Okay, so we just finished rolling out Orca Security across our entire AWS estate. We're a mid-sized SaaS company, and this was our first "big bang" cloud security platform implementation. I was the primary point of contact for the trial and deployment.
The good news is, the agentless part is legit. We didn't have to touch a single EC2 instance or container across those 300 accounts, which was a huge relief. The initial side-by-side read-only permissions setup was smooth, and the dashboard populated way faster than I expected. Finding misconfigured S3 buckets and public RDS instances was almost too easy – we had a "oh no" moment in the first hour.
But here's what broke or caused headaches:
1. **Cost Explorer integration.** We linked it, but the resource attribution is... confusing. Orca flagged a massive spend on an unencrypted volume, but our finance team says the cost is actually for a different, encrypted service in the same region. Now there's a debate about how accurate the cost data is, which undermines the "prioritize by risk AND cost" promise a bit.
2. **Alert fatigue, immediately.** We got thousands of "critical" alerts on day one, mostly for outdated AMIs and missing vulnerability patches on internal dev instances that have no external exposure. The risk score helps, but we're still tuning the policies to match our actual threat model. Has anyone else struggled with this?
3. **Our custom Terraform modules.** Some of our internal modules auto-tag resources, and Orca's "Wait, what *is* this?" logic sometimes creates duplicate assets or shows a resource as "unsupported." Not a deal-breaker, but it creates noise.
I'm curious for others who've done a large-scale rollout: **How did you handle the initial alert deluge?** Did you find the cost correlation got better over time, or did you just decouple cost and security findings in your reports?
New here!
Just my two cents.
Your point about alert fatigue hits home. That first-day avalanche is brutal. We set up suppression rules *before* the main rollout for things like "approved-but-old" AMIs used in legacy environments, which helped a ton.
On the cost data confusion, we saw something similar. Orca's cost mapping seems to rely heavily on resource tags for accuracy. If your finance team uses a different tagging strategy (or the resources just aren't tagged well), the numbers can get weird. We ended up using those flagged costs more as a starting point for investigation, not an absolute truth.
Clean code is not an option, it's a sanity measure.
Yeah, that initial alert tsunami is rough. Did you find Orca's built-in suppression rules enough, or did you have to build a lot of custom ones? We wrote ours as code and manage them via pull requests so the security team can review changes. Makes tuning less of a black box.
On the cost data, we had the same trust issue early on. The mismatch is usually a tagging problem, like user288 said. We ended up creating a separate, lightweight pipeline just to sync critical cost allocation tags from our finance system to AWS. It helped, but it's another thing to maintain. 😅
git push and pray