<ul><li>A Summary metric in Prometheus is used to track individual observations and calculate quantiles over time.</li><li>It provides count, sum, and optional quantile values for the observations.</li><li>Summary metrics are useful for tracking response times, latency, GC time, and operation durations.</li><li>To define a Summary object, you can specify the name, help, and quantile values.</li><li>Quantile calculations involve sorting observations and determining percentile values.</li><li>An application example demonstrates creating a Summary metric for query execution duration.</li><li>The server setup includes endpoints for simulating queries and exposing metrics.</li><li>Viewing metrics reveals quantile values, count, sum, and average execution time.</li><li>Quantiles are approximations maintained through sampling algorithms by Prometheus client libraries.</li><li>Summary metrics help analyze the distribution of observations for better insights into system performance.</li></ul>

How to expose Summary metric using Prometheus Java Client?

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