In an unexpected move, Netflix has announced the end of its support for Conductor, the popular orchestration engine for microservices that the streaming giant had open-sourced in 2016. With over 13,000 GitHub stars and used by countless companies as a vital component of their infrastructure, Conductor has been one of the company’s most beloved open source projects. However, Netflix has made the decision to shift its focus elsewhere.
“This strategic decision, while difficult, is necessary in order to realign our resources and better serve our business objectives through our internal Conductor fork,” the company expressed in a statement.
“We are immensely grateful for the support and contributions from our community over the years. Though Netflix will no longer be maintaining this repository, members of the Conductor community have been actively promoting alternative forks of the project, so we have confidence that the community will continue to thrive in the future.”
Among the companies taking up this project is Orkes, a startup founded by the engineers who originally created Conductor while working at Netflix. The Orkes team plans on taking over the project through a new fork and will maintain close ties with the rest of the Conductor community.
“We are thrilled to collaborate with the broader community to ensure the continued success of Conductor, and this new phase of Conductor OSS truly embodies the collective vision of this thriving community,” announced Orkes.
The company is clearly putting a positive spin on this news, stating that “the roadmap for Conductor will now be influenced by those who use and cherish it – the open source community.”
Recently, Orkes unveiled its AI Orchestration platform. This platform simplifies the process for developers to incorporate language models and machine learning inferencing into their workflows, thanks to Orkes’ existing integrations with services such as Azure Open AI, OpenAI, and Google’s Vertex AI. Alongside the AI Orchestration, Orkes introduced Human Task, designed to bring a human element to AI workflows by making it easier to combine AI-based decision-making with human oversight during key points in a business process.