Pipeline Observability: Know When Things Break

An analyst messages you on Slack: "The revenue numbers look wrong. Is the pipeline broken?" You check the orchestrator — all green. You check the target table — data loaded this morning. You check the row count — looks normal. Forty-five minutes later, you discover that a source API returned empty responses for one region, and the pipeline happily loaded zero rows for that region without alerting anyone. The pipeline succeeded. The data was wrong. No one knew until a human noticed. This is the cost of monitoring pipeline execution without monitoring pipeline output. You Can't Fix What You Can't See Traditional monitoring answers: did the job run? Did it succeed? How long did it take? These questions cover infrastructure health, not data health. A pipeline can execute perfectly — no errors, no retries, no timeouts — and still produce incorrect or incomplete data. Observability goes further. It answers: what did the pipeline process? How much? Was the data complete and correct? Is the ou