feat: Optimize container infrastructure for production by franciscojavierarceo · Pull Request #5881 · feast-dev/feast
- Add multi-worker configuration with auto-scaling (CPU * 2 + 1) - Add worker connections, max-requests, and jitter parameters - Optimize registry TTL from 2s/5s to 60s for reduced refresh overhead - Support --workers=-1 for automatic worker count calculation - Add worker recycling to prevent memory leaks Expected Impact: - 300-500% throughput increase with proper worker scaling - Reduced registry refresh overhead - Better resource utilization in containerized environments Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com>
- Document new worker configuration options (--workers, --worker-connections, etc.) - Add performance best practices for production deployments - Include guidance on registry TTL tuning and container deployments - Provide examples for development vs production configurations Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com>
YassinNouh21 pushed a commit to YassinNouh21/feast that referenced this pull request
* feat: optimize container infrastructure for production - Add multi-worker configuration with auto-scaling (CPU * 2 + 1) - Add worker connections, max-requests, and jitter parameters - Optimize registry TTL from 2s/5s to 60s for reduced refresh overhead - Support --workers=-1 for automatic worker count calculation - Add worker recycling to prevent memory leaks Expected Impact: - 300-500% throughput increase with proper worker scaling - Reduced registry refresh overhead - Better resource utilization in containerized environments Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * style: fix ruff formatting in serve.py Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * docs: add performance configuration documentation - Document new worker configuration options (--workers, --worker-connections, etc.) - Add performance best practices for production deployments - Include guidance on registry TTL tuning and container deployments - Provide examples for development vs production configurations Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * Apply suggestion from @franciscojavierarceo --------- Co-authored-by: Claude Sonnet 4 <noreply@anthropic.com> Signed-off-by: yassinnouh21 <yassinnouh21@gmail.com>
YassinNouh21 pushed a commit to YassinNouh21/feast that referenced this pull request
* feat: optimize container infrastructure for production - Add multi-worker configuration with auto-scaling (CPU * 2 + 1) - Add worker connections, max-requests, and jitter parameters - Optimize registry TTL from 2s/5s to 60s for reduced refresh overhead - Support --workers=-1 for automatic worker count calculation - Add worker recycling to prevent memory leaks Expected Impact: - 300-500% throughput increase with proper worker scaling - Reduced registry refresh overhead - Better resource utilization in containerized environments Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * style: fix ruff formatting in serve.py Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * docs: add performance configuration documentation - Document new worker configuration options (--workers, --worker-connections, etc.) - Add performance best practices for production deployments - Include guidance on registry TTL tuning and container deployments - Provide examples for development vs production configurations Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * Apply suggestion from @franciscojavierarceo --------- Co-authored-by: Claude Sonnet 4 <noreply@anthropic.com> Signed-off-by: yassinnouh21 <yassinnouh21@gmail.com>
jyejare pushed a commit to opendatahub-io/feast that referenced this pull request
* feat: optimize container infrastructure for production - Add multi-worker configuration with auto-scaling (CPU * 2 + 1) - Add worker connections, max-requests, and jitter parameters - Optimize registry TTL from 2s/5s to 60s for reduced refresh overhead - Support --workers=-1 for automatic worker count calculation - Add worker recycling to prevent memory leaks Expected Impact: - 300-500% throughput increase with proper worker scaling - Reduced registry refresh overhead - Better resource utilization in containerized environments Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * style: fix ruff formatting in serve.py Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * docs: add performance configuration documentation - Document new worker configuration options (--workers, --worker-connections, etc.) - Add performance best practices for production deployments - Include guidance on registry TTL tuning and container deployments - Provide examples for development vs production configurations Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com> * Apply suggestion from @franciscojavierarceo --------- Co-authored-by: Claude Sonnet 4 <noreply@anthropic.com>
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