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DevOps & observability · #githubactions
Learn how to diagnose and fix GitHub Actions jobs that stay in the 'Queued' state, focusing on runner label mismatches, concurrency bottlenecks, and offline self-hosted agents.
Stop duplicating your GitHub Actions jobs. Learn how to use Matrix Strategies to test across multiple OS and runtime versions efficiently using include, exclude, and fail-fast settings.
actions/cache speeds up GitHub Actions by restoring your package manager's download store between runs — but only if your key includes a lockfile hash.
I run a CI workflow that connects to a PostgreSQL database during integration tests. Occasionally the workflow fails with a connection pool exhaustion error, even though the number of parallel jobs is below the database's max pool size. The workflow executes on GitHub‑hosted Ubuntu runners, which are virtual machines in Azure with a shared network stack. I s
Configuration must be available to the application without exposing credentials in source control, logs or browser code. What belongs in the runtime and which access controls matter?
Recovery needs to recreate the working service and its required data after a machine or process is lost. Which artifacts and state need protection, and how should the restore be checked?
The same project needs to behave consistently on developer machines, in CI and after deployment. Which versions, dependencies and configuration should be recorded?
A failure needs to be narrowed down before settings are changed or operations retried. Which evidence best separates application errors from environment and dependency problems?
A performance change should improve the measured workload without sacrificing correctness or wasting capacity. Which measurements and bottlenecks should be considered first?