Switched from Aqua to Sysdig and our false positives dropped by half.

Hey everyone! 👋 Wanted to share a quick win from our recent switch in the container security world.

We were running Aqua for runtime security on our Kubernetes clusters for about a year. While it was great at catching *potential* threats, the team was getting seriously fatigued by alert noise. We were constantly tuning policies, but things like benign process executions in our CI/CD pods or certain package manager behaviors kept triggering "suspicious activity" alerts. Our DevOps on-call rotation was not happy.

Last quarter, we decided to pilot Sysdig Secure, focusing on its runtime insights. The difference was pretty striking. After a month of running them side-by-side and then cutting over, our **false positive rate dropped by about 50%**.

Here’s what I think made the difference for us:

* **The Falco ruleset out-of-the-box felt more context-aware.** Sysdig leverages that open-source core, but their managed rules seemed to have better understanding of container behavior.
* **The profiling feature was a game-changer.** We let it learn our normal service behaviors for a week, and it automatically built baselines. This meant alerts fired when something *actually* deviated from *our* normal, not just a generic rule.
* **Integration with the image scanning and registry results** meant runtime could ignore things that were already approved in the pipeline. Aqua had this too, but the linkage felt smoother in Sysdig.

A quick example of a rule we had to write in Aqua to avoid noise, that Sysdig handled better natively:

We had a logging sidecar that needed to run `tar` to package logs. Aqua saw `tar` in a container and flagged it. In Sysdig, we could easily scope the rule to ignore that specific service account.

```yaml
# Sysdig rule example - condition snippet
condition: >
spawned_process and proc.name="tar"
and not k8s.service.name="log-sidecar"
```

The UI for building these exceptions is actually pretty intuitive, too.

Has anyone else made a similar move? I'm curious if others found the profiling and baseline learning as useful as we did, especially for cutting down the alert storm. Our SecOps team is now actually *looking* at the runtime alerts instead of muting them, which is a huge win.