In the fast-paced world of CI/CD, understanding the performance and behaviour of your pipelines is crucial. GitHub Actions has become a popular choice for automating builds and deployments, but anyone who's debugged a flaky workflow or long-running job knows how challenging it can be to get visibility into what's happening under the hood. We usually rely on build logs, timing data, or guesswork when something goes wrong. Wouldn't it be nice to trace a pipeline run step-by-step, or have metrics on how your workflows are performing over time? This is where OpenTelemetry comes into play.
OpenTelemetry [OTel] is an open-source observability framework that enables collecting traces, metrics, and logs in a standard, vendor-agnostic way. With a bit of configuration, OTel can capture telemetry from even our CI/CD pipelines. In this guide, we'll walk through setting up OpenTelemetry for GitHub Actions [covering both tracing and metrics], with practical examples and configuration snippets.
Why Observe CI/CD Pipelines with OpenTelemetry [OTel]?
Just as we use traces and metrics to understand microservices and applications, we can apply the same to CI/CD pipelines. Instrumenting GitHub Actions with OpenTelemetry yields several benefits:
End-to-end visibility: You can trace the entire lifecycle of a workflow run, from trigger to completion. Each job and step can be visualised, showing how they execute and interact.
Performance optimisation: By measuring the duration of each job and step, you can identify bottlenecks or slow steps in your pipeline. For example, a long testing phase or a slow dependency installation.
Error detection and debugging: Traces can pinpoint exactly where a workflow failed or took an unexpected path, making it easier to debug broken pipelines. Instead of combing through logs, you'll see which step or action resulted in an error.
Dependency analysis: In complex workflows with multiple jobs [possibly with dependencies or concurrent runs], tracing helps you understand how different jobs and steps relate to each other within the workflow.
Traditionally, engineering teams have monitored CI pipelines using ad-hoc methods, maybe exporting build logs to an ELK stack, timing data to Prometheus, or using CI-specific analytics. Those approaches often cover only metrics [like durations, success/failure counts] or logs. OpenTelemetry provides a unified approach, it can capture traces [for structure and timing] and metrics [for quantitative monitoring] in one system.
Every pipeline run can become a trace, and important KPIs can be emitted as metrics using OTel. Next, we'll see how to set this up with GitHub Actions.
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