https://null-hypothesis.ines-garcia263.workers.dev/tags/anomaly-detection/ Recent content in Anomaly Detection on Inês Garcia Hugo -- gohugo.io en © 2026 Inês Garcia Thu, 11 Sep 2025 00:00:00 +0000 https://null-hypothesis.ines-garcia263.workers.dev/posts/automatic-dip-detection-statistical-approach/ Thu, 11 Sep 2025 00:00:00 +0000 https://null-hypothesis.ines-garcia263.workers.dev/posts/automatic-dip-detection-statistical-approach/ <p>Monitoring availability metrics at scale creates a familiar problem: you have a time series, you need to know when it drops, and you need to know this automatically — without someone staring at a dashboard.</p> <p>This post walks through a statistical algorithm I built to do exactly that. It detects dips in any continuous metric (availability, reachability, error rate) and returns precise start and end timestamps for each event. No ML required — just a modified z-score, two rolling windows, and a few transition rules.</p>