{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/b63f0eba0fd74750929f37c16b3fca3b\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/b63f0eba0fd74750929f37c16b3fca3b-a257f59db2189043.gif","duration":119.4135,"title":"HolmesGPT - &quot;What Happened Here?&quot;","description":"In 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!"}