I led the design and implementation of a CI/CD pipeline for a FinTech company's ATM cash management system. The project involved integrating a sophisticated Python AI model that optimized cash distribution and predicted ATM replenishment needs.

GitHub and GitLab: Utilized GitHub for source code management and GitLab for CI/CD orchestration. Established automated workflows to ensure seamless integration and deployment processes.

Docker: Developed Docker images for microservices and the AI model, ensuring consistent environments across development, testing, and production.

Kubernetes: Deployed Docker containers on AWS using Kubernetes for efficient scaling, management, and orchestration of services. Configured Kubernetes clusters to handle high availability and load balancing.

Automated testing and deployment processes using GitLab CI/CD pipelines. Set up stages for building, testing, and deploying applications to different environments.

Implemented monitoring and logging to track the performance and availability of applications.

Leveraged AWS services like EKS (Elastic Kubernetes Service) for container management, RDS for database management, and S3 for data storage. Used IAM for secure access control and CloudFormation for infrastructure as code.

Integrated a Python-based AI model to forecast cash demand and optimize logistics for ATM cash replenishment. The model was trained using real-time data streamed through the pipeline, enabling adaptive learning and accurate predictions.