Pit-Stop dashboard

Pit Stop 🏎️

Inspiration

Every development team has experienced it: issues that mysteriously stop moving. A pull request sits in review for days. A blocked ticket gets forgotten. An unassigned task languishes in the backlog. These silent productivity killers don't trigger alarms—they just slowly drain velocity.

We built Pit Stop after watching our own team lose weeks to invisible bottlenecks. Traditional project management tools show you what's happening, but they don't tell you what's wrong. We needed a proactive co-pilot that could detect problems before standup, suggest solutions intelligently, and even fix common issues automatically.

The name "Pit Stop" comes from Formula 1 racing—a pit stop is a critical moment where you diagnose issues, make rapid fixes, and get back on track. That's exactly what our app does for software teams.

What It Does

Pit Stop is an intelligent monitoring system for Jira that acts like a dedicated project health analyst. It continuously scans your issues and:

🔍 Smart Stall Detection

Monitors issues across all active statuses (In Progress, Review, Blocked, etc.)
Uses changelog analysis to distinguish real updates from bot noise
Detects 10+ stall patterns: no activity, missing assignees, blockers, status thrashing, assignment churning
Configurable thresholds per status (e.g., 48hrs for "In Progress", 12hrs for "Blocked")

🧠 Context-Aware Intelligence

Analyzes issue history to understand why work stalled
Identifies patterns like status ping-pong (bouncing between states) and multiple reopens
Generates contextual suggestions based on watchers, blockers, priority, and team dynamics
Distinguishes meaningful activity from noise (ignores bot updates, worklogs, etc.)

🤖 Auto-Remediation

Auto-ping assignees when issues stall beyond threshold
Auto-add severity labels (stalled-critical, stalled-high) for reporting
Auto-reassign when assignee is inactive/on vacation
Auto-move status based on context (e.g., unassigned "In Progress" → "To Do")
Auto-escalate critical stalls to project leads

📊 Real-Time Dashboard

Visual breakdown of healthy vs. stalled issues
Metrics by status, assignee, and severity
Longest stalled issue tracking
Common stall reasons analysis
Team bottleneck identification

📢 Slack/Teams Integration

Daily digest summarizing all stalled issues
Instant critical alerts for severe bottlenecks
Beautiful formatted messages with direct issue links
Configurable notification preferences

💬 Smart Comment Response

Responds when users comment on stalled issues
Posts encouraging messages on healthy progress
Includes actionable next steps in every alert
Respects cooldown periods to avoid spam

How We Built It

Architecture

We built Pit Stop as a Forge app using Atlassian's platform, leveraging:

Backend (Node.js)

scanner.js: Scheduled trigger (every 5 minutes) that processes active issues
telemetry.js: Core stall detection engine with multi-factor analysis
changelogAnalyzer.js: Parses issue history to find meaningful updates
contextAdvisor.js: Generates smart, situation-specific suggestions
autoActions.js: Executes automated remediation actions
slackIntegration.js: Handles webhook communication
configManager.js: Manages persistent configuration via Forge storage

Frontend (React + Forge UI Kit)

Admin panel with three tabs: Dashboard, Thresholds, Settings, Integrations
Real-time metrics visualization
Interactive threshold configuration
Feature toggles for granular control
Webhook testing interface

Data Flow

Scheduler (5min) → Scanner → Stall Detection → Changelog Analysis
                                    ↓
                 Context Advisor → Auto-Actions → Notifications
                                    ↓
                           Jira Comments + Slack/Teams

Key Technical Decisions

Challenge: How to determine if an issue is really stalled?

Solution: Multi-signal approach combining time-based thresholds, human interaction tracking, and changelog pattern detection

Challenge: Bot updates create noise (automation changes labels, ranks, etc.)

Solution: Changelog analyzer filters bot accounts and focuses on meaningful fields (status, assignee, priority)

Challenge: Generic advice doesn't help ("this is stalled")

Solution: Context advisor fetches watchers, blockers, linked issues, and generates situation-specific suggestions

Challenge: Notification fatigue

Solution: Cooldown periods, severity-based filtering, and opt-in auto-actions

Technical Highlights

Intelligent Changelog Parsing

Distinguishes between 13+ types of bot accounts
Tracks meaningful vs. noise fields
Detects 5 behavioral patterns (thrashing, ping-pong, churning, reopens, stuck)

Dynamic Threshold Management

Per-status configuration (Blocked: 12hrs, In Review: 24hrs, etc.)
Stored in Forge storage with real-time updates
Dashboard reflects current configuration

Webhook Integration

Supports both Slack and Microsoft Teams
Rich formatting (Slack blocks, Teams adaptive cards)
Built-in connectivity testing
Graceful degradation if webhooks fail

Safe Auto-Actions

Granular toggles for each action type
Disabled by default (opt-in philosophy)
Comprehensive logging for audit trails
Respects comment cooldown to prevent spam

Challenges We Ran Into

1. Distinguishing Signal from Noise

Issue histories contain dozens of automated updates (rank changes, sprint updates, time logging). Our first iteration flagged everything as "activity," making stall detection useless.

Solution: Built a sophisticated changelog analyzer that:

Identifies bot accounts by name patterns and account type
Whitelists meaningful fields (status, assignee, priority)
Calculates "real" last activity time ignoring noise

2. Jira API Rate Limiting

Processing 50+ issues with full changelog data triggered rate limits, causing scanner timeouts.

Solution:

Batch requests efficiently
Added 100ms delays between issues
Cached issue data during single scan cycle
Prioritized critical data fetching

3. React State Management in Forge UI Kit

Forge's UI Kit has limitations compared to standard React—no localStorage, restricted hooks.

Solution:

Used useForm hook for form state
Stored configuration in Forge backend storage
Implemented optimistic UI updates with verification

4. Generic Advice Problem

Early versions just said "this issue is stalled"—not helpful.

Solution: Built context advisor that:

Fetches additional context (watchers, blockers, linked issues)
Matches stall patterns to specific suggestions
Prioritizes actionable advice over generic warnings

5. Webhook Testing & Debugging

Testing Slack/Teams integration required constant redeployment.

Solution:

Built in-app webhook testing
Added comprehensive logging
Created graceful error handling
Provided setup guides with screenshots

6. Configuration Complexity

With 20+ settings, the admin UI became overwhelming.

Solution:

Organized into logical tabs (Dashboard, Thresholds, Settings, Integrations)
Used progressive disclosure (advanced options hidden by default)
Added inline help text and tooltips
Provided sensible defaults

Accomplishments That We're Proud Of

🎯 It Actually Works in Production

We dogfooded Pit Stop on our own Jira instance. In the first week, it caught:

3 critical issues blocked for 5+ days
12 pull requests stuck in code review
5 unassigned high-priority bugs

🧠 Genuinely Intelligent Detection

The changelog analysis and pattern detection caught issues that we didn't notice. The "status thrashing" pattern revealed a workflow problem we'd been blind to.

🤖 Auto-Actions That Don't Annoy

We were terrified auto-actions would spam the team. But the cooldown logic, severity-based filtering, and conservative defaults made them genuinely helpful—not annoying.

📊 Dashboard That Provides Insight

The dashboard doesn't just show numbers—it reveals team bottlenecks. Seeing "7 issues stalled with Bob" made us realize he was overloaded.

🎨 Beautiful Slack Messages

The daily digest looks professional. Using Slack blocks with proper formatting, severity icons, and clickable links makes it feel like a premium tool.

🏗️ Clean Architecture

Despite growing to 2,000+ lines of code, the codebase remains maintainable with clear separation of concerns:

Detection logic isolated in telemetry.js
Actions separated in autoActions.js
Configuration centralized in configManager.js
Frontend completely decoupled from backend

What We Learned

Technical Lessons

API Design Matters: Jira's REST API is powerful but verbose. Learning to optimize queries (limiting fields, using POST for search) was crucial.
Changelog is Gold: Issue history contains incredible signals if you parse it correctly. The difference between bot updates and human changes is night and day.
Context is Everything: Generic alerts are noise. Specific, actionable suggestions based on issue context are transformative.
Progressive Enhancement: Starting with basic stall detection, then adding changelog analysis, then auto-actions—building features incrementally kept quality high.
Observability Matters: Comprehensive logging made debugging production issues manageable. Every action logs its intent and result.

Product Lessons

Defaults Are Critical: Most users never change settings. Our conservative defaults (auto-actions disabled, high thresholds) prevented disaster.
Test Before Deploy: The webhook testing feature saved us from broken production deployments.
Provide Escape Hatches: Granular feature toggles let teams adopt gradually—enable detection first, add auto-actions later.
Documentation Wins: The in-app setup guides reduced support questions dramatically.

Team Lessons

Dogfood Early: Using Pit Stop ourselves revealed UX issues faster than any testing.
Listen to Frustration: The best features came from our own pain points (forgotten blockers, stuck PRs).
Iterate Quickly: Forge's deployment cycle let us ship fixes in minutes, not days.

What's Next for Pit Stop

🚀 Near-Term (Next 3 Months)

Bi-Directional Slack Integration

Reply to Pit Stop in Slack to assign issues
Slash commands like /pitstop status PROJ-123
Interactive buttons (Assign Me, Mark Resolved)

Custom Stall Rules

User-defined JQL-based detection
Composite conditions (e.g., "High priority + No assignee + 3+ days")
Custom webhook templates

Team Analytics

Velocity tracking over time
Stall frequency by team member
Bottleneck heat maps
Sprint health reports

ML-Powered Predictions

Predict which issues are about to stall
Recommend optimal assignees based on history
Estimate resolution time with confidence intervals

🎯 Mid-Term (6 Months)

Integration Ecosystem

GitHub PR status sync
Linear integration
Asana connector
Notion sync

Smart Workflows

Auto-create sub-tasks when issues stall
Trigger custom automation rules
SLA breach prevention

Mobile App

Push notifications for critical stalls
Quick-assign from phone
Dashboard widgets

🌟 Long-Term Vision

AI Assistant

Natural language queries: "Show me Bob's stalled issues"
Automated root cause analysis
Predictive resource allocation

Enterprise Features

Multi-project dashboards
Organization-wide analytics
Custom compliance rules
SSO integration

Marketplace Ecosystem

Plugin architecture for custom actions
Community-contributed detection rules
Shared best practices library

Impact Potential

Pit Stop addresses a $100B+ problem: according to Gartner, inefficient project management costs enterprises $109M per $1B invested annually. By catching invisible bottlenecks:

Reduce cycle time by 15-30% (catch stalls before they compound)
Improve team morale (no more "forgotten" work)
Increase transparency (managers see bottlenecks in real-time)
Prevent burnout (auto-reassignment when people are overloaded)

For a 50-person engineering team losing 20% productivity to invisible stalls:

Annual cost: ~$500K in lost productivity
Pit Stop potential savings: $75K-150K/year
ROI: 50-100x the cost of the tool

Conclusion

Pit Stop transforms Jira from a passive tracking tool into an active productivity partner. It doesn't just report problems—it diagnoses, alerts, and fixes them automatically.

We're excited to bring this to teams everywhere, helping developers spend less time managing work and more time building great products.

Try Pit Stop today and stop letting work stall. 🏎️💨

Built with ❤️ using Atlassian Forge, React, and way too much coffee.