Vasavi Pabba

Project:

Cloud Infrastructure Automation and Deployment

• Assisted in managing and maintaining AWS infrastructure including EC2, S3, and VPC.
• Supported CI/CD automation using GitHub Actions and Jenkins to streamline deployments.
• Worked with Terraform for basic infrastructure provisioning and configuration.
• Helped containerize applications using Docker for consistent deployment environments.
• Monitored cloud performance using CloudWatch and resolved basic deployment issues.
• Collaborated with the DevOps team to ensure stable, secure, and efficient cloud operations.

• Improved code deployment efficiency by automating processes with CI/CD pipelines.
• Maintained version control systems like Git or SVN for seamless collaboration among developers and engineers during project lifecycles.
• Designed and implemented containerization strategies using Docker and Kubernetes, improving resource utilization and management.

Project 1:

TaskMaster – Serverless Task Management Web App

Developed TaskMaster, a serverless task management web application using AWS Lambda, designed to handle dynamic user requests without managing any servers. The backend was implemented with AWS Lambda functions and exposed via API Gateway to provide secure and scalable RESTful APIs. DynamoDB was used as a high-performance, NoSQL database for storing user tasks, while AWS Cognito handled authentication and role-based access for secure user management.

Key Responsibilities:

• Designed and developed serverless backend logic using AWS Lambda to handle dynamic user requests efficiently.
• Built and secured RESTful APIs with AWS API Gateway and implemented authentication & authorization using AWS Cognito.
• Managed data storage with DynamoDB, ensuring high availability, scalability, and low latency for user data.
• Automated deployment using AWS SAM and CloudFormation for repeatable, error-free provisioning.
• Monitored application performance using AWS CloudWatch, identifying and resolving bottlenecks proactively.
• Collaborated with frontend developers (React/HTML/CSS) to integrate APIs and ensure seamless user experience.

Impact / Outcome:

• Achieved a fully serverless deployment with automatic scaling.
• Reduced infrastructure costs by 70% compared to traditional EC2-based deployments.

Project 2:

Terraform to Deploy AWS Lambda Function with S3 Trigger.

As part of a cloud automation project, I utilized Terraform to provision and configure AWS Lambda functions triggered by events from an S3 bucket. This project involved automating the deployment of serverless applications using infrastructure-as-code (IaC) principles, ensuring scalability and efficient resource management.

Key Responsibilities:

• Designed and implemented infrastructure for deploying Lambda functions in AWS using Terraform.
• Configured S3 event notifications to trigger Lambda functions upon object creation in S3 buckets.
• Defined IAM roles and policies to secure Lambda functions and control access to AWS resources.
• Automated the Lambda deployment process, enhancing operational efficiency and reducing deployment time.
• Implemented S3 bucket notification configurations to filter specific events, such as object uploads or modifications.
• Applied best practices for managing AWS resources and security by following the least-privilege principle.

Technologies & Tools:

• Cloud Platforms: AWS (Amazon Web Services)
• Infrastructure as Code (IaC): Terraform
• Compute Services: AWS Lambda
• Storage: Amazon S3
• Security: AWS IAM (Identity and Access Management), Lambda Permissions
• Programming Languages: Python (for Lambda function options)
• Version Control: Git
• Automation Tools: Terraform CLI

Impact / Outcomes:

• Reduced manual deployment effort and minimized human errors.
• Enabled real-time file processing, improving operational efficiency.
• Achieved cost savings by leveraging on-demand serverless execution.
• Ensured scalable and reliable infrastructure with IaC and CloudWatch monitoring.

Project 3:

DevOps Engineer | Dockerized Flask Application Deployment on AWS EC2 with CI/CD Pipeline (GitHub Actions & Terraform)

In this project, I spearheaded the deployment of a Dockerized Flask application on AWS EC2 using Terraform for infrastructure provisioning and GitHub Actions for continuous integration and deployment (CI/CD). This solution allowed for automated application delivery, infrastructure management, and streamlined deployments in a cloud environment.

Key Responsibilities:

• Designed and implemented a CI/CD pipeline using GitHub Actions to automate the build, test, and deployment process for a Dockerized Flask application.
• Used Terraform to provision AWS infrastructure, including EC2 instances, Security Groups, Elastic IPs, and other resources required to host the application.
• Containerized the Flask application using Docker, ensuring a consistent and portable deployment environment.
• Configured GitHub Actions workflows to automatically build Docker images, push to Docker Hub, and deploy the application to EC2 instances.
• Established AWS EC2 security groups to control traffic and ensure secure access to the deployed application.
• Implemented Terraform modules to automate and manage the infrastructure lifecycle in a version-controlled, repeatable manner.
• Ensured best practices for security, scalability, and performance while deploying and managing the application on AWS.

Technologies & Tools:

• Cloud Platforms: AWS (Amazon Web Services)
• Compute Services: AWS EC2
• Containerization: Docker
• Web Framework: Flask (Python)
• Infrastructure as Code (IaC): Terraform
• CI/CD Tools: GitHub Actions
• Version Control: Git
• Security: AWS Security Groups, IAM (Identity and Access Management)
• Networking: AWS VPC (Virtual Private Cloud), Elastic IP
• Container Registry: Docker Hub
• Programming Languages: Python (Flask), Bash (for GitHub Actions workflows)
• Developed and implemented automated deployment pipelines using AWS services, enhancing deployment speed and reliability.Impact / Outcomes:
• Achieved automated, repeatable deployments, reducing manual intervention and errors.
• Improved deployment speed and reliability with CI/CD pipelines.
• Ensured consistent environments through Docker containerization.
• Enhanced scalability and maintainability of infrastructure via Terraform.
• Reduced downtime and improved monitoring with CloudWatch integration.