How do retries and checkpoints work for cloud media jobs?

How do retries and checkpoints work for cloud media jobs?

Cloud execution can fail because of transient dependencies, resource limits, or process termination. A restart should know what work is safe to reuse.

Checkpoint durable progress

Save validated stage outputs with input versions and attempt identity. On restart, verify that a checkpoint’s object still exists and matches the current job. An incomplete local file is not a trustworthy checkpoint. Classify failures so invalid input does not consume repeated automatic attempts.

Keep completion consistent

Configure bounded retries and record attempt outcomes. Use conditional finalization so a late older attempt cannot replace a newer result. Google’s Cloud Run retry guidance emphasizes restart-safe jobs and checkpointing; apply those ideas to the application’s artifact lifecycle. Test a forced interruption between stages and confirm the job resumes or fails clearly without producing conflicting final outputs.

Further reading: Cloud Run retries and checkpoints.