Worked on the dentiny/ray repository to deliver a Job Log Streaming Observability Enhancement, focusing on improving diagnostics for job log streaming issues. Implemented in Python, the solution surfaced WebSocket close codes and errors within the streaming path, spanning both the submit-pod and dashboard components. By adjusting logging and monitoring practices, the changes preserved existing runtime behavior while adding targeted visibility for CLOSED and ERROR conditions. This approach enabled more effective root-cause analysis of sporadic log streaming interruptions, enhancing reliability for Ray jobs. The work demonstrated backend development skills and contributed to better telemetry and developer productivity through improved observability.