Using ChatGPT for CI/CD in cloud-native apps presents significant challenges, primarily concerning accuracy and security. Large Language Models (LLMs) can hallucinate incorrect commands or code snippets, potentially breaking pipelines or introducing vulnerabilities, making reliable automation difficult. Another major hurdle is context management; ChatGPT struggles to maintain state across complex, multi-stage pipelines and deeply understand dynamic cloud environments. The non-deterministic nature of LLM outputs also makes repeatable and predictable pipeline execution hard to achieve, requiring constant human oversight for validation. Integrating a conversational AI into existing declarative CI/CD tools and complex Kubernetes workflows adds considerable complexity, as does debugging issues within LLM-generated logic. Therefore, ensuring consistent, secure, and explainable automation remains a substantial barrier for widespread adoption in production CI/CD. More details: https://erpsoftwareblog.com/cloud/flow/post_click.php?bid=1&pid=1597&destination=https%3A%2F%2Fabcname.com.ua