{"id":"apache-airflow","name":"airflow","af_score":16.5,"security_score":17.0,"reliability_score":46.2,"what_it_does":"Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows (DAGs). It executes tasks via a scheduler and workers, provides a UI for visualization/monitoring, and supports defining pipelines as code.","best_when":"Your workflow structure is mostly static/slow-changing and you can model execution as DAG-based tasks with idempotent operators and external services for heavy/high-volume processing.","avoid_when":"You need a streaming-first system or you expect to pass large data payloads between tasks through Airflow primitives rather than via external storage/services.","last_evaluated":"2026-03-29T12:58:43.068922+00:00","has_mcp":false,"has_api":false,"auth_methods":[],"has_free_tier":false,"known_gotchas":["Airflow is an orchestrator/platform, not a simple API service; an agent may need substantial domain knowledge and infrastructure configuration (scheduler/workers, DB, message queues, connections).","README indicates pip-only installation is officially supported (install complexity is non-trivial without constraints).","Operational issues (task retries, dependency management, worker concurrency) depend on DAG/operator configuration not shown in the README excerpt."],"error_quality":null}