Step 1
Assign owners for configuration, secrets, and upgrades.
Platform operations
Run the gateway with the same rigor as core platform services
Platform operations teams own configuration, upgrades, monitoring, and incident review for the AI gateway. This page summarizes operator practices that keep policy outcomes trustworthy in production.
What you are trying to solve
Manual configuration drift between environments can change policy outcomes without a tracked release.
Step 2
Automate policy tests on every configuration change.
Step 3
Review evidence samples with security after releases.
Operator responsibilities
Own gateway availability, configuration releases, credential rotation, and upgrade planning. Application teams own client integration but depend on your stable endpoint and configuration.
Document which environments route supported traffic through the gateway and which paths remain out of scope.
Recommended operating practices
Versioned configuration
Store YAML in git, require review for production changes, and keep staging aligned with release candidates.
Policy test gates
Run deterministic tests before and after configuration changes that affect production traffic.
Evidence sampling
Review decision events regularly and pull samples during incidents or policy disputes.
Handoffs to other teams
- Security teams review policy design and evidence samples.
- FinOps teams review usage signals and configured thresholds for applicable scopes.
- Application teams integrate supported clients and report integration defects through your standard workflow.
Related paths
Continue with a template, product area, or guide that matches this page.
Operations teams treat the gateway like any other platform service with tested releases and evidence review.
Download Verdictan and wire the gateway into your staging environment first.