container-validator

Container validation scans Dockerfiles and Kubernetes manifests to identify security risks, misconfigurations, and best-practice violations. It checks for non-root user execution, health checks, resource limits, liveness/readiness probes, exposed secrets, and CIS benchmark compliance before deployment.

Yes. Container validation works in CI/CD pipelines to automatically scan new Dockerfiles and Kubernetes manifests, flagging critical security flaws and performance bottlenecks before deployment. It integrates with image builds and production deployment workflows.

Container validation detects missing health checks, absent resource limits, insecure security contexts, non-root user violations, secret exposure, layer optimization problems, and Kubernetes probe configuration gaps in Dockerfiles, Kubernetes resources, and docker-compose files.

Yes. Container validation requires Python 3 and PyYAML to parse and validate container configurations. These dependencies enable manifest analysis and rule-based scanning against best practices and compliance standards.

Automated container validation against best practices, security standards, and CIS benchmarks prevents misconfigurations and vulnerabilities in production. Validation covers Dockerfile optimization, Kubernetes resource constraints, probe configuration, and security context settings.

Yes. Container validation scans Dockerfiles, Kubernetes manifests, and docker-compose configurations with configurable rules to identify security risks and compliance violations across your container infrastructure.