The value of Adaptive Metrics

As your observability footprint grows, metric data can multiply fast — often faster than you need it to.

Adaptive Metrics is enabled by default, continuously analyzing your metric usage in the background to find optimization opportunities.

This helps you:

  • Lower ingestion and storage costs
  • Speed up dashboards and queries
  • Maintain observability quality as your environment grows
  • Automate ongoing optimization to prevent metric sprawl

You can arrive at Adaptive Metrics from different Grafana workflows depending on the problem you’re trying to solve.

No matter where you begin, this journey shows how to analyze and optimize metrics, so you keep only the data that delivers value.

Common entry points

ProblemEntry PointWhy Use Adaptive Metrics
You see a spike in metric ingestion or cost, or receive a Billing & Usage alertCost Management & BillingIdentify which metrics drive the increase and reduce redundant series to lower cost
Dashboards take too long to load, or Explore queries time outDashboards or ExploreFind and optimize high-cardinality metrics causing performance issues
Alerts or SLO tracking seem noisy or unstableAlerting or SLOsRemove duplicate or overly granular metrics that distort alert conditions
You want to maintain consistent performance and cost controlRoutine observability hygieneReview recommendations and automate metric optimization on a schedule

In the next milestone, you learn how Adaptive Metrics works.

More to explore (optional)

At this point in your journey, you can explore the following paths:

Adaptive Telemetry