Netflix Unveils Maestro: The Revolutionary Open-Source Workflow Orchestrator

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In today’s data-driven companies, the importance of workflow management is growing day by day. Particularly for large-scale tasks such as machine learning model training or data pipeline processing, the complexity and scale are significant. To meet this need, Netflix has open-sourced its internally developed workflow orchestrator, ‘Maestro’. This essential tool, utilized daily by thousands of data scientists, engineers, and content creators within Netflix, is now available to everyone as an innovative solution.

Powerful Features and Advantages of Maestro

Maestro is a fully managed Workflow-as-a-Service (WAAS) that supports a wide range of business logic, making it a versatile orchestrator. It manages the entire lifecycle of workflows, including retries, queue management, and task distribution, ensuring smooth operations of complex, large-scale tasks. Notably, Maestro supports both Directed Acyclic Graphs (DAGs) and cyclical workflows, distinguishing it from other workflow orchestrators.

Within Netflix, various workflows such as ETL pipelines, machine learning workflows, and A/B testing pipelines are operated through Maestro. This tool’s high scalability allows it to manage numerous workflows, handling an average of hundreds of thousands of tasks daily, with busy days seeing up to 2 million tasks completed.

In fact, Netflix has successfully migrated millions of existing workflows to Maestro. During this process, they provided uninterrupted service without a single downtime, achieving remarkable results, such as a 87.5% increase in tasks executed over the past year. This is a significant testament to Maestro’s stability and efficiency, suggesting that other companies could achieve similar success with this tool.

How to Use

Using Maestro is relatively straightforward. Basic prerequisites include Git, Java 21, Gradle, and Docker, with the following steps for installation and execution:

  • Build: Run the `./gradlew build` command to build the project.
  • Run: Execute Maestro with the `./gradlew bootRun` command.
  • Create a sample workflow: You can create and run a simple workflow example.
  • API Integration: Maestro supports managing various workflows through its API.

Conclusion

Maestro, Netflix’s innovative tool, is now available for anyone to leverage. From data scientists to business analysts, a wide range of users can benefit from efficient and reliable workflow management with this tool. Start using Maestro today and experience Netflix-level workflow management, maximizing your operational efficiency.

Reference: GitHub, “Maestro”

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