Worked on observability enhancements for the AI-Hypercomputer/JetStream repository, focusing on per-model performance analytics. Developed and integrated a Prometheus gauge metric to track jetstream_model_load_time, updating the server library to measure and report the duration of loading engine parameters. Introduced a sanitized 'model_name' label to metrics, enabling granular monitoring and differentiation across models. This approach improved diagnostic capabilities and facilitated more precise performance tuning for JetStream deployments. The work leveraged backend development skills with a strong emphasis on metrics, monitoring, and Prometheus, all implemented in Python, resulting in more actionable and detailed operational insights for the platform.