machine-learning-using-k8s
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Add more advanced use cases
Kubeflow community is growing fast. This repository covers basic tutorial for users. I think strategy for next step is to
- bring different phases of machine learning into picture like data loading, model management and experiment, A/B testing.
- integrate with existing AWS services and simplify user's setup.
Action items could be
- Integration with EKS component, like how to easily setup PV using CSI Plugin, Ingress Controller.
- Integration with AWS services, like JupyterHub authentication, logs backend.
- Integrated E2E production ready solution. Multi-tenancy support, Traffic management(Istio), metrics and log solution, CI/CD.
Once these things done, we can contribute back to community.
@Jeffwan thanks for the great input. I think each of these usecases would be super relevant and important. Do you want to send PRs for them?
@arun-gupta I will send you a document to review later next week on provision simplification.