Cloud Deployment Best Practices
- Platform Parameter Specification: explicitly declared at startup
--platform cloudParameter Activation Cloud Adapter - Security Group Configuration: Ensure that gateway ports (default 8000-8100) and ports required for internal communications are open
Key Optimization Recommendations
- Automatic expansion and contraction: Configure elastic scheduling of CPU/GPU resources in conjunction with Kubernetes HPAs
- Hybrid Cloud Support: Local inference services can be connected to cloud-based big model APIs by modifying the url field of config.yaml
Monitoring & Operations
It is recommended that stability be ensured by
- Integration with Prometheus metrics interface (default path)
/metrics) - Execution on a regular basis
git pull origin mainGetting Security Patches - For memory-sensitive tasks add
@memory_limitdecorator
Special Note: Different cloud vendors such as AWS/GCP need to test the storage volume mounting performance separately, and SSD-type cloud drives are recommended.
This answer comes from the articleLazyLLM: Shangtang's open source low-code development tool for building multi-intelligence body applicationsThe
May not be reproduced without permission:AI productivity tools " What are the key points to keep in mind when deploying a LazyLLM application in a public cloud environment?
