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Nareashkaan Vijayaragavan

Software engineer, Web Developer, Apps Developer, Devops enthusiast
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About Me

I'm an adaptable software engineer with a passion for problem-solving and a growing interest in DevOps. I thrive on crafting efficient, scalable solutions and streamlining processes. Committed to continuous learning and collaboration, I excel in writing clean code and exploring DevOps practices.

Name:
Vijayaragavan Nareashkaan
Birthday:
15 January 2001
Degree:
Bsc. (Hons) in Computer Science
Experience:
1+ Years
Phone:
+94 77 848 9936
Email:
vnareashkaan@gmail.com
Address:
No.50 A, Rosary road, Negombo.
Freelance:
Available

3.80/4.0

Current GPA

10+

Projects

4+

Volunteering

Skills

Expericence

Software engineer

Half Life Private Limited | June 2024 - Nov 2024

Worked on a workflow automation tool project, enabling users to create custom processes and automate tasks across various applications and services, while managing OAuth 2.0 credentials.

Software engineer intern

WSO2 Sri Lanka | Nov 2023 - May 2024

A comprehensive framework was developed for managing customized customer tests, integrating deployments and scenarios into WSO2 TestGrid. A CI pipeline was created, product images were created, and a proxy layer was constructed for logic triggers.

Projects

  • All
  • Web development
  • Mobile app devleopment
  • Devops project

Cuddlecare

CuddleCare is a web-based application designed specifically for parents of newborns in Sri Lanka with demanding schedules, helping them track their child's health and development. The app enables parents to manage feeding, sleeping, diaper-changing routines, and developmental milestones with nutritional analysis, while also offering a symptom tracker for common health concerns like fever, cough, and irritability. Built using React and React Native for the front-end and Spring Boot with PostgreSQL for the back-end, CuddleCare combines user-friendly interfaces with a robust, scalable, and efficient backend framework to provide a seamless and reliable experience for parents.

Royal hospital

The Royal Hospital project is an online appointment booking system designed to streamline the process of scheduling doctor appointments. Built using HTML, CSS, and JavaScript for the front-end, PHP for the back-end, and MySQL for database management, the system enables patients to book appointments quickly and efficiently, avoiding transportation challenges and saving time. It also provides features for patients to access and manage their medical reports online and supports online consultations, ensuring safety during health crises like COVID-19. Additionally, the system includes a doctor dashboard for managing booking slots and schedules, improving time management and efficiency for healthcare providers.

Foodie Pokemon

FoodiePokemon is a web application built using the MERN stack (MongoDB, Express.js, React, and Node.js) to streamline food ordering and inventory management in restaurants. It allows users to place orders and track food items efficiently, providing a modern solution for restaurant operations.

Dash Delivery

Dash Delivery is a PERN (PostgreSQL, Express, React, Node) application written in TypeScript, designed for courier service customers to create and track packages seamlessly. The application includes features such as user registration, login, shipment creation, and real-time tracking, supported by a user-friendly dashboard. It ensures robust data persistence, error management, and secure verification with role-based permissions, including an admin user interface for managing records. With a responsive front-end, efficient back-end APIs, and a PostgreSQL database, Dash Delivery provides a reliable and streamlined experience for managing courier services.

WSO2 APIM HELM Deployment

This DevOps project involves deploying an Active-Active API Manager (API-M) setup on an AKS (Azure Kubernetes Service) cluster using modern DevOps tools and practices. The deployment is managed with Docker, Kubernetes, Helm, and Terraform, with prerequisites such as an Azure account and necessary tools (kubectl, kubens, Terraform, Helm, etc.) installed. The process includes setting up the local environment using Minikube, creating Kubernetes namespaces, configuring Helm charts, and deploying PostgreSQL, API-M, and Adminer services. The deployment stage involves creating the infrastructure layer with Terraform, configuring network settings on the Azure portal for inbound and outbound traffic, and accessing the application publicly via the API-M and Adminer URLs. This project ensures a seamless and scalable Active-Active API-M deployment on the AKS cluster.

APIM active-active AKS cluster deployment

This DevOps project focuses on automating the deployment of an API-M (API Manager) cluster with a robust architecture. The deployment includes two nodes of the API-M runtime and two nodes for integration runtimes (Micro Integrator/Streaming Integrator). The automation pipeline is structured into three stages: first, the infrastructure is set up using Infrastructure-as-Code (IaC) to deploy the AKS (Azure Kubernetes Service) cluster and associated resources; second, Helm charts are deployed to manage the application; and third, tests are executed to validate the architecture's stability during updates or new versions of the API-M. The API-M is promoted to the production environment only if all tests are successfully passed, ensuring reliability and seamless deployment.

Research

  • All

Applicability of Deep Learning and Embedding-Based Techniques for Tamil Morphological Analysis

  • Conducting research on Tamil morphological analysis, focusing on tasks such as morphological tagging and lemmatization.
  • An hybrid approach that combines deep learning techniques and similarity-based methods using word embeddings to predict grammatical features and improve accuracy.

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