---
title: "The scaling challenge | Grafana Labs"
description: "Why manual configuration doesn't scale"
---

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

## The scaling challenge

Say you need to add a new metrics scrape to your collectors, maybe you’re rolling out a new integration or collecting extra data to troubleshoot an incident. With the manual approach, you access each machine, edit its configuration file, and reload the collector, then repeat for the next one. For 5 collectors that’s tedious. For 50 it’s most of a day. For 500 it’s impossible to do consistently.

Configuration management tools like Ansible or Terraform help, but they don’t remove the work. You’re still managing deployments, testing changes, and coordinating rollouts, so every configuration change becomes its own project.

[The scaling challenge: manual approach vs remote configuration](fleet-management-scaling-challenge.svg "The scaling challenge: manual approach vs remote configuration")

## How remote configuration changes this

Remote configuration flips the model. You create a configuration pipeline once in Fleet Management and assign it to collectors by their attributes, such as all production collectors or everything in `us-east`. The collectors pull the new configuration automatically on their next poll cycle.

## Updates per change

| Approach          | 5 collectors | 50 collectors | 500 collectors |
|-------------------|--------------|---------------|----------------|
| **Manual**        | 5 updates    | 50 updates    | 500 updates    |
| **Remote config** | 1 update     | 1 update      | 1 update       |

> **Configure once, deploy everywhere.** One update reaches your entire fleet.