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- `--workers, -w`: Number of worker processes. Use `-1` to auto-calculate based on CPU cores (recommended for production)
- `--worker-connections`: Maximum simultaneous clients per worker process (default: 1000)
- `--max-requests`: Maximum requests before worker restart, prevents memory leaks (default: 1000)
- `--max-requests-jitter`: Jitter to prevent thundering herd on worker restart (default: 50)
- `--registry_ttl_sec, -r`: Registry refresh interval in seconds. Higher values reduce overhead but increase staleness (default: 60)
- `--keep-alive-timeout`: Keep-alive connection timeout in seconds (default: 30)
### Performance Best Practices
**Worker Configuration:**
- For production: Use `--workers -1` to auto-calculate optimal worker count (2 × CPU cores + 1)
- For development: Use default single worker (`--workers 1`)
- Monitor CPU and memory usage to tune worker count manually if needed
**Registry TTL:**
- Production: Use `--registry_ttl_sec 60` or higher to reduce refresh overhead
- Development: Use lower values (5-10s) for faster iteration when schemas change frequently
- Balance between performance (higher TTL) and freshness (lower TTL)
**Connection Tuning:**
- Increase `--worker-connections` for high-concurrency workloads
- Use `--max-requests` to prevent memory leaks in long-running deployments
- Adjust `--keep-alive-timeout` based on client connection patterns
**Container Deployments:**
- Set appropriate CPU/memory limits in Kubernetes to match worker configuration
- Use HTTP health checks instead of TCP for better application-level monitoring
- Consider horizontal pod autoscaling based on request latency metrics
## Deploying as a service
See [this](../../how-to-guides/running-feast-in-production.md#id-4.2.-deploy-feast-feature-servers-on-kubernetes) for an example on how to run Feast on Kubernetes using the Operator.
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feat: Optimize container infrastructure for production #5881
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feat: Optimize container infrastructure for production #5881
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