---
title: "Continuous profiling overview | Grafana Labs"
description: "Code-level CPU and memory performance analysis"
---

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

## What you get

| Feature               | Description                                    |
|-----------------------|------------------------------------------------|
| **Flame graphs**      | Visualize where code spends CPU/memory         |
| **Continuous**        | Always-on profiling, not just during incidents |
| **Pyroscope**         | Continuous profiling backend                   |
| **Trace correlation** | Link profiles to specific requests             |
| **Diff analysis**     | Compare profiles across deployments            |

## Questions answered

| With continuous profiling, you can answer…              |
|---------------------------------------------------------|
| What is the root cause of my performance issue?         |
| Which function is consuming the most CPU time?          |
| What code path is causing excessive memory allocations? |
| Did this deployment make the service slower or faster?  |
| Where exactly should we optimize to reduce cloud costs? |
| What changed between yesterday’s baseline and today?    |

## Problems solved

| Problem                                  | Solution                              |
|------------------------------------------|---------------------------------------|
| “Something is slow” but don’t know where | Flame graphs show exact code paths.   |
| High CPU/memory but unclear cause        | Continuous profiles reveal hot spots. |
| Profiling only during incidents          | Always-on catches regressions early.  |
| Can’t compare before/after deployments   | Diff profiles show what changed.      |

## The shift from Level 2

| Level 2 (Traces)            | Level 3 (Profiles)                             |
|-----------------------------|------------------------------------------------|
| “The database call is slow” | “This function processing the results is slow” |
| Service-level timing        | Code-level timing                              |
| Where in the architecture   | Where in the code                              |