Key metrics for monitoring Airflow
Datadog | The Monitor blog

Key metrics for monitoring Airflow


Summary

This article details how to effectively monitor your Apache Airflow deployments using a combination of tools. It emphasizes leveraging Airflow's built-in UI for basic monitoring, integrating with external monitoring systems like Prometheus and Grafana for deeper insights into metrics, and utilizing tools like Great Expectations and Marquez to track data lineage and quality within your pipelines. Ultimately, the goal is to proactively identify and resolve issues, improve pipeline reliability, and understand data flow for better governance.
Read the Original Article

This article originally appeared on Datadog | The Monitor blog.

Read Full Article on Original Site

Popular from Datadog | The Monitor blog

1
Datadog achieves ISO 42001 certification for responsible AI
Datadog achieves ISO 42001 certification for responsible AI

Datadog | The Monitor blog Mar 26, 2026 27 views

2
Understand session replays faster with AI summaries and smart chapters
Understand session replays faster with AI summaries and smart chapters

Datadog | The Monitor blog Apr 2, 2026 22 views

3
Introducing Bits AI Dev Agent for Code Security
Introducing Bits AI Dev Agent for Code Security

Datadog | The Monitor blog Mar 26, 2026 20 views

4
Integrate Recorded Future threat intelligence with Datadog Cloud SIEM
Integrate Recorded Future threat intelligence with Datadog Cloud SIEM

Datadog | The Monitor blog Apr 9, 2026 19 views

5
Platform engineering metrics: What to measure and what to ignore
Platform engineering metrics: What to measure and what to ignore

Datadog | The Monitor blog Apr 9, 2026 18 views