Vishal Jangir

Intern @ Celebal Technology | Azure DevOps Services, Programming Languages · Greater Jaipur Area

Pursuing a BTech in Computer Science Engineering at Amity University Rajasthan, Jaipur, expected to graduate in August 2026. Academic foundation includes computer science, algorithms, and software development principles. Recently completed an internship at Celebal Technology, focusing on deploying a Java Spring Boot application on Microsoft Azure using DevOps practices. Contributed to containerization with Docker, built CI/CD pipelines using GitHub Actions, and facilitated deployment on Azure Web App and AKS. Core skills include Azure DevOps Services, programming languages, and DevOps methodologies. Committed to leveraging technical expertise to contribute to impactful technology-driven solutions.

Experience

C

Intern

Celebal Technology · May 2025 – Jul 2025

Not yet confirmed

• Project Title: Deploying a Java application on Azure Web App using GitHub and DevOps tech.
• Mode: Hybrid.
• Details: Designed, containerized, and deployed a Java (Spring Boot) application on Microsoft Azure by implementing DevOps best practices.
• Built an end-to-end CI/CD pipeline using GitHub Actions, containerized the application using Docker, and deployed it on Azure Web App / Azure Kubernetes Service (AKS).
• Integrated monitoring, logging, and security to ensure scalable and reliable deployments.

Intern

YBI Foundation · Jun 2024 – Aug 2024

Not yet confirmed

• Project Title: Predict the numbers Using Stock images.
• Mode: Online.
• Details: Developed an Ai system to predict numbers in advance by using the stock images reading.
• Implemented data collection from the database and used it for the development of the AI system.

T

Intern

TechForce Academy, Australia · Apr 2022 – Jul 2022

Not yet confirmed

• Project Title: Green Field: Smart irrigation Control System Using IoT.
• Mode: Online.
• Details: Design and implemented a smart irrigation system using soil moisture sensors and weather APIs.
• Automated scheduling reduced estimated water usage by 40% and improved crop yield simulation.
• Automated irrigation scheduling is based on data to reduce water wastage and improve crop yield.