From Spreadsheet Scheduling to Kubernetes - Building an On-Premise ML Platform

Learn how to transition from managing individual Ubuntu servers to building a comprehensive on-premise Kubernetes platform for machine learning workloads using entirely open-source technologies. Discover the journey from spreadsheet-based GPU allocation to implementing team-based managed scheduling systems that streamline resource management. Explore the creation of unified development environments that enhance collaboration and productivity across ML teams. Master the implementation of system observability solutions with long-term metrics storage capabilities that provide comprehensive monitoring and performance tracking. Understand how to build real-time insights and visualization dashboards that enable users to make informed decisions quickly and efficiently. Gain practical insights into the key lessons learned, challenges encountered, and solutions developed during this infrastructure transformation. Examine future enhancement plans focused on improving both system performance and user experience in ML platform operations.