Governance layer, not execution
Keep GitHub Actions or GitLab as the execution layer while adding evidence, approvals, and policy decisions around production authority.
CI/CD infrastructure change governance
Govern the moment infrastructure asks for authority.
Platform teams need durable evidence when production deploys change IAM, networking, data stores, or other high-impact surfaces. Control9 sits on top of GitHub Actions and GitLab pipelines to classify what is changing, require the right approval, verify deployed artifacts, and correlate cloud audit events for off-path changes.
Who it is for
Control9 is built for platform engineering and security teams responsible forprotected repos and protected environments where CDK, Terraform, or deploy steps can mutate production infrastructure. You keep your existing CI runner and IaC execution layer. Control9 adds governance around thecontrol event: the moment a pipeline requests authority to change infrastructure.
What Control9 is (and is not)
CDK and Terraform first
Read plan and template artifacts, classify semantic risk, and tie decisions to deploy verification and durable evidence timelines.
Not a scanner or CI replacement
Control9 is not a vulnerability scanner, internal developer platform, identity provider, Kubernetes product, chatbot, or broad IaC orchestration platform.
Core workflow
- A pipeline step emits a signed, redacted action envelope from CDK, Terraform, or deploy activity.
- Control9 classifies the change and applies policy in shadow mode (observe) orenforce mode (block or require approval).
- Approvals, deploy verification, and evidence are recorded in anevidence timeline outside ephemeral CI logs.
- Cloud audit correlation highlights mutations that bypassed the approved path.
Why teams adopt Control9
Evidence that survives the pipeline
Decisions, approvals, and deploy outcomes live in a durable timeline instead of scrolling through job logs after an incident.
Semantic risk, not just file diffs
Classify infrastructure intent from plan and template artifacts so policy matches what is actually changing in production.
Shadow mode before enforce mode
Start with observe-only installs that rank findings, then enable enforce mode selectively once controls are trusted.
Use cases
Explore how platform teams apply Control9 across common infrastructure change patterns.
Governed Terraform / OpenTofu change
Classify plan output and require approval before production apply.
Governed CDK / CloudFormation change
Evaluate template diffs without moving execution off your pipeline.
Deploy verification
Confirm deployed artifacts match what was reviewed and approved.
Approval evidence
Keep durable records outside ephemeral CI logs.
Off-path detection
Correlate cloud audit signals with governed pipeline activity.
Shadow-mode assessment
Observe-only installs that rank findings before enforce mode.
Ready to assess your pipeline?
Start with a two to four week shadow-mode assessment across selected protected repos. Production deploys continue while you review ranked findings before enabling enforce mode.