Principal/Senior-level Airflow playbook for DAG architecture, scheduling reliability, dependency management, platform governance, and operating workflow orchestration safely at scale.
Use when: designing DAG ecosystems, reviewing orchestration patterns, scaling schedulers and executors, or operating Airflow in production.
Installation
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Principal/Senior-level Airflow playbook for DAG architecture, scheduling reliability, dependency management, platform governance, and operating workflow orchestration safely at scale.
Use when: designing DAG ecosystems, reviewing orchestration patterns, scaling schedulers and executors, or operating Airflow in production.
Airflow Mastery (Senior → Principal)
Operate
Start from orchestration semantics, data dependencies, and failure ownership.
Treat Airflow as workflow control infrastructure, not as a place to hide business logic.
Prefer DAGs that remain readable, recoverable, and operationally predictable.
Optimize for reliability, clear retries, and low scheduler toil.
Default Standards
DAG boundaries should reflect real workflow ownership.
Tasks should be idempotent and retry-aware.
Scheduling semantics must match data availability and SLA reality.
Platform governance should control DAG sprawl and dependency chaos.
Airflow should orchestrate systems, not become the system.