# [[Grafana Adaptive Telemetry]]
![[Adaptive Telemetry.svg]]
[[Grafana Labs]] has pioneered the use of [[Adaptive Telemetry]] within its [[Grafana Cloud|commercial SaaS offering]]. Adaptive Telemetry drops [[Telemetry|telemetry data]] from [[Logs]], [[Traces]], [[Metrics]], and [[Continuous Profiling|profiles]] so that people only pay for what's actually being used.
Here's CTO [[Tom Wilkie]] talking about this feature:
It's currently available for [[Adaptive Logs|Logs]] and [[Adaptive Metrics|Metrics]], but will soon be available for [[Adaptive Traces|Traces]] and [[Adaptive Profiles|Profiles]] as well.
## Benefits
### Cost savings
There are significant cost savings associated with just deleting unnecessary information. A Grafana Cloud user, TeleTracking, stated that they reduced their spending by 46% just by implementing Adaptive Metrics. [^teletracking]
## How does adaptive telemetry work?
Adaptive telemetry deletes data based on:
- What data has actually been historically queried
- What data has alerts on it
- What data is displayed on a dashboard
## Avoiding deletion of important data
The main concern of implementing adaptive telemetry is the possibility of relevant or necessary data being deleted. Often, data that is not queried still becomes important for troubleshooting when an outage occurs later. How can we prevent this data from being deleted?
- Adaptive Telemetry allows you to set *exemptions*: services, telemetry types, and labels that are never deleted.
- Users can set a *maximum drop percentage*, a number that determines a limit for how much of a telemetry signal can be dropped (deleted)
[^teletracking]: Wilkie, T. (2025). *Optimize observability and cut costs without losing insights | What is adaptive telemetry? | Grafana* Retrieved from: https://www.youtube.com/watch?v=Dz5XLSPTpWA
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