In high-scale environments, metrics cardinality isn’t just a resource concern, it’s an architectural challenge. Left unchecked, it can impact performance, query latency, and even system stability. This talk takes a deep technical dive into how VictoriaMetrics enables advanced observability practices with a strong focus on cardinality management. I’ll explore how to design efficient and scalable scrape configurations using Prometheus-compatible jobs and exporters, optimize your label strategies, and use built-in cardinality analysis tools within VictoriaMetrics to identify and mitigate high-cardinality patterns early. The session also covers integration with Grafana open source for visualizing metrics in a way that supports signal clarity and operational response, as well as setting up practical alerting strategies that minimize noise while ensuring fast issue detection. By the end of the talk, the audience will understand the engineering trade-offs of high-cardinality metrics and how to detect them, how VictoriaMetrics handles storage and querying at scale, how to build resilient and low-overhead scrape configs with Prometheus compatibility and how to use Grafana open source to highlight cardinality hot spots and improve alert signal quality.

Diana is a DX Engineer at VictoriaMetrics. She is passionate about Observability, machine learning. She is an active contributor to the OpenTelemetry CNCF open source project and supports women in tech.