Noida, Uttar Pradesh, India
As an AWS DevOps Engineer with 3.5+ years of experience designing, deploying, and managing scalable cloud infrastructure across Development, UAT, Pre-Production, and Production environments. I specialize in building secure, highly available, and resilient cloud-native systems using AWS services such as Amazon EKS, Amazon RDS (PostgreSQL), Amazon S3, and Amazon ECS. My focus is on architecting infrastructure that ensures performance, reliability, and cost optimization for SaaS-based applications. I design and implement end-to-end CI/CD pipelines using AWS CodeCommit, CodePipeline, CodeDeploy, GitHub Actions, and GitLab CI/CD to automate deployments, improve release cycles, and enhance operational efficiency. I am experienced in Infrastructure as Code, containerization with Docker, and orchestration with Kubernetes to streamline modern DevOps workflows. With a Master of Computer Applications, I am deeply passionate about cloud architecture, automation, and building production-grade systems. I thrive in dynamic environments where scalability, stability, and continuous improvement are key priorities. 🔹 Core Expertise: AWS | Kubernetes | Docker | EKS | ECS | RDS PostgreSQL | CI/CD | Infrastructure as Code | Linux | Cloud Automation | High Availability | Monitoring I am always open to challenging opportunities where I can contribute to scalable cloud solutions and drive DevOps excellence.
Rentilium is a cloud-native ERP SaaS application built to support multi-tenant business operations with high availability, security, and scalability. As an AWS DevOps Engineer, I designed, deployed, and managed the complete AWS infrastructure and DevOps lifecycle across Dev, UAT, Pre-Production, and Production environments. The application is hosted on Amazon Linux EC2 with Nginx and Apache Tomcat, while containerized workloads run on Amazon EKS, with images stored in Amazon ECR. Data is managed using Amazon RDS PostgreSQL with RDS Proxy for optimized database connections. Amazon S3 is used for static assets, backups, and deployment artifacts. I implemented CI/CD pipelines using AWS CodeCommit, CodePipeline, and CodeDeploy, enabling multiple deployments per week and reducing release time by ~30%. AWS Lambda was used for automation, scheduled tasks, and event-driven workflows. Security is enforced using AWS IAM (RBAC-based access), Amazon Cognito, and AWS security tools. The production environment is deployed across multiple Availability Zones, achieving 99.9% uptime. Infrastructure optimization and automation resulted in approximately 20–25% cost savings while maintaining performance and reliability.
• Monitored application and server logs, identified critical issues, and performed root cause analysis to prevent recurring incidents. • Troubleshot network, server, and application issues, coordinating with cross-functional teams to resolve production incidents. • Reduced system downtime by 15% by proactively monitoring alerts and resolving store-level technical issues.