Airflow DagRuns
This page provides drill-down visibility into DAG execution history.
Pulse enables full-stack observability for Airflow on Kubernetes by combining:
- DAG-level monitoring
- Task-level drilldowns
- Scheduler and executor health tracking
- Resource utilization visibility
- Performance trend analysis
- Operator-level metrics
This allows faster root cause analysis, improved SLA tracking, and proactive workload optimization.
Steps
- In the Pulse UI, go to Airflow on the left pane.
- Select DagRuns.
DAGs
- DAG ID — Unique DAG name
- Owner — DAG owner
- Recent Runs — Status indicators of the latest runs
- Schedule — Cron or preset schedule
- Paused — Whether DAG is paused
- Start Date — Initial activation date
Runs Section
For each DAG run:
- Run ID — Unique run identifier
- State — Success, Failed, Running, etc.
- Run Type — Scheduled, Manual, Backfill
- Started At — Execution start time
- Queued At — Time entered queue
- Ended At — Completion time
DAG Run Details
Provides deep observability for a specific DAG run.
Run Summary
Run Information
- Run ID
- Run Type
- State
Timing Details
- Started At
- Queued At
- Ended At
- Duration
DAG Run Trends
Compares:
- Elapsed Time
- Queued Duration
Across historical runs.
Tasks Table
For each task:
Task Information
- Task ID
- Job ID
- Operator
Execution Status
- Previous State
- Current State
Timing Details
- Queue
- Started At
- Ended At
- Duration
Resource and Scheduling
- Pool
- Pool Slots
- Priority Weight
Task Tries
- Shows retry attempts and retry behavior trends.
Landing Times
- Displays task scheduling, landing times, and execution distribution.
Execution Timeline
Visual timeline view showing:
- Task execution order
- Parallelism
- Dependencies
- Branch behavior
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