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Upgrade to PremiumQ1. What's the difference between what a Pool limits and what max_active_tasks limits?
max_active_tasks limits concurrency within a single DAG only. A Pool limits concurrency for tasks assigned to it across every DAG in the deployment - the only mechanism that caps concurrent usage of a specific shared resource regardless of which DAG is requesting it.
Q2. Why does an SLA miss get triggered even for a task that only took 5 minutes to actually run?
SLA time is measured from the DAG run's logical start time, not from when that specific task began executing - time spent queued behind other work counts against the SLA just as much as actual execution time.
Q3. A DAG has catchup=False. Does that prevent someone from manually backfilling a historical date range later?
No - catchup=False only stops Airflow from automatically running every missed interval when the DAG is unpaused. A manual airflow dags backfill for a specific date range works regardless of the DAG's catchup setting.
Q4. What's the main practical benefit of DAG Bundles in Airflow 3.0 over the git-sync/shared-volume patterns from the Architecture module?
Airflow itself becomes aware of where DAG code comes from (a specific Git repo and ref) as first-class, queryable state - rather than relying on external tooling to keep a shared filesystem in sync, with no built-in way to ask Airflow which commit is actually deployed.
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