README.md

File Management Application

Disclaimer

Warning

This application is for demo purposes only and is NOT ready for production use. Please use it with caution and be aware that it is not suitable for real-world deployment at this stage.

Features

The File Management Application is a Python application built on the FastAPI framework, providing a set of REST APIs to efficiently manage files. It offers the following features:

1. Upload a File

   Easily upload files to the application, securely storing them in cloud storage.

2. Retrieve an Uploaded File by Name

   Retrieve any previously uploaded file by specifying its name. The application will efficiently fetch the file for you.

3. Delete an Uploaded File by Name

   Remove any uploaded file from the storage with a simple request, freeing up space as needed.

4. Smart File Management

   The application has the intelligence to detect files with similar content. Instead of duplicating files, it reuses uploaded files to optimize storage space efficiently.

For details, refer to the API documentation available at https://nthienan.github.io/file-mgmt-app/

System Design

• Architecture design
• CI/CD
• Infrastructure deployment

Development

Prefer to app/README.md

Repository Structure

For this small project, I've opted for a monorepo, which serves as a centralized repository for storing the application source code, infrastructure code for deploying the application to AWS, and the deployment pipeline, along with their respective configurations. The directory structure I've chosen promotes simplicity and ease of navigation. In the app/ directory which houses the main application code. Additionally, a Dockerfile is included for containerization and a requirements.txt file to manage Python dependencies.

The infra/ directory houses essential Terraform configuration files, including variables.tf and provider.tf. Additionally, within the infra/ directory, there is a tfvars/ subdirectory that contains corresponding Terraform variable files for each deployment environment. For instance, tfvars/dev.tfvars is used for the development environment, tfvars/stag.tfvars for the staging environment, and so on.

To streamline development and ensure consistent workflows, I've made use of GitHub Actions in the .github/ directory. The workflows/ subdirectory contains wf-build-and-deploy.yaml, which automates continuous integration and continuous deployment processes.

Additionally, the docs/ folder contains documentation and relevant resources for the project. This includes architecture diagram, and any other documentation essential for understanding and maintaining the project.

As always, the README.md file provides essential project information. This structure allows me to maintain a clean and organized project.

.
├── Makefile
├── README.md
├── app
│   ├── Dockerfile
│   ├── README.md
│   ├── main.py
│   ├── requirements.txt
│   └── ...
├── docs
│   └── ...
└── infra
    ├── README.md
    ├── data.tf
    ├── local.tf
    ├── provider.tf
    ├── tfvars
    │   └── dev.tfvars
    ├── variables.tf
    ├── version.tf
    ├── ...