Learning term
Worker crash — Incident analysis and recovery
A worker crash unexpectedly terminates the processing process during or before a job. This card shows its role in “Incident analysis and recovery” and a safe diagnostic path.
Orientation
A worker crash unexpectedly terminates the processing process during or before a job. At this level, separate purpose, input, and visible result. Place Worker crash within Incident analysis and recovery before changing settings or files.
Practical use
A previously reachable service fails after a change. For Worker crash, preserve the timeline, task history, exit code, latest logs, and resource state; then test the smallest justified correction and confirm recovery with the same request. Start in a sandbox with neutral examples. Record the expected state, make one controlled change, and compare status output, application behavior, and logs.
Technical understanding
A worker crash unexpectedly terminates the processing process during or before a job. Technically, Worker crash connects through interfaces, configuration, state, or dependencies. Trace data from input to output and check versions, permissions, networking, storage, and resources separately.
Operations and debugging
A previously reachable service fails after a change. For Worker crash, preserve the timeline, task history, exit code, latest logs, and resource state; then test the smallest justified correction and confirm recovery with the same request. In production-like operations, use measurable signals, least privilege, reproducible configuration, and a documented rollback. Preserve evidence, isolate the cause, and verify the correction with the same test.
Exercise
Try it safely
A previously reachable service fails after a change. For Worker crash, preserve the timeline, task history, exit code, latest logs, and resource state; then test the smallest justified correction and confirm recovery with the same request. Open an isolated test environment and run “docker service ps example-service --no-trunc”. Write down the expected output first, do not alter production data, and record one safe next diagnostic step.
docker service ps example-service --no-truncQuick check
Can you explain the purpose, observable state, and most common failure source of Worker crash — Incident analysis and recovery in one sentence each? Which evidence would you preserve before changing anything, and which repeated test would prove that the correction actually worked?