Observability

Metrics, logs, traces, audit data, incident evidence, and workload health.

Learn#

• Well-Architected Lakehouse — reference · generated · needs review

Build#

• Lakeflow data engineering — Build and run ingestion, declarative pipelines, orchestration, replay, and reconciliation.
• AI and ML platform — Put MLflow, serving, Vector Search, evaluation, governance, and observability into production.

Operate#

• Platform lessons — guide · curated · needs review