Deployed Aqua Security in a Kubernetes environment - lessons learned

Hi everyone, I recently wrapped up a production deployment of Aqua Security (specifically the Aqua CSPM/Trivy stack) across our multi-tenant EKS clusters. We were looking to enhance our vulnerability management and runtime security posture. The rollout was mostly smooth, but there were a few "gotchas" I wish I'd known beforehand.

**The Good:**
* The Helm charts are well-structured and make the initial deployment straightforward.
* The vulnerability scanning is fast and integrates nicely into our CI/CD pipeline. The ability to fail builds based on policy is a game-changer.
* The runtime console gives excellent visibility into container behavior and network policies.

**The Gotchas & Lessons Learned:**

1. **Resource Sizing is Critical:** The default resource requests/limits in the Helm charts were too low for our scale. We saw the `scanner` and `enforcer` pods getting OOMKilled. We had to adjust based on node capacity and workload density.
```yaml
# Example override in our values.yaml for the scanner
scanner:
resources:
requests:
memory: "512Mi"
cpu: "250m"
limits:
memory: "1Gi"
cpu: "500m"
```

2. **Database Configuration:** For a production setup, using the embedded Postgres instance isn't recommended. We had to plan and execute a migration to an external RDS PostgreSQL instance for better reliability and backup management. This wasn't documented as clearly as I'd hoped.

3. **Network Policies:** Aqua creates several services and pods that need to talk to each other. In a cluster with Calico CNI and strict network policies enabled, we had to craft specific policies to allow Aqua's internal traffic. This tripped us up for a day.

4. **Cost Awareness:** The per-node pricing model is clear, but remember that the `enforcer` DaemonSet runs on *every* node. If you have large nodes with many pods, the cost efficiency is good. But if you have many small nodes (like in a fargate-like setup), the cost can add up quickly. We optimized by consolidating workloads onto fewer, larger nodes.

Overall, I'm happy with the security insights we're getting. The key is to treat it like any other stateful, complex application: plan for storage, networking, and resources from the start. For those who've deployed it, how did you handle the database layer? Any other tips for scaling the enforcers?

-- Amy