Hello Hello , I'm

Jayasurya

Devops Engineer @ Codemagen

About me

Hi there! I'm Jayasurya, an AWS Cloud Architect and DevOps Engineer with a strong focus on building and deploying scalable, reliable cloud infrastructures. With hands-on experience in tools like Docker, Kubernetes, Terraform, and CI/CD platforms like GitHub Actions and CircleCI, I specialize in automating workflows and managing infrastructure as code.

I work extensively with AWS services like EC2, S3, Lambda, and EKS to deploy cloud-native applications. From containerization to automated deployments and infrastructure provisioning, I ensure robust and efficient DevOps solutions.

Here are my main skills:

My Experience

Codemagen Technologies

DevOps Engineer Intern

Apr 2025 - present

I design and manage CI/CD pipelines for seamless software deployment. I will handle cloud infrastructure on AWS, Azure, and GCP using Terraform, CloudFormation and also includes containerizing applications with Docker and managing them with Kubernetes for scalability.

CentillionLabs

DevOps Engineer Intern

Dec 2023 - Feb 2024

EZOUT: Spearheaded the deployment and automation of Kubernetes clusters using Terraform and CircleCI, ensuring seamless and scalable infrastructure environments in Amazon Web Service. Assisted in the design, deployment, and management of cloud infrastructure.

ChainAim Corp USA

Platform Engineer / Deployment Engineer Intern

Aug 2024 - Nov 2024

Deployed the ACTUS platform and built a Docusaurus-based documentation site. Additionally, I deployed the ACTUS Hackathon Challenge site, further enhancing my deployment skills.

Systimanx

Software Engineer Intern

Mar 2024 - May 2024

Contributed to the development of enterprise applications, focusing on improving the user interface and enhancing system performance. Worked with backend services and collaborated with cross-functional teams to implement solutions.

Devops Projects

Full Stack Kubernetes Deployment on Minikube

A full-stack application is deployed on Minikube, a local Kubernetes environment. It manages containerized services for the front-end, back-end, and database, ensuring scalability and secure configuration handling.

Portfolio Web App Deployed on Kubernetes

Deployed my portfolio app using Kubernetes and Minikube. I containerized the app with Docker, set up Kubernetes deployment and services, and scaled it for better performance.

Machine Learning Model Deployed on AWS

This project not only demonstrates my ability to integrate cloud infrastructure but also showcases my skills in automating deployment pipelines and creating scalable, production-ready applications.

Revolutionizing Deployment with Ezout on GKE

Ezout simplifies deployment by seamlessly deploying Docker images on Google Kubernetes Engine (GKE), with enhanced flexibility through node pod creation in distinct GKE locations. By utilizing TorchServe for efficient model serving, Ezout ensures scalable and optimized operations.

Infrastructure as Code with Terraform on AWS

Designed and implemented infrastructure using Terraform on AWS, including a detailed architecture diagram. The project demonstrates secure, scalable, and reliable infrastructure provisioning and management, showcasing best practices in infrastructure as a code (IaC).

React Application Deployed on AWS EC2

Deployed a React application on an AWS EC2 instance using Terraform for infrastructure as code. Integrated CircleCI for continuous integration and continuous deployment (CI/CD), automating the process. Pulled a Docker image from Docker Hub and deployed it on the EC2 instance.

Machine Learning Projects

Machine Learning Based Crop Recommendation System

Developed a machine learning model to recommend the most suitable crops based on various parameters like soil type, weather conditions, and historical data. The system uses algorithms such as Naive Bayes and Random Forest for high accuracy.

AI Assistance for Kongu Engineering College

Developed an AI chatbot for my college using Vertex AI in GCP. The chatbot provides real-time assistance and information to students and parents through a user-friendly interface created with Flask. It can answer frequently asked questions, provide updates on events, and guide users through various administrative processes.

Deep Learning based Crop Disease Prediction

Developed a deep learning model to predict crop diseases using image data. Implemented a convolutional neural network (CNN) in TensorFlow and Keras to classify different types of crop diseases. The project was converted into a paper, published in IEEE Xplore, and presented at ICAICCIT 2024.

MERN Projects

SnapURL - URL Shortening with Advanced Features

SnapURL is a full-stack application designed for quick and efficient URL shortening. It offers features like custom short URLs, click limits, password protection, and QR code generation with an intuitive and user-friendly interface.

Persionalized Product Recommendation System

Built an innovative personalized recommendation system in 24 hours for the Farm2Bag platform during the AI Conclave Hackathon. This system enhances user experience by analyzing preferences and delivering tailored product recommendations, boosting user engagement and sales.

Random Quote Generator

A MERN stack application that displays random quotes with the author's name, featuring a simple UI. It uses MongoDB, Express.js, Node.js, and React to fetch and present a diverse collection of quotes. Users can also contribute their own quotes to the database, enhancing the collection.

My Achievements

AI Concave Hackathon

Winner - ₹10,000

Won the National-level Hackathon with "Farm2Bag," a personalized recommendation system enhancing user experience and boosting sales.

Puzzle Solving Fest

1st Place

Won 1st place at the highly competitive puzzle-solving fest conducted at Kongu Engineering College, showcasing exceptional logical thinking and problem-solving skills.

Internship Excellence

Outstanding Contribution

Achieved recognition for exceptional problem-solving skills and initiative during my internship at SystimaNx, contributing to key projects and delivering results beyond expectations.

Hacksphere Hackathon

2nd Place

Secured 2nd place in the Hacksphere hackathon by developing an innovative chatbot for farmers, enabling natural language-based CRUD operations with the Farm to Bag platform.