video1.0<iframe src="https://www.loom.com/embed/b63f0eba0fd74750929f37c16b3fca3b" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/b63f0eba0fd74750929f37c16b3fca3b-a257f59db2189043.gif119.4135In this video, I showcase the incredible capabilities of Holmes GPT when analyzing CPU usage spikes in my cluster, specifically focusing on Prometheus. I demonstrate how Holmes can visually interpret graphs and gather relevant data, such as application logs and Kubernetes events, to provide a comprehensive understanding of what happened at the time of the spike. I discovered that the CPU spike was due to Prometheus performing database compaction, which is a periodic process that causes significant resource usage. I encourage you to explore how Holmes can enhance your monitoring and troubleshooting efforts. Please let me know if you have any questions or need further insights!