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DevOps & observability · #githubactions
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?
An upgrade needs a compatibility check, a tested release and a recovery path. Which changes deserve particular attention before the new version reaches production?
Compare suitability, operational responsibilities and limits before choosing this technology for a project. Which trade-offs should guide the decision?