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CONTENT OF PORTFOLIO
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    DEVOPS AND CLOUD RELATED PROJECTS

    EXECUTED PROJECTS || CONTRIBUTIONS

    1. GITHUB ACTIONS CICD PIPELINE PROJECT – SOURCE GITHUB
    2. MICROSERVICE_CHAT_ APPLICATION USING DOCKER AND KUBERNETES
    3. PROVISIONING DOCKER INFRASTRUCTURE USING TERRAFORM
    4.  PYTHON AUTOMATION PROJECT
    5. SETTING UP A TERRAFORM MODULE FOR A VIRTUAL PRIVATE CLOUD 
    6. STATIC HOSTING IN AMAZON S3
    7.  BUILDING A VIRTUAL PRIVATE CLOUD
    8. VPC TRAFFIC FLOW AND SECURITY 

    GITHUB ACTIONS CICD PIPELINE PROJECT

    CLICK HERE FOR FULL PROJECT IN GITHUB
    This is a full DevOps project demonstrating:
    • Docker containerization
    • Automated builds & tests using GitHub Actions
    • Pushing Docker images to Docker Hub
    • Deployment using Docker Hub images
    • Unit testing with PyTest
    • A simple Python/Flask application
    Tools&Softwares
    • Kubernetes
    • Docker 
    • Pytest unit testing
    • GitHub Actions CI/CD Pipeline
    • Automatic build & push to Docker Hub
    • Deployment using Docker Hub image

    MICROSERVICE-CHAT-APPLICATION

    CLICK HERE FOR FULL PROJECT IN GITHUB
    Tool requirement for the project
    1. Python 3.11+ installed (for FastAPI services)
    2. Docker & Docker Compose installed
    3. VS Code extensions (optional but helpful):
    4. Python (for code highlighting, virtualenv)
    5. Docker (to manage containers)
    6. Pylance (for type checking)
    7. REST Client (optional, test APIs from VS Code)
    8. Live Share (optional, for collaboration)
    Tools&Softwares
    • Flask (simple Python API)
    • Docker 
    • Pytest unit testing
    • GitHub Actions CI/CD Pipeline
    • Automatic build & push to Docker Hub
    • Deployment using Docker Hub image

    PROVISIONING DOCKER INFRASTRUCTURE USING TERRAFORM

    CLICK HERE FOR FULL PROJECT IN GITHUB
    PROJECT DESCRIPTION

    Creating and managing Docker infrastructure using Terraform involves defining your desired Docker resources in Terraform configuration files and then using Terraform commands to provision and manage those resources.

    1. Terraform and its related plugins
    2. Docker images
    KEY TAKEAWAYS FROM PROJECT
     
    The above project demonstrated the following
    1. Key understanding of the terraform modules and syntaxes
    2. Understanding the implementations of the verious terraform commands
    3. Re-organization of the various modules to provision an infrstrasture(Docker)
    4. Understanding of versioning in terraform and implementations with plugins in terraform

    BACKEND DEVELOPMENT FOR A RESTAURNT BLOG

    CLICK HERE FOR FULL PROJECT IN GITHUB
    PROJECT DETAILS
    1. Node.js and Express.js are distinct components within the JavaScript ecosystem for server-side development, serving different purposes but often used together.
      • Node.js is a runtime environment that allows JavaScript code to be executed outside of a web browser, typically on a server.why we use mongo db?
    2. MongoDB is a popular choice for many modern applications due to its flexibility, scalability, and high performance. It’s a NoSQL database, offering a schema-less document model that allows for easier handling of diverse and evolving data structures. MongoDB’s horizontal scalability and robust indexing also make it suitable for applications with high traffic and complex data

    KEY TAKEAWAYS FROM THE PROJECT

    1. Installation of project depenedencies using npm
    2. Installation of router for connection
    3. Creating models for backend development
    4. Setting up of a database connection for mongodb

    TERRAFORM INSTRUCTURE SETUP FOR VIRTUAL PRIVATE CLOUD

    CLICK HERE FOR FULL PROJECT IN GITHUB
    Project Goals
     
    • This project serves as a showcase of best practices in Infrastructure as Code (IaC), specifically demonstrating:
    • Modular and Reusable Code: Using Terraform to define an entire VPC stack, including networking components.
    • Networking Fundamentals: Establishing a highly available and secure network architecture (e.g., public and private subnets, routing).
    • Remote State Management: Setting up a remote backend (e.g., S3/DynamoDB, Azure Storage, GCS, or HCP Terraform) for collaborative and secure state storage.
    • Input Variables: Utilizing variables to make the configuration dynamic and easily deployable in different environments.
    Key Takeaways (What I Learned)
     
    • Provider Configuration: Learned to configure the [AWS/GCP/Azure] provider and authenticate securely.
    • Resource Dependency: Handled implicit dependencies, such as ensuring the Route Tables are attached to the Subnets after they are created.
    • Data Sources: Used data “aws_availability_zones” to dynamically fetch AZs, ensuring the subnets are distributed correctly for high availability.
    • Resource Loops: Used for_each or count arguments to provision multiple, identical resources (like subnets) efficiently.

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