Shay focused on enhancing data infrastructure within the mlrun/ce repository by integrating TDengine and Kafka using Helm and Kubernetes. He developed Helm charts to automate the deployment of TDengine as a StatefulSet alongside Kafka listeners, streamlining the setup of scalable data ingestion and streaming pipelines. Working primarily with YAML and DevOps practices, Shay validated the end-to-end deployment workflow to ensure reliability and repeatability. This work enabled MLRun CE to support robust, real-time analytics by simplifying the deployment of a complete data stack. The depth of the integration addressed both scalability and operational efficiency for data-driven applications within the project.