Anomaly Detection — News, Updates & Deep Dives

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Observability's Sixth Sense: Grounding Anomaly Detection in Reality

Learn how VictoriaMetrics combines machine learning, MCP, and natural-language workflows to simplify observability with anomaly detection and reduce operational overhead.

What's new in VictoriaMetrics Anomaly Detection (Q2 2026)

The Q2 2026 vmanomaly update introduces Temporal Envelope, a redesigned UI, faster online-model execution, and an AI-assisted workflow that turns natural-language monitoring goals into tested configurations and alerting rules.

What's new in VictoriaMetrics Anomaly Detection (Q1 2026)

Q1 2026 brought incremental but important updates to VictoriaMetrics Anomaly Detection: UI improvements, AI assistance inside the UI, a public traces playground, new false-positive reduction controls, and continued resource optimizations.

What’s new in VictoriaMetrics Anomaly Detection (2025)

VictoriaMetrics Anomaly Detection has had a productive year with lots of user feedback that has had a major impact on product development. We’ve added improvements across the board: in core functionality, simplicity, performance, visualisation and AI integration. In addition to bug fixes and speedups, below is a list of what was accomplished in 2025.

How a US Software Provider Improved Traffic Alerting with VictoriaMetrics Anomaly Detection

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.

VictoriaMetrics Anomaly Detection: What's New in Q3 2024?

Explore the latest improvements in VictoriaMetrics Anomaly Detection (vmanomaly), including optimizations, online models, multitenantcy and mTLS support.

VictoriaMetrics Anomaly Detection: What's New in H1 2024?

Explore the latest improvements in VictoriaMetrics Anomaly Detection (vmanomaly), including presets, new models, enhanced tuning, and better resource management

VictoriaMetrics Machine Learning takes monitoring to the next level

Announcing VictoriaMetrics Anomaly Detection solution, which harnesses machine learning to make database alerts more relevant, accurate and actionable for enterprise customers.

Anomaly Detection for Time Series Data: Techniques and Models

This blog post series centers on Anomaly Detection (AD) and Root Cause Analysis (RCA) within time-series data. In Chapter 3, we delve into a variety of advanced anomaly detection techniques, encompassing supervised, semi-supervised, and unsupervised approaches, each tailored to different data scenarios and challenges in time-series analysis.

Anomaly Detection for Time Series Data: Anomaly Types

This blog post series centers on Anomaly Detection (AD) and Root Cause Analysis (RCA) within time-series data. In this second part, we explore the distinct anomaly types inherent to time-series and offer insights on how to tackle them effectively.