Chaitanya M

DevOps/Cloud Engineer with over 5 years of experience in AWS and Azure environments, specializing in object-oriented programming with a strong command of Java, Python, JavaScript, HTML, SQL, and C++. Demonstrates expertise in CI/CD processes, infrastructure as code, and test automation to develop scalable solutions. Proven track record of enhancing performance, reliability, and efficiency in coding environments while leveraging telemetry and metrics for operational excellence. Committed to driving innovation and collaboration within teams to achieve strategic objectives.

• AWS Certified Solutions Architect – Associate, 2023
• AWS Certified Cloud Practitioner, 2022

Project: YOLOv5 Traffic Signal Detection on Android Studio:

• Developed a real-time traffic signal detection application using the YOLOv5 object detection model integrated with Android Studio.
• Utilized Python for model training and optimization, achieving high accuracy in detecting traffic signals.
• Integrated cloud services such as AWS S3 for model storage and retrieval, ensuring scalability and accessibility.
• Implemented continuous integration and deployment pipelines using Jenkins and Docker for seamless updates and improvements.
• Collaborated with cross-functional teams to enhance the application's performance and user experience.

Project: Smart City Traveler:

• Utilized Python for the backend development of the Smart City Traveler mobile application, ensuring robustness, scalability, and maintainability of the server-side components.
• Integrated Python-based RESTful APIs to facilitate communication between the mobile application front end and the cloud-based backend services, enabling seamless data exchange and real-time updates for users.
• Implemented Python libraries and frameworks for data processing and analytics within the cloud-based services, enabling efficient route planning and personalized recommendations based on user preferences and historical data.
• Utilized Python for integrating IoT sensors and devices, enabling the collection and processing of environmental data such as air quality and traffic conditions to enhance the accuracy of recommendations and improve the overall user experience.
• Incorporated Python-based AI algorithms for predictive analysis of transportation patterns and demand forecasting, leveraging machine learning techniques to optimize route planning and resource allocation.
• Employed Python SDKs and libraries for seamless integration with cloud services such as AWS and Azure, ensuring scalability, reliability, and efficient Smart City Traveler application updates deployment.

• Assisted in deploying and managing cloud environments on AWS and Azure, ensuring system reliability and optimizing resource utilization.
• Built and maintained CI/CD pipelines using Jenkins, GitLab CI, and Azure DevOps, reducing deployment time and improving software release efficiency.
• Gained experience in automating infrastructure provisioning with Terraform and CloudFormation, ensuring consistency across environments.
• Worked on containerized deployments using Docker and Kubernetes (EKS, AKS), improving application scalability and management.
• Implemented basic monitoring solutions using AWS CloudWatch, Prometheus, and Splunk, helping teams identify and resolve issues faster.
• Assisted in configuring IAM policies, security groups, and encryption protocols, improving cloud security posture.
• Helped optimize cloud resources using AWS Cost Explorer and Azure Cost Management, reducing unnecessary costs.