Grafana insights
Open SourceVersions: [current]242 metricsLow dashboard refresh intervals (e.g., every 30 seconds or less) create unnecessary query load on data sources, degrading performance and potentially causing timeouts or errors, especially when querying long time ranges or high-cardinality data.
Nodes become critical when their failure would cause replica unavailability. Detecting critical nodes before termination prevents data loss and service disruption. This is indicated by the /_status/critical_nodes endpoint showing non-empty criticalNodes array.
High Anthropic API latency (>500ms) signals backend strain or network issues. Early detection prevents cascading failures in AI-powered applications.
Grafana instances using Cassandra as a backend can experience silent performance degradation when JMX metrics (compaction tasks, heap usage, GC pauses) are not collected. Without JMX visibility, operators miss early warnings of heap exhaustion, compaction backlog, or GC thrashing that manifest as sudden dashboard failures.
Growing replication lag in CockroachDB PCR indicates the standby cluster cannot keep pace with primary writes. Unchecked lag degrades failover readiness and increases potential data loss window.
In CockroachDB physical cluster replication (PCR) setups monitored via Grafana, replication lag (replicated_time vs. actual time) can grow unnoticed if only DB Console is used. During failover, this lag translates to data loss or extended RTO, as the standby cluster is further behind than expected.