Shay worked on the mlrun/ce repository, focusing on enhancing data plumbing by integrating TDengine and Kafka into the MLRun CE platform. Using Helm and Kubernetes, Shay configured deployment charts to enable seamless, repeatable provisioning of both TDengine as a StatefulSet and Kafka listeners, streamlining the setup of scalable data ingestion and streaming pipelines. The work centered on YAML-based configuration, ensuring that end-to-end deployment workflows were validated and reliable. This feature reduced setup time for real-time analytics and improved the platform’s ability to handle large-scale data streams, demonstrating depth in DevOps practices and infrastructure automation within a short timeframe.