How should a training DAG handle a mid-job failure?
PICTURE THIS: DATA SPLIT
Fit on train, tune on val, report on test once.
Simple meaning
Make steps idempotent, checkpoint weights, and retry from the last successful stage rather than restarting a six-hour fit.
WHY — Orchestration instead of guessing?
Why interviewers care about Orchestration:
who only read docs from people who shipped.
and tied to MLOps work.
Name the idea, why it exists, then one short example.
End with when you use it and one common pitfall.
STEPS — What happens step by step?
Before you speak the answer, walk the interviewer through these steps:
- 1Make steps idempotent, checkpoint
weights, and retry from the last successful stage rather than restarting a six-hour fit.
- 2Persist intermediate artifacts in
object storage.
- 3Alert on repeated failure
so you do not silently skip the daily champion refresh.
- 4Give an example
One tiny concrete case you can say aloud.
- 5Common mistake
What juniors usually get wrong.
- 6Close
When you pick this over the alternative.
EXAMPLE — See it in action
Here's a short line you can speak, broken into clear beats:
Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.
Key takeaway
Make steps idempotent, checkpoint weights, and retry from the last successful stage rather than restarting a six-hour fit. Persist intermediate artifacts in object storage.