Apache Airflow observability integration
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To achieve continuous Apache Airflow observability and monitoring, IBM® Databand® features seamless Airflow integration.

Your data’s health is more complicated than a task or run failure. You need to know that your Airflow pipelines will deliver complete and accurate data on time. More importantly, you need alerts on data quality issues before they affect downstream consumers.

Integrating your Airflow environments with IBM Databand delivers continuous Airflow observability. By centralizing pipeline metadata, logs and statuses, Databand provides the insights you need to consistently deliver high quality data.

Use cases
Observe and monitor Airflow clusters

Databand integrates with the most popular managed Airflow clusters, including Google Cloud Composer, Astronomer and Amazon MWAA.

Proactively alert on data pipeline incidents

Analyze and alert on metadata anomalies or missing data, then trace the root cause of pipeline failures, data quality problems and the impact issues on your data deliveries.

Centralize pipeline metadata for continuous tracking

With a bird’s eye view of all your Airflow instances, Databand makes it easy to track pipeline statuses, run durations, data volumes and data quality metrics.

Improve data pipeline health

Get visibility across DAGs, data flows and levels of infrastructure for better pipeline reliability.

How it works

Databand provides various monitoring, alerting and analytical functionality that helps you monitor the health and reliability of your Airflow DAGs. By allowing you to monitor multiple Airflow instances, it providing a centralized tracking system for company-wide DAGs.

Integrating with Databand’s Airflow connector involves a simple three-step process:

  1. Install Databand’s dbnd-airflow-auto-tracking Python package on your Airflow cluster
  2. Configure a new Airflow Syncer to create an Airflow Syncer in your Databand UI
Capabilities

Databand’s comprehensive set of capabilities helps simplify and centralize your Apache Airflow observability.

Data-in-motion observability

With powerful preventative alerting, stay on top of Airflow pipelines that are at risk for late deliveries due to long task duration. Plus, discover anomalies in data volume and gain visibility into data quality issues, such as breaking changes in your dataset structure by sources that normally fly under the radar.

Root cause analysis

Alerts bring you directly to where an incident occurs so you can drill beneath the surface and cut down on engineering’s mean-time-to-resolution. Everything you need to uncover the root cause of an issue is found on a single, easy-to-use dashboard, including pipeline inputs and outputs, error traces, logs, data source, parameters, xcoms and user metrics.

360 visibility

With all your Airflow observability activities in one place, Databand’s comprehensive dashboard makes it easy to highlight all important metrics for each of your high-stakes Airflow DAGs. Visualizations and charts of your critical data assets allow you to see whether pipeline metrics are in the right ranges and if Airflow throughput is on schedule for delivery.

Take the next step

Implement proactive data observability with IBM Databand today so you can know when there’s a data health issue before your users do.

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