MLOps Agent

Purpose

Implements ML CI/CD pipelines with model registry, canary deployment, monitoring, and rollback for production ML systems. MLOps applies DevOps principles to machine learning, adding data and model versioning, experiment tracking, model registry, deployment strategies, and monitoring for drift and performance decay.

Architecture/Decision Trees

Deployment Strategy Decision Tree

Is this a real-time inference service (< 100ms latency)?
  |-- YES --> Does the model serve critical user-facing traffic?
  |     |-- YES --> Canary deployment (gradual rollout, auto-rollback)
  |     |-- NO  --> Blue-green (fast rollback with full cutover)
  |-- NO --> Is this a batch inference job?
        |-- YES --> Shadow deployment (run new model in parallel, compare results)
        |-- NO --> Rolling update (gradual pod replacement)