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Automate Machine Learning with H2O Driverless AI on Dell Infrastructure
Introduction Revision history The challenges of AI adoption Overview of AutoML and H2O Driverless AI Solution architecture for AutoML
Solution architecture for AutoML
Kubernetes-based deployment using Enterprise Steam
Docker image
Security
GPU support
Storage and network configuration
Licensing
Invoking H2O Driverless AI from cnvrg.io MLOps Platform AutoML on an optimized Dell infrastructure Sizing of AutoML infrastructure Validated use cases for AutoML Dell Technologies services and support The Dell Technologies Customer Solutions Center Conclusion References Appendix A – Model serving in cnvrg.io

Storage and network configuration

Storage and network configuration

  • H2O Driverless AI requires no special network considerations. The Kubernetes-based deployment uses ingress control and load balancers to govern access to the deployment.

    H2O Driverless AI uses persistent volumes to save the required data and to connect to external data sources such as NFS.