Grafana Labs announced the general availability of Adaptive Profiles in Grafana Cloud, completing the Adaptive Telemetry suite to span all four telemetry signals: metrics, logs, traces, and profiles.
With Adaptive Profiles now GA, every layer of an organization's observability stack can automatically identify and retain high-value data while filtering out what doesn't matter, without manual tuning or engineering toil.
Grafana Labs built the Adaptive Telemetry suite to continuously analyze how telemetry is actually used and surfacing precise recommendations for what to keep, aggregate, or drop.
"The fundamental problem with observability economics today is that cost scales with ingestion, not insight," said Steven Dungan, Staff Product Manager at Grafana Labs. "Adaptive Telemetry inverts that model. Every signal: metrics, logs, traces, and profiles, now has an intelligent layer that learns how data is used in practice, and then optimizes automatically. With Adaptive Profiles reaching GA, we've closed the loop on the full stack. Teams get more signal, less noise, and lower bills and they don't have to sacrifice one for another."
Adaptive Profiles dynamically adjusts the detail and frequency of data collection based on workload behavior. During normal operations, it collects at a cost-effective baseline. When anomalies or performance issues arise, it automatically increases resolution to ensure engineers have the data they need to investigate.
For engineering teams that have struggled to justify fleet-wide profiling, Adaptive Profiles makes the economics work, delivering richer performance data where it matters, without requiring a fixed high-cost collection rate across every service.
Across the full Adaptive Telemetry suite, organizations using multiple components see 30–50% reductions in total telemetry costs on average.
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