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Apiiro onboarding experience - what to expect during the first month

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(@cloud_ops_amy)
Honorable Member
Joined: 7 months ago
Posts: 450
Topic starter   [#25220]

Hi everyone, our engineering team is starting to onboard Apiiro for our cloud-native CI/CD pipeline. We're looking to get a better handle on our application security posture, especially around IaC scanning and risk-based prioritization. I've read the docs, but I'd love to hear from teams who have already gone through the first 30 days.

What should we realistically expect in terms of setup, initial findings, and team bandwidth? Specifically:

* **Initial Integration & Data Onboarding:** How long did it take for the platform to fully ingest and map your code, cloud resources (we're heavy on AWS and Terraform), and pipelines? Were there any surprises with the data collection agents or APIs?
* **Noise-to-Signal Ratio:** After the first scan, were the initial risk findings overwhelming? How much tuning was needed to filter out the "expected" risks in our dev environments?
* **Team Process Changes:** Did you have to immediately adjust your development or deployment workflows? For example, we're concerned about how it integrates with our existing GitHub Actions and ArgoCD pipelines.

Here's a simplified snippet of our current Terraform setup it will be assessing. I'm curious how granular the IaC security findings get.

```hcl
resource "aws_iam_role" "lambda_exec" {
name = "my_lambda_role"
assume_role_policy = jsonencode({
Version = "2012-10-17"
Statement = [{
Action = "sts:AssumeRole"
Effect = "Allow"
Principal = {
Service = "lambda.amazonaws.com"
}
}]
})
# Inline policy example - likely a finding
inline_policy {
name = "root"
policy = jsonencode({
Version = "2012-10-17"
Statement = [{
Action = "*"
Effect = "Allow"
Resource = "*"
}]
})
}
}
```

Any insights on the learning curve for the security team versus the development teams would be super helpful. Also, how was the support experience during the critical first month?

-- Amy


Cloud cost nerd. No, I don't use Reserved Instances.


   
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(@charliep)
Prominent Member
Joined: 3 months ago
Posts: 800
 

The initial data onboarding is where the sales pitch meets reality. They claim it's automatic, but expect to spend the first week just getting the AWS integration to see all your accounts. Terraform ingestion is slow, and their mapping of resources to pipelines is often... creative.

Noise-to-signal? Prepare for a firehose. The default risk rules flag everything from dev service accounts to approved IAM patterns. You'll spend the entire second week tuning it just to get a report that doesn't panic management. Their "risk-based prioritization" is just a fancy term for you manually setting severity thresholds.

It absolutely forces workflow changes. The GitHub Actions integration will add minutes to your PR builds, and you'll need to write exemptions for every legacy deployment in ArgoCD. The promise is simplification, but the first month is just adding another approval gate.


Your stack is too complicated.


   
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(@emilyw)
Reputable Member
Joined: 3 months ago
Posts: 185
 

Oof, that sounds rough. The bit about the GitHub Actions adding minutes to PR builds is a real worry for us, as we're trying to keep feedback loops tight.

Did you find that the initial flood of findings uncovered any truly *new* risks your team wasn't aware of, or was it mostly just repackaging known issues in a noisier format?



   
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