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Prizm connects to Apache Airflow to catalog DAGs and tasks, monitor pipeline health through operational metrics, and stitch lineage across Airflow and the data warehouses it orchestrates. Once connected, every DAG run is tracked — duration, success rate, freshness — and failures surface as Prizm alerts alongside your data quality alerts.

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Connection Modes

Prizm supports three ways to connect to Airflow. The mode determines who initiates the connection, where credentials live, and how quickly metadata arrives. The mode is set at source creation and cannot be changed afterward — switching requires creating a new source.
API Pull is the only mode with automatic retries. CLI and Plugin both fail silently on a transient network issue. If you choose either and freshness matters, monitor for gaps via scheduler logs.

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Metrics

Prizm evaluates four pipeline health metrics for each connected Airflow source: Auto-thresholded metrics derive a normal band from few runs up to 100 prior historical values based on settings. They need sufficient run history before thresholds activate; new DAGs with few runs will show the metric value without an alert threshold until enough history accumulates. Separately, two alert options fire directly on run state regardless of which metrics are enabled:

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Lineage Support

Prizm supports three distinct types of lineage:
  1. Task Lineage (no additional connector needed): Shows task-to-task dependencies within a single DAG — this comes straight from Airflow’s own DAG structure, so it works out of the box no additional connection or connector required.
  2. Cross-DAG Lineage: Shows dependencies between DAGs based on control flow, not data — detected by reading DAG source code for TriggerDagRunOperator (one DAG kicks off another) or ExternalTaskSensor/ExternalTaskMarker (one DAG waits on a task in another).
  3. Table/Data Lineage (needs a warehouse connector): Shows which DAG feeds which table — e.g., “Task X wrote to table B.” There are two methods:
    1. Query Tag: Prizm reads the query tag attached to the warehouse query and uses it to identify and build the lineage between the DAG/task and the table.
    2. OpenLineage: Prizm captures OpenLineage job/dataset events directly and builds the lineage from them,

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What Gets Cataloged

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Next Steps

Setup

Create an Airflow source and configure API Pull or CLI mode.

Plugin Setup

Install and configure the Prizm Airflow Plugin for real-time push-based metadata.

What We Collect

Full breakdown of every field Prizm extracts from DAGs, tasks, and run history.