Having recently implemented Prisma Cloud across several mature AWS organizations, I've observed a significant signal-to-noise issue with the default compliance and alerting policies. The out-of-the-box rulesets appear calibrated for greenfield deployments or organizations with minimal existing guardrails, generating a flood of findings that often lack operational criticality.
For example, default policies flagging every S3 bucket without versioning or every security group with a wide rule, while technically correct, create alert fatigue for teams who have consciously accepted those risks as part of a broader architectural pattern. This drowns out the alerts for genuine, high-severity misconfigurations like publicly exposed EC2 instances with sensitive IAM roles.
My immediate approach has been to aggressively customize the policy framework:
- **Disable** broad "best practice" rules that don't align with our internal security baselines.
- **Tune** thresholds for resource-based policies (e.g., only alert on security groups with *all* ports open to 0.0.0.0/0).
- **Leverage** policy suppression tags to exclude validated, non-conforming legacy resources.
However, this customization layer itself becomes a substantial maintenance burden, requiring constant updates as new default policies are introduced with each platform update. It feels like we're fighting the tool rather than having it work for us.
I'm curious if other organizations with established cloud governance have faced similar challenges. What has been your strategy for taming the noise? Have you found success with a "disable all defaults and build from scratch" approach, or is iterative tuning the only viable path?
--crusader
Commit early, deploy often, but always rollback-ready.