Grafana Labs Gives Every Observability Signal an Intelligent Optimization Layer, Completing Adaptive Telemetry Suite with Adaptive Profiles GA
With Grafana Labs' Adaptive Telemetry suite, customers including Mux, SailPoint, TeleTracking, and Auditboard have cut telemetry spend by 30–50% on average,redirecting savings into deeper observability coverage
Grafana Labs, the company behind the open observability cloud, today 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.
Telemetry volumes are growing faster than the insight they generate, and AI is accelerating the problem. As organizations deploy AI agents and LLM-powered applications, every model call, tool invocation, and agentic workflow generates new telemetry that needs to be observed, traced, and profiled. According to Grafana Labs' 2026 Observability Survey, 57% of organizations are already implementing LLM observability in some capacity, and 65% cite cost as the top criteria for selecting observability tools. AI gives teams more to watch, which means the cost of watching everything is rising sharply. Most organizations are already collecting far more data than they ever query, alert on, or act upon — AI-generated telemetry is making that gap wider, faster. Grafana Labs built the Adaptive Telemetry suite to address this directly: not by asking teams to manually cull their data, but by continuously analyzing how telemetry is actually used and surfacing precise recommendations for what to keep, aggregate, or drop.
