Prefect

Prefect is a modern Python workflow orchestration framework designed for building resilient data platforms. It lets developers turn any Python function into an observable, orchestratable unit of work, so production-grade data pipelines can be built without rewriting existing code.

• Dynamic workflow orchestration: Python-native workflow management with a dynamic DAG engine that adapts to change without stalling workflows
• Automated monitoring and recovery: automatic retries, caching, scheduling, and event-based automation keep data pipelines reliable
• Seamless code integration: add a decorator to turn existing Python functions into Prefect tasks, keeping your code clean
• Scalable infrastructure deployment: scale horizontally without code changes, with enterprise-grade security and governance
• Rich observability: built-in monitoring, error tracking, and workflow visualization

In data engineering scenarios, Prefect is widely used to build and manage ETL/ELT data pipelines; in machine learning teams, it helps orchestrate complex workflows spanning training, inference, and model deployment; for analytics teams, Prefect automates data processing tasks and safeguards data quality.

Compared with the traditional Apache Airflow, Prefect takes a more modern, Python-driven approach with greater dynamic event management capability and far less monolithic infrastructure, and is used by well-known companies like Cash App, Cisco, and 1Password.