, analytics, and feature enhancements, ready to use out-of-the-box.

Using extensions in Pigsty involves four core steps: Download, Install, Config/Load, and Create.

pg-meta:
 hosts: { 10.10.10.10: { pg_seq: 1, pg_role: primary } }
 vars:
 pg_cluster: pg-meta
 pg_databases:
 - name: meta
 extensions: [ postgis, timescaledb, vector ] # Create: Create extensions in database
 pg_libs: 'timescaledb, pg_stat_statements, auto_explain' # Config: Preload extension libraries
 pg_extensions: [ postgis, timescaledb, pgvector ] # Install: Install extension packages

HA Drill: Handling 2-of-3 Node Failure

Sat, 11 Jan 2025 00:00:00 +0000

If a classic 3-node HA deployment experiences simultaneous failure of two nodes (majority), the system typically cannot complete automatic failover and requires manual intervention.

First, assess the status of the other two servers. If they can be brought up quickly, prioritize recovering those two servers. Otherwise, enter the Emergency Recovery Procedure.

The Emergency Recovery Procedure assumes your admin node has failed and only a single regular database node survives. In this case, the fastest recovery process is:

PostgreSQL

Mon, 01 Jan 0001 00:00:00 +0000

PostgreSQL is the world’s most advanced and popular open-source database.

Pigsty supports PostgreSQL 14 ~ 18 and provides 510 PG extensions.

Quick Start

Install Pigsty using the pgsql configuration template.

./configure -c pgsql # Use postgres kernel
./deploy.yml # Set up everything with pigsty

Most configuration templates use PostgreSQL kernel by default, for example:

meta : Default, postgres with core extensions (vector, postgis, timescale)
rich : postgres with all extensions installed
slim : postgres only, no monitoring infrastructure
full : 4-node sandbox for HA demonstration
pgsql : minimal postgres kernel configuration example

Configuration

Vanilla PostgreSQL kernel requires no special adjustments:

Bind a L2 VIP to PostgreSQL Primary with VIP-Manager

Mon, 01 Jan 0001 00:00:00 +0000

You can define an OPTIONAL L2 VIP on a PostgreSQL cluster, provided that all nodes in the cluster are in the same L2 network.

This VIP works on Master-Backup mode and always points to the node where the primary instance of the database cluster is located.

This VIP is managed by the VIP-Manager, which reads the Leader Key written by Patroni from DCS (etcd) to determine whether it is the master.

Deploy HA Citus Cluster

Sat, 11 Jan 2025 00:00:00 +0000

Citus is a PostgreSQL extension that transforms PostgreSQL into a distributed database, enabling horizontal scaling across multiple nodes to handle large amounts of data and queries.

Patroni v3.0+ provides native high-availability support for Citus, simplifying the setup of Citus clusters. Pigsty also provides native support for this.

Note: Citus 13.x supports PostgreSQL 18, 17, 16, 15, and 14. Pigsty extension repo provides Citus ARM64 packages.

Babelfish

Mon, 01 Jan 0001 00:00:00 +0000

Babelfish is a PostgreSQL-based SQL Server compatibility layer, open-sourced by AWS.

Overview

Pigsty lets you deploy Babelfish in mssql mode and provide, on top of PostgreSQL:

SQL Server wire protocol compatibility (TDS, 1433)
T-SQL compatibility
Unified integration with Pigsty capabilities (HA, backup, monitoring, IaC)

In v4.2.0, Babelfish defaults to PostgreSQL 17 and is part of Pigsty’s standard delivery path.

What Changed in v4.2.0

Compared with older Babelfish/PG15 docs, current behavior is:

Percona

Mon, 01 Jan 0001 00:00:00 +0000

Percona Postgres is a patched Postgres kernel with pg_tde (Transparent Data Encryption) extension.

It’s compatible with PostgreSQL 18.1 and available on all Pigsty-supported platforms.

Performance Test for Percona Transparent Data Encryption (TDE)

Quick Start

Use Pigsty’s standard installation process with the pgtde configuration template.

curl -fsSL https://repo.pigsty.io/get | bash; cd ~/pigsty;
./configure -c pgtde # Use percona postgres kernel
./deploy.yml # Set up everything with pigsty

Configuration

The following parameters need to be adjusted to deploy a Percona cluster:

openHalo

Mon, 01 Jan 0001 00:00:00 +0000

OpenHalo is an open-source PostgreSQL kernel that provides MySQL wire-protocol compatibility.

openHalo is based on PostgreSQL 14.18 and provides wire-level compatibility with MySQL 5.7.32-log / 8.0.

Pigsty supports OpenHalo deployment on all supported Linux platforms.

RPM build spec: github.com/pgsty/rpm/rpmbuild/specs/openhalodb.spec
DEB build spec: github.com/pgsty/deb/debbuild/openhalodb

Quick Start

Use Pigsty’s standard installation flow with the mysql template.

curl -fsSL https://repo.pigsty.io/get | bash; cd ~/pigsty;
./configure -c mysql # Use MySQL (openHalo) template
./deploy.yml # Install (change passwords in pigsty.yml before production use)

Cluster Config

pg-meta:
 hosts:
 10.10.10.10: { pg_seq: 1, pg_role: primary }
 vars:
 pg_cluster: pg-meta
 pg_users:
 - {name: dbuser_meta ,password: DBUser.Meta ,pgbouncer: true ,roles: [dbrole_admin] ,comment: pigsty admin user }
 - {name: dbuser_view ,password: DBUser.Viewer ,pgbouncer: true ,roles: [dbrole_readonly] ,comment: read-only viewer for meta database }
 pg_databases:
 - {name: postgres, extensions: [ aux_mysql ]} # mysql-compatible database
 - {name: meta ,baseline: cmdb.sql ,comment: pigsty meta database ,schemas: [pigsty]}
 pg_hba_rules:
 - {user: dbuser_view , db: all ,addr: infra ,auth: pwd ,title: 'allow grafana dashboard access cmdb from infra nodes'}
 node_crontab: [ '00 01 * * * postgres /pg/bin/pg-backup full' ] # full backup at 1 AM daily

 # OpenHalo specific settings
 pg_mode: mysql
 pg_version: 14
 pg_packages: [ openhalodb, pgsql-common ]

OpenHalo provides a dedicated extension, aux_mysql, which includes functions and types needed for MySQL compatibility. Enable it in the postgres database to get full compatibility behavior.

OrioleDB

Mon, 01 Jan 0001 00:00:00 +0000

OrioleDB is a PostgreSQL storage engine extension that claims to provide 4x OLTP performance, no xid wraparound and table bloat issues, and “cloud-native” (data stored in S3) capabilities.

OrioleDB’s latest version is based on a patched PostgreSQL 17.6 and an additional extension

You can run OrioleDB as an RDS using Pigsty. It’s compatible with PG 17 and available on all supported Linux platforms. The latest version is beta14, based on PG 17_16 patch.

Cloudberry

Mon, 01 Jan 0001 00:00:00 +0000

Cloudberry is an open-source MPP data warehouse kernel derived from the Greenplum ecosystem, suitable for large-scale parallel analytics workloads.

Overview

In Pigsty, Cloudberry uses gpsql mode and shares the same identity model, monitoring logic, and directory conventions as Greenplum / MatrixDB.

Kernel package: cloudberry
Mode identifier: pg_mode: gpsql
Role flag: gp_role: master | segment
Current repo version: Cloudberry 2.0.0
Current version string: PostgreSQL 14.4 (Apache Cloudberry 2.0.0-incubating build 1)
Default binary directory: /usr/local/cloudberry

The important boundary is this: Pigsty currently focuses on package delivery, node management, monitoring onboarding, access control, and configuration orchestration for Cloudberry. For MPP cluster initialization, scale-out, rebalance, and other upstream-specific operational actions, you should still use the official Cloudberry toolchain.

AgensGraph

Mon, 01 Jan 0001 00:00:00 +0000

AgensGraph is a property graph database kernel built on PostgreSQL, supporting openCypher queries and mixed Cypher/SQL workflows.

Overview

Pigsty integrates AgensGraph through pg_mode: agens while preserving most of the standard PostgreSQL operational model.

Kernel package: agensgraph
Mode identifier: pg_mode: agens
Current template version: AgensGraph 2.16
Current version string: PostgreSQL 16.9 (AgensGraph 2.16)
Built-in template: agens
Typical use cases: graph relationship analysis, path queries, knowledge graphs, and risk/association analysis layered onto relational data

From the client side, AgensGraph still speaks the PostgreSQL wire protocol, so normal PostgreSQL clients, drivers, and connection pools can connect directly. The real difference from vanilla PostgreSQL is not how you connect, but that the database now contains graph objects, Cypher syntax, and the agtype data type.

pgEdge

Mon, 01 Jan 0001 00:00:00 +0000

pgEdge is a distributed PostgreSQL distribution for edge scenarios, built on Spock multi-master logical replication.

Overview

Pigsty integrates pgEdge through pg_mode: pgedge and delivers it through the standard PostgreSQL cluster workflow:

pgedge: a PG18-compatible kernel
spock: Active-active multi-master logical replication
snowflake: Distributed unique sequences
lolor: Large object logical replication compatibility layer

In the current Pigsty repository, pgEdge PG18 is shipped as the pgedge-18 18.3 package, together with spock 5.0.6, snowflake 2.4, and lolor 1.2.2. PG17 packages are still kept as a transition option, but the pgedge configuration template now defaults to pg_version: 18. From the client side, pgEdge is still PostgreSQL wire compatible, so psql, JDBC/ODBC, DBeaver, and similar tools work as usual.

Param Templates

Mon, 01 Jan 0001 00:00:00 +0000

Pigsty provides four preset Patroni/PostgreSQL config templates optimized for different workloads:

Template	CPU Cores	Use Case	Characteristics
`/docs/pgsql/template/oltp.yml`	4-128C	OLTP transactions	High concurrency, low latency
`/docs/pgsql/template/olap.yml`	4-128C	OLAP analytics	Large queries, high parallelism
`/docs/pgsql/template/crit.yml`	4-128C	Critical/Finance	Data safety, audit, zero-loss
`/docs/pgsql/template/tiny.yml`	1-3C	Tiny instances	Resource-constrained envs

Use pg_conf to select a template; default is /docs/pgsql/template/oltp.yml.

The database tuning template pg_conf should be paired with the OS tuning template node_tune.

Usage

Set pg_conf in your cluster definition. It’s recommended to set node_tune accordingly for OS-level tuning:

PG Kernels

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In Pigsty, you can replace the native PostgreSQL kernel with different PostgreSQL “flavors” to unlock specialized capabilities.

Pigsty supports multiple PostgreSQL kernels and compatibility branches so you can get compatibility layers, multi-master replication, graph queries, MPP warehousing, transparent encryption, and more inside one operational framework.

One thing to keep in mind is that not every kernel has the same delivery depth in Pigsty: PostgreSQL, Citus, Babelfish, IvorySQL, PolarDB, AgensGraph, and pgEdge already have relatively clear templates and configuration paths; Cloudberry and Greenplum, by contrast, are more often managed through gpsql mode, and their MPP initialization plus scale-out operations are still better handled with upstream tooling.

Quick Start

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Using extensions in Pigsty requires four steps: Download, Install, Config, and Create.

Download: Download extension packages to the local repository (Pigsty has already downloaded mainstream extensions by default)
Install: Install extension packages on cluster nodes
Config: Some extensions need to be preloaded or configured with parameters
Create: Execute CREATE EXTENSION in the database to create the extension

Declarative Configuration

Declare extensions in the Pigsty configuration manifest, and they will be automatically installed and created during cluster initialization:

Introduction

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Extensions are the soul of PostgreSQL. Pigsty includes 510 pre-compiled, out-of-the-box extension plugins, fully unleashing PostgreSQL’s potential.

What are Extensions

PostgreSQL extensions are a modular mechanism that allows enhancing database functionality without modifying the core code. An extension typically consists of three parts:

Control file (.control): Required, contains extension metadata
SQL scripts (.sql): Optional, defines functions, types, operators, and other database objects
Dynamic library (.so): Optional, provides high-performance functionality implemented in C

Extensions can add to PostgreSQL: new data types, index methods, functions and operators, foreign data access, procedural languages, performance monitoring, security auditing, and more.

Packages

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Pigsty uses a package alias mechanism to simplify extension installation and management.

Package Alias Mechanism

Managing extensions involves multiple layers of name mapping:

Layer	Example `pgvector`	Example `postgis`
Extension Name	`vector`	`postgis`, `postgis_topology`, …
Package Alias	`pgvector`	`postgis`
RPM Package Name	`pgvector_18`	`postgis36_18*`
DEB Package Name	`postgresql-18-pgvector`	`postgresql-18-postgis-3*`

Pigsty provides a package alias abstraction layer, so users don’t need to worry about specific RPM/DEB package names:

pg_extensions: [ pgvector, postgis, timescaledb ]  # Use package aliases

Pigsty automatically translates to the correct package names based on the operating system and PostgreSQL version.

Download

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Before installing extensions, ensure that extension packages are downloaded to the local repository or available from upstream.

Default Behavior

Pigsty automatically downloads mainstream extensions available for the default PostgreSQL version to the local software repository during installation.

Benefits of using a local repository:

Accelerated installation, avoiding repeated downloads
Reduced network traffic consumption
Improved delivery reliability
Ensured version consistency

Download New Extensions

To download additional extensions, add them to repo_extra_packages and rebuild the repository:

Install

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Pigsty uses the operating system’s package manager (yum/apt) to install extension packages.

Two parameters are used to specify extensions to install:

Parameter	Purpose	Default Behavior
`pg_packages`	Global common packages	Ensure present (no upgrade)
`pg_extensions`	Cluster-specific extensions	Install latest version

pg_packages is typically used to specify base components needed by all clusters (PostgreSQL kernel, Patroni, pgBouncer, etc.) and essential extensions.

pg_extensions is used to specify extensions needed by specific clusters.

Config

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Some extensions require preloading dynamic libraries or configuring parameters before use. This section describes how to configure extensions.

Preload Extensions

Most extensions can be enabled directly with CREATE EXTENSION after installation, but some extensions using PostgreSQL’s Hook mechanism require preloading.

Preloading is specified via the shared_preload_libraries parameter and requires a database restart to take effect.

Extensions Requiring Preload

Common extensions that require preloading:

Extension	Description
`timescaledb`	Time-series database extension, must be placed first
`citus`	Distributed database extension, must be placed first
`pg_stat_statements`	SQL statement statistics, enabled by default in Pigsty
`auto_explain`	Automatically log slow query execution plans, enabled by default in Pigsty
`pg_cron`	Scheduled task scheduling
`pg_net`	Asynchronous HTTP requests
`pg_tle`	Trusted language extensions
`pgaudit`	Audit logging
`pg_stat_kcache`	Kernel statistics
`pg_squeeze`	Online table space reclamation
`pgml`	PostgresML machine learning

For the complete list, see the Extension Catalog (marked with LOAD).

Create

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After installing extension packages, you need to execute CREATE EXTENSION in the database to use extension features.

View Available Extensions

After installing extension packages, you can view available extensions:

-- View all available extensions
SELECT * FROM pg_available_extensions;

-- View specific extension
SELECT * FROM pg_available_extensions WHERE name = 'vector';

-- View enabled extensions
SELECT * FROM pg_extension;

Create Extensions

Use CREATE EXTENSION to enable extensions in the database:

Update

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Extension updates involve two levels: package updates (operating system level) and extension object updates (database level).

Update Packages

Use package managers to update extension packages:

# EL systems
sudo yum update pgvector_18*

# Debian/Ubuntu systems
sudo apt update && sudo apt upgrade postgresql-18-pgvector

Batch update using Pigsty:

# Update extension packages for specified cluster
./pgsql.yml -l pg-meta -t pg_extension -e '{"pg_extensions":["pgvector"]}'

# Using pig package manager
pig update pgvector

Update Extension Objects

After package updates, extension objects in the database may need to be synchronized.

Remove

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Removing extensions involves two levels: dropping extension objects (database level) and uninstalling packages (operating system level).

Drop Extension Objects

Use DROP EXTENSION to remove extensions from the database:

-- Drop extension
DROP EXTENSION pgvector;

-- If there are dependent objects, cascade delete is required
DROP EXTENSION pgvector CASCADE;

Warning: CASCADE will drop all objects that depend on this extension (tables, functions, views, etc.). Use with caution.

Check Extension Dependencies

It’s recommended to check dependencies before dropping:

Default Extensions

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Pigsty installs and enables some core extensions by default when initializing PostgreSQL clusters.

Default Installed Extensions

Extensions installed by default via pg_packages:

Extension	Description
`pg_repack`	Handle table bloat online, important maintenance tool
`wal2json`	Logical decoding outputs JSON format changes, commonly used in CDC scenarios

Extensions optionally installed via pg_extensions (commented by default):

Extension	Description
`postgis`	Geospatial database extension
`timescaledb`	Time-series database extension
`pgvector`	Vector data type and indexes

Default Enabled Extensions

Extensions enabled by default in all databases via pg_default_extensions:

FAQ

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Why can’t my current user use the `pg` admin alias?

Starting from Pigsty v4.0, permissions to manage global Patroni / PostgreSQL clusters using the pg admin alias have been tightened to the admin group (admin) on admin nodes.

The admin user (dba) created by the node.yml playbook has this permission by default. If your current user wants this permission, you need to explicitly add them to the admin group:

sudo usermod -aG admin <username>

PGSQL Init Fails: Fail to wait for postgres/patroni primary

There are multiple possible causes for this error. You need to check Ansible, Systemd / Patroni / PostgreSQL logs to find the real cause.

Repository

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Pigsty provides supplementary extension repositories, offering additional extension packages on top of the PGDG official repository.

YUM Repository

Applicable to EL 7/8/9/10 and compatible systems (RHEL, Rocky, AlmaLinux, CentOS, etc.).

Add Repository

# Add GPG public key
curl -fsSL https://repo.pigsty.io/key | sudo tee /etc/pki/rpm-gpg/RPM-GPG-KEY-pigsty >/dev/null

# Add repository configuration
curl -fsSL https://repo.pigsty.io/yum/repo | sudo tee /etc/yum.repos.d/pigsty.repo >/dev/null

# Refresh cache
sudo yum makecache

China Mainland Mirror

curl -fsSL https://repo.pigsty.cc/key | sudo tee /etc/pki/rpm-gpg/RPM-GPG-KEY-pigsty >/dev/null
curl -fsSL https://repo.pigsty.cc/yum/repo | sudo tee /etc/yum.repos.d/pigsty.repo >/dev/null

Repository URLs

International: https://repo.pigsty.io/yum/
China: https://repo.pigsty.cc/yum/

APT Repository

Applicable to Debian 11/12/13 and Ubuntu 22.04/24.04/26.04 and compatible systems.

Misc

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Citus

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Pigsty natively supports Citus. This is a distributed horizontal scaling extension based on the native PostgreSQL kernel.

Installation

Citus is a PostgreSQL extension plugin that can be installed and enabled on a native PostgreSQL cluster following the standard plugin installation process.

./pgsql.yml -t pg_extension -e '{"pg_extensions":["citus"]}'

Configuration

To define a citus cluster, you need to specify the following parameters:

pg_mode must be set to citus instead of the default pgsql
You must define the shard name pg_shard and shard number pg_group on each shard cluster
You must define pg_primary_db to specify the database managed by Patroni
If you want to use postgres from pg_dbsu instead of the default pg_admin_username to execute admin commands, then pg_dbsu_password must be set to a non-empty plaintext password

Additionally, you need extra hba rules to allow SSL access from localhost and other data nodes.

IvorySQL

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IvorySQL is an open-source PostgreSQL kernel fork that aims to provide “Oracle compatibility” based on PG.

Overview

The IvorySQL kernel is supported in the Pigsty open-source version. Your server needs internet access to download relevant packages directly from IvorySQL’s official repository.

Please note that adding IvorySQL directly to Pigsty’s default software repository will affect the installation of the native PostgreSQL kernel. Pigsty Professional Edition provides offline installation solutions including the IvorySQL kernel.

PolarDB PG

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Overview

Pigsty allows you to create PostgreSQL clusters with “domestic innovation qualification” credentials using PolarDB!

PolarDB for PostgreSQL now uses PostgreSQL 17 as its base. The polar template, default path, and extension notes in Pigsty have all been updated to PG17. Any client tool compatible with the PostgreSQL wire protocol can access PolarDB clusters.

Pigsty’s PGSQL repository provides PolarDB PG open-source installation packages, but they are not downloaded to the local software repository during Pigsty installation.

PolarDB Oracle

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Pigsty allows you to create PolarDB for Oracle clusters with “domestic innovation qualification” credentials using PolarDB!

According to the Security and Reliability Evaluation Results Announcement (No. 1, 2023), Appendix 3, Centralized Database. PolarDB v2.0 is an autonomous, controllable, secure, and reliable domestic innovation database.

PolarDB for Oracle is an Oracle-compatible version developed based on PolarDB for PostgreSQL. Both share the same kernel, distinguished by the --compatibility-mode parameter.

We collaborate with the Alibaba Cloud kernel team to provide a complete database solution based on PolarDB v2.0 kernel and Pigsty. Please contact sales for inquiries, or purchase on Alibaba Cloud Marketplace.

Greenplum

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Pigsty supports deploying Greenplum clusters and its derivative distribution YMatrixDB, and provides the capability to integrate existing Greenplum deployments into Pigsty monitoring.

Overview

Greenplum / YMatrix cluster deployment capabilities are only available in the professional/enterprise editions and are not currently open source.

Installation

Pigsty provides installation packages for Greenplum 6 (@el7) and Greenplum 7 (@el8). Open source users can install and configure them manually.

# EL 7 Only (Greenplum6)
./node.yml -t node_install -e '{"node_repo_modules":"pgsql","node_packages":["open-source-greenplum-db-6"]}'

# EL 8 Only (Greenplum7)
./node.yml -t node_install -e '{"node_repo_modules":"pgsql","node_packages":["open-source-greenplum-db-7"]}'

Configuration

To define a Greenplum cluster, you need to use pg_mode = gpsql and additional identity parameters pg_shard and gp_role.

Neon

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Neon adopts a storage and compute separation architecture, providing seamless autoscaling, scale to zero, and unique database branching capabilities.

Neon official website: https://neon.tech/

Neon binaries are currently too large to include in the open-source package set. This support path remains in pilot stage; contact Pigsty sales if you need it.