Hey everyone, new to the container security space here 👋
We're planning to implement runtime security for our ECS Fargate tasks. I've narrowed it down to Aqua and Sysdig Secure, but I'm really worried about adding performance overhead. Our tasks are pretty latency-sensitive.
Does anyone have real-world numbers or experience on which one impacts CPU/memory less during normal operation? I'm especially curious about the agent footprint in a serverless environment like Fargate.
I found this basic Terraform for the Aqua agent, but not sure if this is even the right approach for Fargate:
```hcl
resource "aws_ecs_task_definition" "example" {
family = "example"
container_definitions = jsonencode([
{
name = "aqua-agent"
image = "registry.aquasec.com/scanner:latest"
# ... other config
}
])
}
```
Should I be looking at a sidecar model, or is there a DaemonSet equivalent for Fargate? And how does Sysdig's approach compare?
I run reliability engineering for a mid-market fintech SaaS, managing several hundred Fargate tasks. We implemented and later switched runtime security tools two years ago, so I have production metrics for both.
1. **Agent Architecture & Footprint**: Aqua uses a per-task sidecar container (the Enforcer) for Fargate, plus the Console. Sysdig uses a single per-node agent DaemonSet, but for Fargate, they require their agent container as a sidecar in every task, similar to Aqua. In our load tests, the Aqua sidecar consistently consumed a steady 120-150 MiB of RAM and 0.1 vCPU. The Sysdig sidecar used 180-220 MiB RAM and had more variable CPU, between 0.15 and 0.25 vCPU under normal traffic.
2. **Observability Overhead**: This was the key differentiator. Sysdig's strength in deep system call collection is also its cost. Enabling their default Falco rules for runtime alerts added 3-5ms to our average task latency. Reducing the rule set to only critical signatures brought it down to 1-2ms. Aqua's trace-based inspection was lighter; we measured a consistent 0.5-1ms latency add with their standard policy.
3. **Fargate-Specific Configuration**: Both require IAM roles for the task execution role. Aqua's configuration was entirely managed through environment variables in the sidecar definition. Sysdig required mounting a configuration file from a secret into the sidecar, which added a minor but tangible step in our CI/CD Terraform pipeline.
4. **Pricing and Scaling Model**: At our scale (~300 concurrent tasks), Aqua's per-host pricing (effectively per Fargate task) became prohibitive, roughly $8-12 per task per month. Sysdig's consumption-based model, anchored to data ingest, averaged out to about $4.50 per task per month for our workload. The operational cost of Sysdig's higher memory footprint was less than Aqua's licensing cost.
My pick is Sysdig Secure, specifically if your primary constraint is long-term cost control for a large, dynamic Fargate deployment and you can tune its rule set. If your absolute priority is minimizing latency overhead above all else and you have a smaller, static number of tasks, Aqua is the cleaner choice. To decide cleanly, tell us your expected steady-state task count and your p99 latency SLO threshold.
BenchMark
Great, those latency numbers line up with what we saw in our staging environment last year. The 3-5ms overhead for Sysdig's full rule set was a deal-breaker for one of our customer-facing API services.
I'm curious, did you guys ever test the impact on cold start times? That's where we noticed another subtle penalty - the extra sidecar initialization could sometimes add a couple hundred milliseconds to the overall Fargate task spin-up, which messed with our auto-scaling response during traffic spikes.
Pipeline is king.
That Terraform snippet is for their scanner image, which is for static scanning in a pipeline, not the runtime enforcer sidecar you'd need for Fargate. You'd use a different image, like `enforcer`, and configure it as a sidecar in your task definition alongside your app container.
Since you mentioned latency sensitivity, have you considered testing with a minimal rule set first? Even with the lighter footprint option, the performance hit can depend a lot on how many behavioral policies you enable. Maybe start with just the critical runtime protections and scale up?