This episode looks into the observability tool Parca & Polar Signals Cloud with Frederic Branczyk and Thor Hansen. We discuss experiences and discoveries using Parca for detailed system-wide performance analysis, which transcends programming languages.
We highlight a significant discovery related to kube-prometheus and the unnecessary CPU usage caused by Prometheus exporter's attempts to access BTRFS stats, leading to a beneficial configuration change for Kubernetes users globally.
We also explore Parca Agent's installation on Kubernetes 1.28 running on Talos 1.5, the process of capturing memory profiles with Parca, and the efficiency of the Parca Agent in terms of memory and CPU usage.
We touch upon the continuous operation of the Parca Agent, the importance of profiling for debugging and optimization, and the potential of profile-guided optimizations in Go 1.22 for enhancing software efficiency.
🎬 Screensharing videos that go with this episode:
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