ReadMeFeed / Community knowledge
Real questions. Useful conversations. Find the people who know your stack.
Stop battling slow Grafana dashboards. Learn how to use Prometheus recording rules to precompute expensive PromQL expressions and drastically reduce query latency.
Recording rules precompute expensive PromQL expressions on a fixed interval and store results as new metrics. Configuration example, naming conventions, and the pitfalls that cause silent failures.
Stop fighting Prometheus query timeouts. Learn how to use Recording Rules to pre-compute expensive PromQL expressions and drastically speed up your Grafana dashboards.
Query Memory Overhead Calculation Prometheus query caching (queries.cache.enabled) is documented as a mechanism to reduce memory pressure during repeated query execution, yet the exact memory overhead calculation for PromQL query evaluation remains undocumented. This creates challenges for capacity planning when deploying complex queries that process high-ca
Query Timeout Behavior in Prometheus Prometheus utilizes a global --query.timeout flag to prevent resource exhaustion from long-running queries. While the HTTP API allows for per-request timeout overrides, the server must manage the lifecycle of the underlying PromQL engine process when these limits are reached or when a client abruptly closes the connection
prometheus