Results for “deployment-pipeline”

Design and implement ML operations — model registry, serving patterns, deployment strategies (shadow/canary/blue-green), drift detection, feature stores, retraining triggers, and prediction monitoring. Use when asked to "deploy a model", "model registry", "MLflow", "feature store", "drift detection", "retrain trigger", "shadow mode", "model versioning", "serving infrastructure", or "ML pipeline". Do NOT use for: prompt engineering or RAG pipelines — see prompt-engineering and rag-architect skills. Do NOT use for: general API deployment without an ML component.

Coordinate end-to-end deployments across Stripe, Supabase, and Vercel using the Composio CLI. Update pricing, apply database migrations, deploy frontend, verify changes, and announce releases from a single script.