Daisy-DAG is a YAML-driven, production-ready DAG workflow engine with parallel execution, retries, conditional branching, batch iteration, and pluggable actions.
Key Takeaways
Defined via YAML DSL; engine validates, executes, and visualizes workflows from a single config.
Supports parallel execution, retries, and conditional branching out of the box.
Batch iteration and pluggable actions enable extensible pipeline composition.
Repo ships with backend, frontend, Docker, and docker-compose for self-contained deployment.
Hacker News Comment Review
The sole substantive critic flags no comparison to mature orchestrators (Airflow, Prefect, Temporal) and questions whether this is a learning exercise rather than a production alternative.
YAML as the workflow DSL draws skepticism; commenters expect code-native or typed DSLs in newer orchestration tools.
