Maestro is a general-purpose workflow orchestrator developed by Netflix to provide a fully managed workflow-as-a-service (WAAS) for its data platform users. It serves a diverse range of users, including data scientists, engineers, machine learning experts, and business analysts, supporting various use cases with high efficiency and reliability.
Key Features
- Scalability: Handles hundreds of thousands of workflows and millions of jobs daily, even during traffic spikes.
- Extensibility: Designed to support both existing and new use cases, ensuring flexibility for future needs.
- Managed Service: Offers a fully managed WAAS, reducing the operational burden on end users.
- Strict SLOs: Operates under strict Service Level Objectives, ensuring high availability and performance.
Technology Stack
- Built with Java 21 and Gradle for robust performance and easy builds.
- Supports Docker for containerized deployments.
- Integrates with Kubernetes for orchestration in cloud environments.
Getting Started
Maestro can be run locally or in a cloud setup. The project provides comprehensive instructions for building, running, and testing workflows via REST APIs. Sample workflows are included to help users get started quickly.
Use Cases
Maestro is versatile, catering to:
- Data pipeline orchestration.
- Machine learning workflow management.
- Business process automation.
For more details, refer to Netflix's blog post about Maestro.