Grafana Cloud Adaptive Metrics has helped users save up to 70% on observability costs by automatically aggregating unused and partially used metrics.
This video features a demo on Adaptive Metrics, where you’ll learn what we mean by “adaptive” — automating the process of recommending which metrics to drop while giving you the flexibility to determine any exemptions. This boils down to maintaining effective observability while reducing costs.

Learn how to:

• Identify and eliminate unnecessary high-cardinality labels
• Use Adaptive Metrics to automatically aggregate time series data based on usage patterns
• Continuously adapt your observability stack to minimize data overload and reduce costs
• Set exemptions to ensure essential data is always preserved
• Stay in control of your observability with automated recommendations and updates

Chapters

0:00 Hellos

0:09 What is Adaptive Metrics?

1:05 What “Adaptive” Means

2:00 Adaptive Metrics Demo

3:15 Setting Up Exemptions for Data You *Might* Need

3:48 Why You Don’t Need to Worry About Data Loss - You’re in Control

With Adaptive Metrics, you and your team can start managing metric volumes more efficiently, confidently make data-driven decisions, and ultimately, save on cloud costs. Over 1,500 organizations are already using Adaptive Metrics, with some reducing their costs by up to 70%.

Helpful links:

📄 Learn more about how organizations have benefitted from Adaptive Metrics: https://grafana.com/blog/2024/08/12/why-companies-choose-adaptive-metrics-and-how-they-save-time-and-a-lot-of-money/

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