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.
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.
We love connecting with our community in person, and the next few months are packed with opportunities to do just that. Our team will be attending (and in some cases, speaking at) several conferences and meetups. If you’re planning to be there, we’d love to meet you—here’s where you can find us.
As we’re half-way through the year, we’d like to take this opportunity to provide an update on the most recent changes in our Long-Term Support (LTS) releases.
Open source defies everything you’ve ever heard or learned about business before. This blog post is an introduction to how we’re creating a sustainable business model rooted in open source.
The OpenTelemetry Astronomy Shop demo has long served as a reference environment for exploring observability in distributed systems, but until now it shipped with only a Prometheus datasource. VictoriaMetrics forked the demo and extended it with VictoriaMetrics, VictoriaLogs, and VictoriaTraces, providing insights into VictoriaMetrics’ observability stack where metrics, logs, and traces flow into a unified backend.
Proper alerting is an art. It is all about foreseeing bad scenarios before they happen, so you can prepare for them. In this article, we go through practical recommendations of approaching the alerting to reduce alerting fatigue and avoid false positives.
Tech Talk: In this post, we explore vmanomaly through the eyes of its creators. Learn how this AI-powered alerting system helps cut through noise, avoid static rule spaghetti, and deliver actionable insights directly from your monitoring data.
VictoriaLogs uses three core concepts: message, time, and stream fields to structure log data. Too few streams create fat streams that are slow to query, while too many unique stream combinations create high cardinality problems…
Operating systems expose a wall clock that can leap or slew with NTP and a monotonic clock that never runs backward. In Go, only time.Now (might) carries both readings, while values from time.Parse, time.Date, etc., are wall-clock-only—so naïve equality checks or time.Since on those can mislead when the system clock shifts.
We’re excited to announce a new deployment region for VictoriaMetrics Cloud in ap-southeast-1 (Singapore), making it easier for users in Asia Pacific to run low-latency VictoriaMetrics Cloud stacks closer to home.