MLOps interview questions and answers

I would snapshot reference histograms from the training window, then compare live daily distributions with PSI or KS per feature.

If the model is well calibrated on the new region of X, or if the shift is a known campaign you already encoded as a feature, retraining can wait.

Track frequency of each level, the share of unknown or new levels, and entropy of the distribution.

Use proxy or leading indicators, such as chargeback rates that arrive earlier, and monitor residual errors on a delayed labeled sample.

If the model’s scores change who gets a loan, future training data is selected by the previous model.

Unit tests for transforms, schema tests on sample data, a tiny training job that must beat a dummy baseline, and a serving smoke test that loads the artifact.

After training, an evaluation step compares the candidate to the current champion on a frozen eval set and required slices.

A golden set is a versioned batch of inputs with expected scores or labels used as a regression test.

Inject them from a secret manager at runtime, never commit them, and scope IAM to read-only training tables.

Pin the CUDA base image digest, driver-compatible tags, and Python lockfile, and record nvidia-smi output in the run.

The builder stage can contain compilers and test deps

Prefer safer formats such as ONNX, safetensors, or joblib only inside trusted images, and treat pickle as a last resort.

Liveness restarts a stuck process

Requests help the scheduler place Pods

The Horizontal Pod Autoscaler adds replicas from CPU, memory, or custom metrics such as queue depth or QPS.

Use a Job or a workflow CRD such as Kubeflow or Argo, not a long-lived Deployment.

Staging is for candidates that passed offline gates and maybe shadow traffic.

Log the entire Pipeline with mlflow.sklearn.log_model so preprocessing and estimator stay together, plus a conda or pip environment.

The tracking DB stores metadata

Operational monitoring is RED or USE metrics: rate, errors, duration, CPU, memory.