---
title: "Distributed tracing and continuous profiling at scale | Grafana Labs"
description: "Grafana Cloud Traces and Grafana Cloud Profiles make storing and querying high trace volumes and fleet-wide profile data available and affordable."
---

> For a curated documentation index, see [llms.txt](/llms.txt). For the complete documentation index, see [llms-full.txt](/llms-full.txt).

## Grafana Cloud Traces

Often, a high-traffic system produces far more traces than you can affordably store and query on your own.

Grafana Cloud Traces runs that backend and storage for you, so you can afford to keep enough trace history to investigate.

- **No backend to operate**: Storage, scaling, sharding, and capacity planning are handled for you.
- **Adaptive Traces**: Healthy requests produce far more traces than you need, but tail sampling keeps what matters and drops the rest. Open source can tail-sample too, but you run the pipeline yourself and redeploy it to change policies. Adaptive Traces is the managed version, where policy changes take effect within about 10 seconds, no redeploy.

## Grafana Cloud Profiles

Profiling works the same in open source and Grafana Cloud, but the difference is operating it.

- Always-on profiling generates continuous data from every instance in your fleet.
- Storing and querying that volume affordably is hard to run yourself.

Grafana Cloud Profiles stores and queries that volume for you, so you keep profiling on everywhere.

## Real results from real teams

- [**Uber**](/events/observabilitycon-on-the-road/2025/san-francisco-bay-area/uber-journey-with-grafana-cloud-profiles-cut-costs-reduce-latency-streamline-incident-response/)
  
  > Moved from manual, reactive profiling to always-on continuous profiling with Grafana Cloud Profiles.
- [**IG Group**](/events/observabilitycon/2024/centralized-observability-with-grafana-cloud-at-ig-group/)
  
  > Chose Grafana Cloud specifically for Tempo as their traces store at scale, alongside Mimir for metrics. Built an “observable by default” platform using OpenTelemetry across cloud and on-prem.