VictoriaMetrics

We've moved VictoriaMetrics to Adopt because it has matured into a reliable choice for organizations operating large-scale, self-managed observability platforms. As a high-performance, open-source time-series database, it handles high-volume and high-cardinality metrics workloads that can challenge Prometheus. In one of our projects, a VictoriaMetrics cluster handles five million samples per second with 20 to 30 labels per metric, demonstrating its suitability for large-scale deployments.

The platform offers a straightforward single-node version for smaller workloads as well as a clustered architecture that separates ingestion, querying and storage into independently scalable components. It integrates with existing observability architectures by supporting native OpenTelemetry ingestion, Prometheus APIs and remote write support, allowing teams to adopt it without replacing their existing instrumentation and dashboards. Whether used as long-term storage behind Prometheus or as a complete metrics stack with components such as vmagent and vmalert, VictoriaMetrics is a compelling option for infrastructure where retention, cardinality or cost has become a challenge.

现代可观察性依赖于收集和汇总一组详尽的细粒度指标，以充分理解、预测和分析系统行为。但面对由大量冗余，协作进程和主机组成的云原生系统时，由于基数（唯一时间序列数）会随着每个额外的服务、容器、节点、集群等呈指数增长，现代可观察性的应用显得相对笨重。对于这些高基数的数据，我们发现 VictoriaMetrics 表现出众。VictoriaMetrics 尤其适用于运行由 Kubernetes 托管的微服务架构，它的 operator 使团队可以轻松地以自助服务的方式实现自我监控。我们还喜欢它的组件化架构以及即使在中央服务器不可用时也能继续收集指标的能力。虽然我们的团队对 VictoriaMetrics 很满意，但云原生的可观察性是一个快速发展的领域，我们建议也同时关注其他高性能的、Prometheus 兼容的时间序列数据库，例如 Cortex 或 Thanos。