Tutorials

If you are a developer, especially running a small business and delivering applications to your customers alone, you don’t have time and you don’t want to care about “everything DevOps”. You don’t want to care about pipelines, about deployments, and especially about infrastructure. You simply don’t have time to learn it deeply and later manage […]

Managing data at scale is now baseline. Teams must reliably ingest, store, transform, process, and serve data across many sources and consumers. A modern data platform sits at the core of well-run companies. It drives market insight, shows the state of the business, and powers the AI systems teams rely on. This tutorial is courtesy […]

Use this tutorial if you’re ready to build. You’ll provision an UpCloud VM with the OpenTofu UpCloud provider, configure remote state on an S3-compatible bucket (with DynamoDB locking), enable client-side AES-GCM encryption for state and plans (OpenTofu ≥1.7), add guardrails with Conftest + OPA, and optionally verify Terraform compatibility via import. If you want the […]

If you’ve already explored our earlier guide, Understanding Distributed Tracing and Why Jaeger Matters, you know how tracing helps connect the dots between microservices, latency, and performance in modern systems. If not, give it a quick read first it breaks down the core concepts and why tracing is essential in modern observability. In this tutorial, you’ll put […]

In our earlier guide, What is OpenTelemetry? Understanding the Standard for Cloud-Native Observability, we explained how OpenTelemetry standardizes the collection of metrics, traces, and logs across distributed systems. Then, in the follow-up tutorial, How to Deploy OpenTelemetry on UpCloud Managed Kubernetes, we showed how to put those concepts into practice by deploying the OpenTelemetry Collector […]

OpenTelemetry gives you a unified, open-source framework for collecting metrics, traces, and logs across your cloud-native infrastructure. In this tutorial, you’ll learn how to deploy a complete OpenTelemetry pipeline on UpCloud Managed Kubernetes from setting up the cluster and deploying the OpenTelemetry Collector, to instrumenting a Python application and verifying telemetry flow into your observability […]

So far in this series, you’ve built a complete observability foundation on UpCloud. You’ve set up Prometheus and Grafana to monitor infrastructure-level metrics from Kubernetes and VMs, and you’ve added application-level instrumentation using Prometheus client libraries for real-time insights into your workloads. With dashboards and alerts in place, your system is observant. The only aspect […]

After setting up the foundation with infrastructure-level monitoring in earlier parts of this series (tracking Kubernetes workloads, VM metrics, and visualizing them in Grafana), you have a solid understanding of system health and resource usage monitoring. But infrastructure metrics only tell part of the story. To truly understand your applications’ behavior, you need to observe […]

In the first two parts of this series, we walked through setting up Prometheus on an UpCloud-managed Kubernetes cluster and began collecting metrics from both the cluster and external VMs using Node Exporter. With Prometheus scraping metrics effectively, the next logical step is turning that raw data into meaningful visual insights. That’s where Grafana comes […]

After setting up Prometheus in Part 1 on a dedicated UpCloud Managed Kubernetes cluster, with support for both Kubernetes-native workloads and external VMs, you now have a flexible monitoring foundation in place. But collecting metrics is only as good as the visibility it provides. To truly understand what’s happening on your virtual machines, you’ll need […]