We're currently evaluating cloud security posture management (CSPM) tools for a large AWS environment (~2000 EC2 instances, plus associated VPCs, S3, RDS). Palo Alto's Prisma Cloud is a finalist. Most reviews are from smaller setups or focus on the container side. I'm looking for concrete experience from anyone running it at a similar scale, specifically on the Compute (VM) side.
Key questions for those with hands-on experience:
* **Performance & Impact:** What was the observed overhead of the Defender on your workloads? We're particularly concerned about latency-sensitive applications. Any hard numbers on CPU/RAM consumption under load would be invaluable.
* **Alert Fatigue & Tuning:** How manageable was the initial alert volume? We've trialed tools that generated thousands of "critical" findings for minor deviations. What was your process for creating actionable policies? For example, how did you handle rules like `AWS Security Groups allow internet traffic to SSH port (TCP:22)` without drowning in noise?
* **API & Automation:** We intend to manage everything via Terraform and their API. How stable and consistent is the Prisma Cloud API for bulk operations (e.g., onboarding all accounts, setting policy exceptions at scale)? Any pitfalls in the IaC workflow?
Here's a snippet of the kind of policy logic we need to codify, to see if Prisma's model aligns:
```python
# Pseudocode for a custom policy we'd need
if resource.type == "aws_security_group":
if is_internal_vpc(resource.vpc_id) and resource.has_ingress(port=22, cidr="0.0.0.0/0"):
severity = "high" # Internal SG with open SSH to internet
elif is_dmz_vpc(resource.vpc_id) and resource.has_ingress(port=443, cidr="0.0.0.0/0"):
severity = "low" # Expected for public web tier
```
* **Cost vs. Value:** Does the granular visibility and runtime protection justify the premium over more basic CSPM scanners for a purely VM-based estate? Were there unexpected cost drivers?
Our shortlist also includes Wiz and Lacework. Benchmarks on policy evaluation speed and console responsiveness at this scale would directly influence our decision.
garbage in, garbage out
We migrated about half that scale last year, so my experience is a bit smaller, but hopefully still useful.
On the Defender overhead, we saw a pretty consistent baseline of 1-2% CPU and around 150-200MB RAM per instance. The real hit came with the initial full disk scan - that spiked CPU on some of our heavier I/O app servers. We scheduled those scans during off-peak windows to be safe. For latency-sensitive apps, we ended up using the agentless option for those specific instances, which worked but obviously loses some runtime visibility.
The alert fatigue was real, especially with those broad security group rules. We built our deployment around their API and Terraform, and the key was using their policy-as-code framework from day one. We didn't just silence rules; we cloned them and made them specific to our environment. For example, we modified that SSH rule to only flag SG's attached to instances with a specific "bastion" tag, and ignored our development VPCs entirely. It took a few weeks of iterating, but the API was stable enough for that bulk policy work.
What's your timeline for the rollout? Are you planning a phased approach or a big-bang deployment across all 2000 hosts?
Migration is never smooth.
Phased rollouts are a smart way to deal with the initial scan spikes. But have you run the numbers on the cost for 1000+ agents? That licensing adds up fast.
Why not just use AWS's own tools? Security Hub with Config Rules and GuardDuty covers a huge chunk of CSPM use cases and is already paid for. You miss some runtime stuff, but for 90% of posture needs it's fine.
The overhead you reported, while small per instance, is a non-trivial total compute tax at scale.
linux is free
Ran it at about 1600 hosts. The defender overhead is negligible, close to what user43 said. The real bottleneck was the console and API during bulk operations. Onboarding 2000 hosts via their API for inventory sync and policy assignment was painfully slow and prone to timeouts.
You can't just manage everything via Terraform. Some critical settings, like alert routing to our SIEM, are API-only with poor documentation. We had to open a support ticket to get the right endpoints.
Alert tuning for something like the SSH rule is straightforward. You build a compliance standard from a clone of the built-in one, then modify the rule logic to exclude your jump/bastion hosts by tag. But that process isn't intuitive through the API. You'll end up using the UI for policy building and the API for assignment.
Your API and Terraform focus is the right approach, but you'll hit a wall. The API coverage is inconsistent. We had the exact same plan and ended up with a hybrid mess: Terraform for resource policies and some alerts, but the UI for any complex compliance standard modifications and all alert routing logic. Their documentation lists endpoints that don't work as advertised for bulk assignments at your scale.
On alert fatigue for something like the SSH rule: don't just disable it globally. Use their policy-as-code to build a custom rule that excludes instances tagged with `Function: Bastion`. The logic is there, but constructing the JSON payload for the API to create that custom rule was undocumented; we reverse-engineered it from a UI-created rule.
For performance, our numbers aligned with user43. The silent killer is the console latency when you're trying to investigate an incident across hundreds of affected resources. It bogs down. If you're relying on the UI for anything operational at 2000 hosts, it'll frustrate you. Automate everything you need for daily workflows, and treat the console as read-only.
Garbage in, garbage out.
Your point about the hybrid Terraform/UI/API management model is exactly what our audit team flagged in a recent vendor assessment. We observed the inconsistency you describe; certain critical compliance objects, like modified policy rules or alert destinations, are not represented as resources in their official Terraform provider. This creates a drift risk where the documented "source of truth" in Terraform doesn't match the actual runtime state, a significant concern for SOC 2 controls.
The API documentation gap for bulk operations is a recurring pattern. In our experience, you often have to script around the pagination and timeout limits they don't adequately document. We ended up implementing an exponential backoff and batch size of 50 resources per call, which was only discovered through support escalation. This operational overhead isn't trivial for an estate of your size.
This also impacts your ability to prove compliance. If you can't reliably reproduce the entire security posture configuration through code, you're left with manual screenshots for audit evidence, which is far from ideal.
trust but verify