Headline

DevOps Engineer @Cognizant | Python | Java | DevOps & Cloud Engineer | CI/CD | Cloud Computing & Opeartions | AWS | Terraform | Kubernetes | AI/ML | DevSecOps | cyber security | Linux | ansible | jira | jenkins

About

I am a DevOps & Cloud Engineering professional who believes that great systems are not just built — they are engineered for reliability, automation, and scale. My curiosity started with one question: How does code reliably move from development to production without breaking things? That curiosity led me to work deeply with cloud infrastructure, CI/CD automation, Kubernetes deployments, and monitoring systems. I enjoy understanding how distributed systems behave under load, how failures happen, and how automation can eliminate human error. I strongly follow three principles: 👉🏻 Automate repetitive work 👉🏻 Design for scalability 👉🏻 Monitor everything in production Currently, I work on provisioning cloud infrastructure, maintaining CI/CD pipelines, deploying containerized applications, and improving system observability. I enjoy debugging production issues, analyzing logs, optimizing deployments, and improving system uptime — because that’s where real DevOps engineering happens. What I Have Worked On 👉🏻 Automated cloud resource provisioning using Terraform and AWS, reducing environment setup time and ensuring consistent dev, test, and production configurations. 👉🏻 Built and maintained CI/CD pipelines using GitHub Actions and Azure DevOps to automate builds, testing, Docker image creation, and Kubernetes deployments. 👉🏻 Deployed and supported containerized microservices on Kubernetes (EKS), contributing to high availability and faster production recovery. 👉🏻 Implemented monitoring and alerting systems using Prometheus, Grafana, and ELK Stack to improve production visibility and reduce incident resolution time. 👉🏻 Built a secure serverless file API using AWS Lambda, S3, and API Gateway with CloudWatch monitoring. Core Technical Skills 🤌🏻 Cloud: AWS (EKS, Lambda, S3, API Gateway) 🤌🏻 Infrastructure as Code: Terraform 🤌🏻 CI/CD: GitHub Actions, Azure DevOps 🤌🏻 Containerization: Docker, Kubernetes 🤌🏻 Monitoring & Observability: Prometheus, Grafana, ELK 🤌🏻 Programming & Scripting: Python, Bash, Java 🤌🏻 Databases & Caching: Redis, MongoDB, MySQL DevOps for me is not just a job title — it is the mindset of continuous improvement, automation, and reliability engineering. I am currently seeking opportunities as a DevOps Engineer or Cloud Engineer where I can contribute to building scalable, cloud-native systems and grow in platform engineering and site reliability. If you are hiring or working on interesting infrastructure challenges, let’s connect and build something impactful. Ph.No: +91-8900779272 | E.Mail: arnaba178@gmail.com

Location

Gurugram

AI stack

codex

cursor

claudecode

Work experience

DevOps Engineer at Cognizant, Nov 2025 - Present · 10 mos, Chennai, During my tenure, Cognizant was delivering enterprise-grade SaaS and cloud-native solutions to global clients, requiring highly reliable, scalable, and automated infrastructure across development, testing, and production environments. In this fast-paced delivery environment, I: • Automated cloud infrastructure provisioning, reducing environment setup time by 55% using Terraform and AWS. • Built CI/CD pipelines, shortening release cycles and improving deployment consistency using GitHub Actions and Azure DevOps. • Deployed and managed containerized workloads, maintaining 99.9% uptime using Docker and Kubernetes (EKS). • Resolved production incidents and optimized pod/network configurations, improving recovery time using Kubernetes troubleshooting and logging tools. • Implemented observability dashboards and alerting, reducing incident detection time using Prometheus and Grafana. This role strengthened my expertise in: Infrastructure as Code (IaC), CI/CD Automation, Kubernetes Administration, Cloud Architecture, Production Support, Monitoring & Observability.

Cloud Engineer Intern (DevOps) at NTT DATA, Jan 2025 - Aug 2025 · 8 mos, Remote, During this phase, the organization was focused on building scalable SaaS-based systems and optimizing performance for high-traffic applications. The emphasis was on reliability, automation, and distributed system efficiency. Within this environment, I: • Implemented Redis-based caching, reducing API response time by 45% and lowering database read load by 50% using Redis and performance tuning techniques. • Built centralized logging and monitoring stack, reducing mean time to resolution using Prometheus, Grafana, and ELK Stack. • Containerized and deployed microservices, improving deployment reliability and achieving high availability using Docker and Kubernetes with autoscaling. • Automated infrastructure provisioning and deployments, reducing manual effort from days to hours using Terraform and GitHub Actions CI/CD. This experience helped me develop strong foundations in: Cloud Infrastructure, Microservices Architecture, Distributed Systems, Performance Optimization, CI/CD Pipelines, and Observability Engineering.

Education

Bachelor of Technology - BTech, Computer Engineering, COEP (College of Engineering, Pune)

Public links

github: https://github.com/ArnabAdhikar