Agent skill · data analytics · grafana
adaptive-metrics
Cut Grafana Cloud Metrics cost by shrinking active-series count with Adaptive Metrics aggregation rules — auto-recommendations from query history, custom exact/regex rules, label-drop config, unused-metric detection, and Alloy remote_write fallback. Use when investigating a high Mimir/Grafana Cloud bill, hunting high-cardinality labels (`pod_uid`, `service_instance_id`, `version`), pre-aggregating counters/gauges, dropping unused metrics, or measuring `grafanacloud_instance_active_series` before/after — even when the user says "reduce cardinality", "too many series", "metrics spend", "active series count is exploding", or "drop the version label" without naming Adaptive Metrics.
Why this skill is useful
Provides specific API commands and workflows for managing Grafana Cloud Metrics costs that the AI wouldn't reliably generate on its own.
What it needs
Requires grafana account access. About 2k tokens when loaded. Last updated 2026-08-05. 212 stars on the source repository.
What this skill does
Grafana Cloud Adaptive Metrics Docs: https://grafana.com/docs/grafana-cloud/cost-management-and-billing/reduce-costs/metrics-costs/adaptive-metrics.md Aggregation rules that pre-shrink high-cardinality metrics before storage — directly reduces active-series billing. Prerequisites Grafana Cloud Metrics plan (any paid tier) API key with metrics:write (for the Adaptive Metrics API — adaptive-metrics.grafana.net, Bearer auth) For the verification queries: the metrics query endpoint (prometheus-prod-XX.grafana.net) uses HTTP basic auth — <metricsuser> (numeric stack/instance ID) plus a token with metrics:read — not the Bearer key Access to Home → Adaptive Metrics in the Cloud portal Common Workflows 1. Review + apply auto-recommendations Rollback — delete the rule: 2. Hand-write a custom rule Full payloads (regex match, aggregation types, all caveats): references/api.md. 3. Drop unused metrics entirely Measure the impact Rules take effect within ~5 minutes; full billing impact appears within an hour. The original high-cardinality samples keep flowing but the dropped labels no longer count toward billing. Resources Adaptive Metrics docs Adaptive Logs docs Cardinality in Prometheus
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills grafana/adaptive-metrics