This article explains the fundamentals of metrics, introduces dimensional metrics, compares Prometheus, OpenMetrics, and OpenTelemetry standards, and provides detailed guidance on the four Prometheus metric types—Counters, Gauges, Histograms, and Summaries—including their use‑cases, PromQL queries, and Python client examples.
This article explains the fundamentals of metrics, the evolution of dimensional data, and provides a deep dive into Prometheus' four metric types—Counters, Gauges, Histograms, and Summaries—complete with practical code examples, query patterns, and a comparison of their strengths and trade‑offs.
This guide explains the role of optimizer statistics in Oracle, when to gather them, how to use automatic and manual collection jobs, tune ESTIMATE_PERCENT and METHOD_OPT, manage histograms, handle bind peeking, apply dynamic sampling, and safely test changes with pending statistics.
This guide explains how to verify and configure Oracle's automatic optimizer statistics collection, customize collection windows, tailor statistics for large and partitioned tables, detect stale statistics, and decide when to gather histograms, providing practical SQL and PL/SQL examples.
