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.
By Engineers For Engineers
For Simple, Reliable, Efficient Monitoring
Key metrics
Whether open source or enterprise: Our monitoring and observability solutions deliver incredible performance, ease of use, scalability and (cost-)efficiency.
Learn how VictoriaMetrics combines machine learning, MCP, and natural-language workflows to simplify observability with anomaly detection and reduce operational overhead.
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.
VictoriaMetrics July updates bring a new LTS release, vmestimator, and a set of improvements across the stack that make operations simpler and observability more practical.
An interactive tour of what’s new in Go 1.27: every notable language, runtime, and standard library change, with short runnable examples you can edit and run in the browser.
Together, we’re building a friendly and happy open-source community, where every question gets answered – fast.