kubeflow
fashion-mnist-kfp-lab
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| kubeflow | fashion-mnist-kfp-lab | |
|---|---|---|
| 3 | 1 | |
| 13,634 | 0 | |
| 1.3% | - | |
| 8.5 | 0.0 | |
| 9 days ago | about 3 years ago | |
| TypeScript | Jupyter Notebook | |
| Apache License 2.0 | MIT License |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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
fashion-mnist-kfp-lab
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Machine Learning Orchestration on Kubernetes using Kubeflow
Let's try to learn Kubeflow with an example. In this demo, we will try Kubeflow on a local Kind cluster. You should have at least 16GB of RAM, 8 CPUs modern machine to try it on your local machine, otherwise use a VM in cloud. We will use Zalando's fashion MNIST dataset and this notebook by manceps for demo.
What are some alternatives?
kserve - Standardized Serverless ML Inference Platform on Kubernetes
fashion-mnist - A MNIST-like fashion product database. Benchmark :point_down:
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
pipelines - Machine Learning Pipelines for Kubeflow
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!
kfctl - kfctl is a CLI for deploying and managing Kubeflow
polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
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.
kube-manifests - A collection of misc Kubernetes configs for various jobs, as used in Bitnami's production clusters.