Julius will give a quick update on the latest developments in Prometheus and then give a deep dive into the new experimental native histograms: Histograms are crucial for anyone who wants to track service latency and other numeric value distributions in Prometheus. However, the existing "legacy" histograms in Prometheus come with a number of painful drawbacks: they require manual and static bucket configuration, generate a separate time series for each configured histogram bucket, and thus require you to make hard tradeoffs between a histogram's resolution and cost. This is where the new "native" histogram metric type comes in. These native histograms allow you to track value distributions in higher detail at a significantly lower storage and processing cost, while also reducing the manual bucket configuration effort. Julius will explain how native histograms work, how they achieve these key benefits, and how you can use them in Prometheus today in an experimental fashion.
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