Evolution of Netflix Conductor

Conductor is a workflow orchestration engine developed and open-sourced by Netflix. If you’re new to Conductor, this earlier blogpost and the documentation should help you get started and acclimatized to Conductor. In the last two years since inception, Conductor has seen wide adoption and is instrumental in running numerous core workflows at Netflix. Many of the Netflix Content and Studio Engineering services rely on Conductor for efficient processing of their business flows. The Netflix Media Database (NMDB) is one such example. In this blog, we would like to present the latest updates to Conductor, address some of the frequently asked questions and thank the community for their contributions. Conductor is one of the most heavily used services within Content Engineering at Netflix. Of the multitude of modules that can be plugged into Conductor as shown in the image below, we use the Jersey server module, Cassandra for persisting execution data, Dynomite for persisting metadata, DynoQueues as the queuing recipe built on top of Dynomite, Elasticsearch as the secondary datastore and indexer, and Netflix Spectator + Atlas for Metrics. Our cluster size ranges from 12–18 instances of AWS EC2 m4.4xlarge instances, typically running at ~30% capacity. We do not maintain an internal fork of Conductor within Netflix. Instead, we use a wrapper that pulls in the latest version of Conductor and adds Netflix infrastructure components and libraries before deployment. This allows us to proactively push changes to the open source version while ensuring that the changes are fully functional and well-tested.

Source: medium

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