AI in DevOps: The Risks of Blindly Trusting Generated Manifests

This Habr article explores the risks of using generative AI to create Kubernetes manifests. While LLMs can quickly produce valid code, the authors warn of hidden dangers: models often rely on outdated practices, insecure configurations, and fail to account for specific infrastructure requirements. Consequently, errors are frequently discovered only during production deployment. The article analyzes why AI makes these mistakes and suggests methods for validating generated configurations before they are deployed. The core message emphasizes the need for a critical approach to AI-generated results and the implementation of automated quality control tools. Using AI in DevOps requires mandatory human oversight to verify manifests, ensuring that security incidents and cluster performance issues are avoided.