SageMaker AI and MLflow Execution Quiz
Multiple Choice Questions
- Which resource is used for new managed MLflow deployments?
- A) Only the legacy Tracking Server
- B) SageMaker MLflow App
- C) A public EKS LoadBalancer
- D) Only a local SQLite file
Show Answer
Answer: B
The managed path uses the current SageMaker MLflow App API.
- What is required before a full run?
- A) A completed smoke run and raw-PII logging scan
- B) Removal of project membership
- C) Immediate maximum-step execution
- D) Disabled teardown
Show Answer
Answer: A
Review smoke completion, logging safety, aggregate results, and adapter inventory first.
- What is the EKS Job failure/deadline contract?
- A) Unlimited retries and no deadline
- B)
backoffLimit: 0andactiveDeadlineSeconds: 10800 - C) Ten retries and one hour
- D) A permanent Deployment
Show Answer
Answer: B
These are retry and Job deadline settings. Controller or node failures can delay reclamation; they do not guarantee all resources disappear within three hours or cap total cost.
- When must cleanup verification fail?
- A) No resources remain
- B) Resources remain or errors prevent confirming their state
- C) Smoke succeeds
- D) Dataset hashes match
Show Answer
Answer: B
Zero remaining is insufficient when queries failed. Preserve unknown states and refuse name-only deletion from old inventories without ownership evidence.
- What was actually exercised on September 1?
- A) A full SageMaker Training Job
- B) A full EKS GPU Job
- C) Provisioning and cleanup paths
- D) Tuned-model evaluation
Show Answer
Answer: C
Both GPU Jobs stopped before submission.
- Why is GPU execution blocked as of September 12, 2026?
- A) The pinned PyTorch 2.8 DLC reached end of patch on August 6
- B) Source bundling is billable
- C) Every MLflow App was deleted
- D) Local unit tests require a GPU
Show Answer
Answer: A
Validate a supported DLC, torch, dependency cohort, and GPU smoke run. Removing the date check alone is not an upgrade.
- What does the SageMaker launcher do without
--execute?- A) Submit the full Job immediately
- B) Write the request JSON only
- C) Delete existing Jobs
- D) Guarantee a cost estimate
Show Answer
Answer: B
Request preview is the default. Actual submission requires the runtime support check and separate review.
- Is saving EKS MLflow metric/parameter JSON enough?
- A) Yes, it automatically includes adapter weights
- B) Download final adapters and aggregate artifacts, then verify hashes
- C)
emptyDirsurvives cluster deletion - D) A log tail can reconstruct the model
Show Answer
Answer: B
Metadata export is different from preserving files. A cluster retained after export failure also needs cost awareness and subsequent cleanup.