How to Debug CI/CD Pipelines: A Handbook on Troubleshooting with Observability Tools

Observability is a game-changer for CI/CD pipelines, and it’s one of the most exciting aspects of DevOps. When I started working with CI/CD systems, I assumed the hardest part would be building the pipeline. But with increasingly complex setups, the ...

Jun 17, 2025 - 08:50

How to Debug CI/CD Pipelines: A Handbook on Troubleshooting with Observability Tools

Observability is a game-changer for CI/CD pipelines, and it’s one of the most exciting aspects of DevOps. When I started working with CI/CD systems, I assumed the hardest part would be building the pipeline. But with increasingly complex setups, the real challenge is debugging failures, like builds crashing or tests failing only in production.

Observability tools, such as logs, metrics, and traces, provide the visibility you need to pinpoint issues quickly. In this handbook, we’ll explore free and open-source tools you can use to make your CI/CD pipelines more reliable. We’ll use practical steps to troubleshoot like a pro – no enterprise licenses required.

Prerequisites

There are some things you should know and have to get the most out of this handbook:

Technical Knowledge:

Basic understanding of CI/CD pipelines (for example, build, test, deploy stages).
Familiarity with Linux/Unix commands (for example, mkdir, grep, curl).
Comfortable with Docker basics (for example, docker run, docker-compose up).
Optional: Awareness of observability concepts (logs, metrics, traces) or YAML configuration.

Software and Tools:

Docker and Docker Compose: Installed and running (verify with docker --version and docker-compose --version).
CI/CD Platform: Access to GitHub Actions, Jenkins, or GitLab CI with a sample pipeline that generates logs.
Text Editor: For editing YAML files (for example, VS Code, Nano).
Web Browser: To access tool UIs (for example, Grafana on port 3000, Kibana on 5601).
Optional: curl for testing log forwarding, Git for version control.

Hardware and Infrastructure:

Machine with:
- OS: Linux, Windows (with WSL2), or macOS.
- 4GB RAM (8GB recommended), 20GB free disk space.
- Stable internet and ability to open ports (for example, 3100 for Loki, 9200 for Elasticsearch).
Optional: Cloud provider access (for example, AWS, GCP) for scalable setups.

Access and Permissions:

Admin access to install Docker and configure CI/CD tools.
Permissions to modify pipeline configs (for example, .github/workflows, .gitlab-ci.yml).
Optional: Container registry access (for example, Docker Hub) for custom images.

Why Observability is Important

Modern CI/CD pipelines are no longer linear scripts – they are now complex, distributed systems involving multiple tools, environments, and infrastructure layers. One job runs on GitHub Actions, another deploys via Jenkins, and a third builds Docker images in a Kubernetes cluster.

So when something breaks, you’re left chasing logs across tools, guessing where the issue originated, and wasting hours trying to reproduce it.

And worse still, traditional debugging tools often stop at the surface, only showing failed jobs without the context of why they failed or where in the system the fault actually lies.

Observability flips the script. Instead of hunting through disconnected logs or rerunning failed builds blindly, observability gives you insight, not just data. By combining structured logs, metrics, and traces, you can:

Reconstruct exactly what happened in a pipeline failure
Trace a failure across CI agents, deployment steps, and containers
Visualize patterns and anomalies before they become outages

More importantly, observability helps you move from reactive debugging to proactive prevention.

Here’s what you’ll learn about and accomplish in this guide:

Set up cost-effective observability using Grafana Loki, lightweight ELK, and OpenTelemetry
Create a unified logging strategy to connect your pipeline
Write precise queries to quickly pinpoint root causes, correlate logs, metrics, and traces for comprehensive debugging
Troubleshoot CI/CD issues like build failures, flaky tests, and container crashes
Build custom dashboards and automated diagnostic tools
Promote observability through documentation and post-mortems

Whether you're a solo developer or part of a DevOps team, this guide will transform your chaotic CI/CD pipelines into clear, reliable, and observable systems.

How to Choose the Right Observability Tool for CI/CD

Here’s a quick comparison of Grafana Loki, Lightweight ELK, and Vector for CI/CD observability:

Tool	Resource Usage	Setup Complexity	Best For	CI/CD Fit
Grafana Loki	Low (lightweight)	Easy (Docker-based)	Small teams, budget infra	Simple pipelines, JSON logs, Grafana users
Lightweight ELK	High (Elasticsearch-heavy)	Moderate (multi-container)	Teams needing advanced search/visualization	Complex pipelines, rich querying needs
Vector	Very low	Easy (single binary)	Resource-constrained setups	Minimal setups, log forwarding

How to choose:

Loki: Ideal for startups or solo devs with limited resources. Integrates well with Prometheus/Grafana.
ELK: Best for teams needing Kibana’s advanced visualizations or handling large log volumes.
Vector: Great for lightweight log forwarding in distributed CI/CD setups.

Grafana Loki is a log aggregation system like ELK, but it's more lightweight, and it’s ideal for CI/CD pipelines with limited infrastructure.