VictoriaMetrics Anomaly Detection enables reliable alerting for highly variable, multi-domain traffic without relying on static thresholds. In this case study, fine-tuned models, backtesting, and clear visualization helped reduce alert noise, improve confidence in anomaly detection, and lower operational overhead.
Spotify needed to replace its legacy in-house time series database to overcome stability and performance limitations, which would bring about query delays and timeouts. The Spotify observability team chose VictoriaMetrics to support efficient metric ingestion, querying, and alerting at scale.
VictoriaMetrics delivers a complete open-source observability stack, combining a highly scalable time series database with a powerful log management system. This streamlined, single-binary solution simplifies deployment while providing fast, cost-effective monitoring and logging at any scale.