A job fails with a quota error. What is the right response?
Why C is the answer
Check quotas, and request an increase if needed
A quota error means you should check your quotas, and request an increase if needed.
In detail
- Check the quota, and request an increase if needed.
- Sometimes reducing use is better.
Use case
An illustrative scenario, not a real incident.
A job fails with a quota error, so the team checks usage, and requests an increase.
See it in different ways
sequenceDiagram participant C as Managed Service for Apache Airflow participant J as Dataproc job participant L as Cloud Logging participant O as Operator C->>J: Start the step J--xC: Fails C->>J: Retry J->>L: Logs C-->>O: Alert if retries run out
flowchart LR S0["Read the error"] --> S1["Check usage"] --> S2["Reduce or request more"]
Key point: Check quotas first.
Why the other options are wrong
- A. Rewrite the pipeline in another language
- A rewrite does not fix a quota.
- B. Disable logging
- Disabling logs hides the evidence.
- D. Delete the dataset
- Deleting data does not fix a quota.