Question 1easy
What do CI and CD stand for / do?
Question 2easy
What is the AI-specific addition to a standard CI/CD pipeline?
Question 3medium
Why are unit tests necessary but not sufficient for an AI app?
Question 4medium
How does an eval gate block a bad merge in CI?
Question 5hard
What cautions apply to an eval gate in CI? (Select all that apply)
Question 6medium
Why tag deployable images by git commit SHA rather than using 'latest'?
Question 7medium
Where do secrets (like API keys) come from in a CI pipeline?
Question 8hard
What is a blue-green deployment?
Question 9hard
What triggers a rollback during a canary deploy of an AI app?
Question 10medium
How does CI/CD relate to the LLMOps discipline from Track 5?
Question 11hard
Which are CI/CD pitfalls for AI apps? (Select all that apply)
Question 12medium
What kind of gate (two words) — running the golden-set regression suite in CI — blocks a merge on model-quality regression?
Question 13hard
What deploy strategy (one word) routes a small % of traffic to the new version and watches metrics before ramping up?