Creating pipelines
| Approach | Best for |
|---|---|
| Integration templates | Common use cases (Linux, MySQL, PostgreSQL) |
| Custom configuration | Specific requirements, custom scrapes |
Pipeline operations
| Action | What it does |
|---|---|
| Activate/Deactivate | Toggle collection on/off instantly |
| Edit | Update configuration content |
| View history | See what changed and when |
Why this matters
- Instant changes — No deployments, no restarts
- Safe experimentation — Toggle off if something goes wrong
- Audit trail — History shows what changed and when
Script
Now that you understand what pipelines are, let’s look at how you work with them in practice.
There are two ways to create pipelines. Integration templates are pre-built configurations for common use cases—Linux metrics, MySQL monitoring, PostgreSQL, and more. These are great for getting started quickly. Custom configuration is where you write your own config from scratch, useful for specific requirements or custom scrape targets.
Once a pipeline exists, you have several operations available. You can activate or deactivate pipelines with a single click. Need to temporarily stop collecting certain metrics? Just toggle it off. You can edit the configuration content anytime. And you can view the pipeline history to see what changed and when, which is invaluable for troubleshooting.
The key insight here is that pipelines are reusable. You create a pipeline once, define which collectors should receive it with attribute matching, and Fleet Management handles the distribution. One pipeline can serve hundreds of collectors.