From 30s to 200ms: Optimizing Multidimensional Time Series Analysis at Scale

Monitoring production systems in real-time is crucial for reliability. Multidimensional anomaly detection is a very helpful tool in this regard. However, it does require time-series analysis to be blazing fast. This follow-up blog shows how to speed them up by using different strategies like indexing, filtering, bucketing, etc., to achieve a consistent performance in the 100s of ms range. Recap Most teams learn the hard way that global all-green dashboards can hide real incidents in a single cohort. In Part 1: A Guide to Multidimensional Anomaly Detection , we covered the why and the solution blueprint.