https://github.com/kingabzpro/gitops-project
A Simple Guide to GitOps using machine learning project.
https://github.com/kingabzpro/gitops-project
Last synced: 3 months ago
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A Simple Guide to GitOps using machine learning project.
- Host: GitHub
- URL: https://github.com/kingabzpro/gitops-project
- Owner: kingabzpro
- License: apache-2.0
- Created: 2024-12-23T08:47:34.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-12-23T09:23:54.000Z (5 months ago)
- Last Synced: 2024-12-23T10:25:28.144Z (5 months ago)
- Language: Python
- Size: 32.2 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Simple GitOps ML Project
This repository provides a minimal setup for:
- A training script (`train.py`) that saves a model to `model/model.pkl`
- A FastAPI-based inference service (`app.py`)
- Kubernetes manifests for GitOps (`manifests/`)
- GitHub Actions CI/CD workflow in `.github/workflows/ci-cd.yml`
## Step-by-Step Usage
1. **Clone the repo**:
```bash
git clone https://github.com/kingabzpro/GitOps-Project.git
cd GitOps-Project
```
2. **Install dependencies**:
```bash
Copy code
pip install --upgrade pip
pip install -r requirements.txt
```
3. **Run the training script**:
```bash
python src/train.py
```
4. **Run the inference service**(optional test):
```bash
uvicorn src.app:app --reload --host 0.0.0.0 --port 80
```
5. **Build and run via Docker**:
```bash
docker build -t ml-service:latest .
docker run -p 80:80 ml-service:latest
```
6. **Deploy to Kubernetes**:
```bash
kubectl apply -f manifests/deployment.yaml
kubectl apply -f manifests/service.yaml
```
7. **GitOps**:
- If you're using a GitOps tool (Argo CD, Flux, etc.), point it to this repo (or a specific directory/branch).
- Any commit changes to the `manifests/` folder will be automatically picked up and deployed.