Pavan Kumar

About Pavan Kumar

Hi, I\'m Pavan Kumar Buddepu, a passionate DevOps Engineer with having experience of 4+ in…

Experience

1. Azure Devops Engineer

   Tata Consultancy Services

   Nov 2021 — Present · Hyderabad, IN

   Built CI/CD pipelines using Jenkins for continuous integration and continuous deployment. Utilized Terraform for Infrastructure as Code (IaC) to automate resource provisioning, resolve discrepancies, and ensure consistent infrastructure states. Created Dockerfiles for containerizing applications and enabling deployment through Docker. Conducted resource allocation and utilization analysis, leading to the optimization of container resource limits and requests. This resulted in a 15% reduction in infrastructure costs while maintaining optimal application performance. Streamlined the CI/CD pipeline for Java-based applications using Maven, resulting in a 20% reduction in build and deployment times. Developed a custom Shell script to automate routine system backups, enhancing disaster recovery capabilities. Integrated tools across CI/CD stages including Nexus, SonarQube for code quality, and security checks. Managed source code with Git, GitLab, and GitHub, resolving merge conflicts and managing branches and permissions to maintain organized development workflows Implemented proactive monitoring and alerting using Prometheus and Grafana, reducing system downtime by 15%. Provisioning AWS cloud infrastructure using Terraform and configuring them using Ansible. Experience setting multi region and multi cloud terraform projects and well versed using terraform workspaces. Integrated security analysis tools such as OWASP Dependency Check for vulnerability scanning Demonstrated excellent problem-solving skills by automating routine server maintenance tasks, freeing up valuable team resources for strategic projects. Managed and maintained Kubernetes clusters, ensuring high availability and scalability for containerized applications. Implemented rolling updates and automatic scaling to accommodate increased workloads during peak usage periods.