One-click deployment configurations for popular cloud platforms.

# Install flyctl and deploy curl -L https://fly.io/install.sh | sh fly deploy

# Local development docker-compose up # Production with Nginx docker-compose --profile production up

1. Click the "Deploy on Railway" button above
2. Connect your GitHub account
3. Fork this repository
4. Railway will automatically build and deploy
5. Your Shimmy instance will be available at https://your-app.railway.app

1. Click the "Deploy to Render" button above
2. Connect your GitHub repository
3. Render will use the render.yaml configuration
4. Your service will be available with automatic HTTPS

1. Install the Fly CLI: curl -L https://fly.io/install.sh | sh
2. Clone this repository: git clone https://github.com/Michael-A-Kuykendall/shimmy.git
3. Navigate to the project: cd shimmy
4. Create and deploy: fly deploy
5. Access your app: fly open

# Build and deploy to Cloud Run gcloud builds submit --tag gcr.io/PROJECT-ID/shimmy gcloud run deploy --image gcr.io/PROJECT-ID/shimmy --platform managed

1. Create apprunner.yaml in your repository root:

version: 1.0 runtime: docker build: commands: build: - echo "Building Shimmy with Docker" run: runtime-version: latest command: shimmy serve --bind 0.0.0.0:8080 network: port: 8080

1. Create app via DigitalOcean control panel
2. Connect your GitHub repository
3. DigitalOcean will detect the Dockerfile automatically
4. Set environment variables as needed

• CPU: 0.5 vCPU
• Memory: 512MB RAM
• Storage: 100MB (binary only)

• CPU: 1 vCPU
• Memory: 1GB RAM
• Storage: 1GB+ (for model caching)

• CPU: 2+ vCPU
• Memory: 4GB+ RAM
• Storage: 10GB+ SSD

1. Authentication: Shimmy doesn't include built-in authentication. Use a reverse proxy (Nginx, Cloudflare) for auth.

2. Rate Limiting: The included Nginx configuration has basic rate limiting. Adjust as needed.

3. HTTPS: Most cloud platforms provide automatic HTTPS. For self-hosted deployments, configure SSL certificates.

4. Firewall: Only expose port 11434 (or your configured port) to the public internet.

All configurations include health checks at /health endpoint.

Set RUST_LOG=debug for detailed logging. Most platforms provide log aggregation.

For production deployments, consider adding:

• Prometheus metrics
• Jaeger tracing
• Custom monitoring dashboards

Shimmy is stateless and can be horizontally scaled. Use a load balancer to distribute requests.

For better performance with large models:

• Increase memory for model caching
• Add more CPU cores for parallel processing
• Use SSD storage for faster model loading

1. Out of Memory: Increase memory allocation or use memory-mapped loading
2. Slow Startup: Enable model caching and use persistent storage
3. Connection Timeout: Increase proxy timeout settings for large model inference

# Enable debug logging RUST_LOG=debug shimmy serve

# Access running container docker exec -it shimmy-container /bin/bash # Check logs docker logs shimmy-container