promql-validator

You can validate PromQL queries by analyzing their syntax, verifying semantics like proper rate usage on counters, and detecting anti-patterns like high cardinality or regex overuse to ensure reliable dashboard and alerting results.

Common PromQL anti-patterns include high cardinality issues, regex overuse, and missing recording rules for expensive queries, which can cause noisy dashboards and fragile alerting if not detected and remediated.

Optimizing slow PromQL queries involves rewriting expressions, adding label filters to narrow scope, and implementing recording rules to pre-compute expensive calculations, generating an optimized query variant for better performance.

You can check Prometheus alert rules by validating the PromQL expressions within them to enforce best practices, detect semantic misuses such as histogram quantiles misapplied, and receive actionable remediation guidance across development and production environments.

PromQL queries return misleading results when semantic safeguards are violated, such as using rate functions on gauge metrics instead of counters, which can be detected by analyzing query semantics and applying proper metric type matching.