Hey everyone! Just wanted to share our team's experience migrating from Aqua Security to Orca Security. We finished the full deployment about six months ago, so I thought I'd report back.
The main driver for us was simplifying our cloud security view. With Aqua, we felt like we were managing a lot of separate pieces. Orca's side-scanning approach really cut down our deployment headaches. The biggest win has been in prioritization—their alerts focus on the actual risks, so we aren't chasing low-severity noise.
What would you recommend as the next step after a successful deployment? We're looking at deepening our use of Orca for compliance workflows and maybe even cloud asset management. Any tips from teams further along? 😊
I run security tooling for a 150-person SaaS shop on AWS/GCP. We trialed both Aqua and Orca 18 months ago before settling on a third option (Wiz), but we ran them head-to-head for a quarter.
**True TCO:** Orca's pricing leans on per-asset scanning, which at my last shop ran ~$25-30k annually for a modest AWS footprint. Aqua's consumption-based licensing for container scanning and serverless felt more predictable, around $18-22k. Both balloon if you auto-discover everything without scoping.
**Deployment Friction:** Orca's side-scanning was trivial to deploy - one cloud role per account. Aqua required lightweight agents on our EKS nodes and a daemonset for container registry scanning, which added about 3 days of infra-as-code tweaking.
**Alert Fatigue:** Orca's "risk score" genuinely cut our daily alert volume from ~120 with Aqua to ~25-30 actionable items. The trade-off is you lose granular control over alert thresholds; you're buying their threat model.
**Compliance Gap:** For compliance workflows (like your next step), Aqua's built-in policy templates for PCI-DSS v3.2.1 were more detailed. Orca treats compliance as another finding type, so you'll be building more custom reporting.
I'd only recommend Orca to a team that values operational simplicity over deep, customizable policy engines. If compliance automation is your next major goal, you might find Orca's reporting a bit thin. What's your team's size and what's your tolerance for building custom policies versus using out-of-box ones?
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Side-scanning does cut deployment time, but watch your cloud bills. That data pull from the cloud APIs isn't free. On AWS, our CloudTrail bill went up 18% after enabling Orca's full inventory.
For next steps, push their API. Pull findings into a data lake (DuckDB works). Then you can run your own trend analysis over time. We found 40% of their "high" alerts were repeats on stale dev assets we forgot to delete. Their UI won't show you that.
Numbers don't lie.
You're absolutely right about the hidden cost of cloud API calls. That 18% CloudTrail bump is significant. We saw something similar but on the data transfer side - our egress charges from CloudWatch Logs increased because Orca's default configuration pulled more frequently than we needed for our relatively static dev environments.
Your point about the API and trend analysis is the real unlock. We've been pushing findings into Snowflake via their webhook and using dbt to deduplicate. The pattern you noticed with stale dev assets is common. We also found that "high" alerts on transient auto-scaling group instances were being counted as unique each time, inflating our perceived risk. Building a simple aggregate view by resource type and tag over a rolling 30-day window changed our entire response workflow.
What's your method for flagging those stale assets automatically? We ended up creating a simple Workato flow that cross-references Orca findings with our CI/CD pipeline's last deployment tag.
connected
Pushing findings to Snowflake is a solid move. We do something similar but landed on BigQuery because our whole logging pipeline was already there. The real trick is that cross-reference step for stale assets.
We built a scheduled query that compares Orca's asset inventory against our Terraform state files in a GCS backend. Anything in Orca that isn't in the state file and hasn't been modified in the cloud console for 90 days gets flagged for a cleanup ticket automatically. It's brutal but effective, and it stops those repeat alerts on zombie resources.
A word of caution on that method - it only works if your infra is 100% IaC. For the legacy bits, we had to fall back on a tag-based lifecycle policy.
Automate everything. Twice.
That's a really smart approach, pulling in the Terraform state for comparison. We went a similar route, but instead of querying state files directly, we started piping the Orca inventory into our data lake alongside a feed from our CI/CD pipeline. That way we can correlate active resources with recent deployments, not just declared state.
It catches those "temporarily manual" fixes that sometimes never get codified. The tag fallback for legacy stuff is key though. We ended up creating a mandatory `owner` tag policy as a stopgap, which at least gives us someone to nudge when the orphaned resource alerts pop up.
ship it