🚀 GitFlow – Lightweight CI/CD Orchestrator

Tech Stack: Go · React · Docker · WebSockets · Gin · TailwindCSS

DevFlow is a self-hosted CI/CD automation tool that executes YAML-defined workflows inside Docker containers, streams real-time logs locally!!.

🌟 Features

✅ Pipeline as Code: Define multi-stage workflows using simple YAML files
✅ Dockerized Execution: Each job runs in an isolated container
✅ Real-Time Logs: WebSocket streaming from Go backend to React UI
✅ Modern UI: Built with React + Tailwind + Framer Motion for smooth animations

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⚙️ Setup Instructions

Below is the following instructions of how to setup the project for your system.

1️⃣ Clone the Repository

Clone the repository and use the following command to install the project inside your system.

git clone https://github.com/<your-username>/gitflow.git
cd gitflow

🏃‍♂️ Build & Run with Docker Compose

Copy and Run the following command to run the frontend and backend of the project, and navigate to the give localhost address.

cd backend && make build && make run
cd frontend && npm i && npm run dev

• Backend → http://localhost:8000
• Frontend → http://localhost:5173

Example for running workflow.

Create Project Create a new test-project directory in your system

mkdir test-project

Copy Location of project use this command to know the exact location of your project that will be used during creation of the project.

cd test-project
pwd

Create YAML copy the following yaml structure, create new file and paste the content inside the file.

Note that the jobs are for golang only .

name: Build & Test
jobs:
  build:
    image: golang:1.23
    steps:
      - run: go build -o app .
  test:
    image: golang:1.23
    steps:
      - run: go test ./...

Creating the pipeline paste the project/directory that you want to run using pwd command, and include the pipeline yaml file.

Run Pipeline Click on the Run button to see the logs.

To Do's

Currently this is a MVP project here are some feature that will be added soon.

• Divide the logs into stages to differentiate logs for each jobs.
• Visualize the jobs inside the workflow to view the dependencies of jobs.
• Store the result of the pipeline into database possibly PostgreQL/SQLite