Apply your Kubernetes engineering rules throughout the software lifecycle
Kubernetes standards are often documented centrally but implemented independently across repositories and teams.
The Kubernetes Assurance Agent turns platform rules into repeatable checks that can run while code is written, before merge, in CI, and, where required, against deployed clusters.
One rule set, multiple checkpoints
During coding
Use the Kubernetes assurance skill on the current change before commit.
Before merge
Review PR changes against required platform rules.
In CI
Scan the relevant repository or generated configuration and fail required checks.
At runtime
Audit live clusters and compare deployed state with expected engineering rules.
What the agent can evaluate
The intended checking domain includes:
- security contexts
- container privileges
- ServiceAccounts
- probes
- resource requests and limits
- namespace conventions
- network policies
- deployment settings
- workload identity
- secret usage
- image policies
- configuration standards
- organization-specific Kubernetes conventions
Findings should be actionable
A useful finding should contain:
- the rule
- severity
- affected file or resource
- evidence
- why the rule matters
- suggested remediation
- whether the finding blocks acceptance
Vague output such as "Kubernetes configuration may be insecure" is not a finding.
Platform teams keep ownership of the rules
The platform or architecture team defines the required standards.
AJWAIN.AI helps translate those standards into executable assurance checks and works with customer engineering teams to refine the agent using real repositories and deployed environments.
Common checks can be reusable. Organization-specific standards remain configurable for the customer.
Frequently asked questions
During coding on the current change, in PR review, in CI against the repository or generated configuration, and, where required, as a runtime audit of live clusters.
The rule, severity, affected file or resource, evidence, why the rule matters, a suggested remediation, and whether the finding blocks acceptance.
The platform or architecture team defines the required standards. AJWAIN.AI helps translate them into executable checks and refines the agent with your engineering teams using real repositories and deployed environments.