Contributed two targeted enhancements to the mlflow/mlflow repository, focusing on security and deployment reliability. Updated the documentation to strengthen the default admin password, reducing the risk of unauthorized access by addressing default-credentials vulnerabilities. Refactored Docker-Compose Bash commands to improve multiline parsing, which enhanced both readability and the reliability of deployment scripts. Employed DevOps practices and leveraged skills in Docker, YAML configuration, and Bash scripting to ensure robust, maintainable solutions. Maintained clear documentation and traceable, signed commits throughout the process. No bugs were fixed during this period, with efforts concentrated on proactive improvements to security posture and developer experience.