MLOps interview questions and answers

Recompute the historical offline table for the affected window, version the new feature, and decide whether to retrain.

Atomic adds, cuDNN autotune, and mixed precision can change reduction order and thus floats.

Store a dataset hash, partition dates, query, and DVC or table snapshot ID with the run.

dvc.yaml declares stages with deps, outs, and commands so DVC can skip unchanged steps using checksums.

Push cache to a shared remote, pull before experiments, and keep .dvc files in the same PR as code that consumes that data.

Start small enough that a disaster is contained, but large enough to see latency and error signal within minutes, often 1 to 5 percent.

Shadow serving sends live features to the new model but does not affect the user

Blue-green stands up a full new environment and switches all traffic at once after checks.

I would check deploy correlation, GC or Python GIL stalls, feature store latency, GC of large batches, and downstream timeouts.

If a shared dependency such as a feature store, GPU, or database is saturated, extra Pods just queue there.

Replay production-like payloads, including feature store hits and batch size mix, not a tiny tensor of zeros.

REST/JSON is simple to curl and debug

They are Kubernetes-native serving layers that roll out models, scale, and sometimes canary using custom resources.

Kubeflow is closer to Kubernetes-native ML steps, artifacts, and retries on GPU Jobs.

Make steps idempotent, checkpoint weights, and retry from the last successful stage rather than restarting a six-hour fit.

Require tags for project, owner, and git SHA, expire old artifacts, and delete failed smoke runs.

A kill switch routes traffic to a previous model, a heuristic, or a default deny/allow without a full cluster rollback.

A model card documents intended use, data, metrics, limitations, and ethical notes for a version.

Minimize fields, encrypt, tokenize identifiers, set retention, and restrict access.

Clock skew in timestamps, different timezone handling, online features that are not backfilled, and batch aggregations that include the label window.