setup-minikube
kubeflow
| setup-minikube | kubeflow | |
|---|---|---|
| 1 | 3 | |
| 90 | 13,735 | |
| - | 1.1% | |
| 9.4 | 8.3 | |
| 5 days ago | 7 days ago | |
| TypeScript | TypeScript | |
| MIT License | Apache License 2.0 |
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setup-minikube
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Preloadiing images to minikube cluster
I'm guessing your using this github action https://github.com/medyagh/setup-minikube
kubeflow
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Is it possible to store the username in a config file inside the jupyter notebook spawned by kubeflow?
I'm not 100% sure this will work but sounds like PodDefault is what you need.
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Machine Learning Orchestration on Kubernetes using Kubeflow
If you are looking for bringing agility, improved management with enterprise-grade features such as RBAC, multi-tenancy and isolation, security, auditability, collaboration for the machine learning operations in your organization, Kubeflow is an excellent option. It is stable, mature and curated with best-in-class tools and framework which can be deployed in any Kubernetes distribution. See Kubeflow roadmap here to look into what's coming in the next version.
- Jupyter notebooks in kubeflow
What are some alternatives?
up-to-date-react-template - ♻ An Always up-to-date React template with Typescript, Jest, Prettier, Github Actions and Renovate
kserve - Standardized Serverless ML Inference Platform on Kubernetes
jira-ci-cd-integration - Jira Integation for sending Build/Deploy information. Use with any CI/CD provider (via Docker)
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
fashion-mnist - A MNIST-like fashion product database. Benchmark :point_down:
pipelines - Machine Learning Pipelines for Kubeflow
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
kfctl - kfctl is a CLI for deploying and managing Kubeflow
kube-manifests - A collection of misc Kubernetes configs for various jobs, as used in Bitnami's production clusters.
mpi-operator - Kubernetes Operator for MPI-based applications (distributed training, HPC, etc.)