mpi-operator
Kubernetes Operator for MPI-based applications (distributed training, HPC, etc.) (by kubeflow)
kubeflow
Machine Learning Toolkit for Kubernetes (by kubeflow)
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| mpi-operator | kubeflow | |
|---|---|---|
| 1 | 3 | |
| 396 | 13,658 | |
| 2.0% | 1.5% | |
| 7.3 | 8.5 | |
| 7 days ago | 6 days ago | |
| Go | TypeScript | |
| Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
mpi-operator
Posts with mentions or reviews of mpi-operator.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-01-25.
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Scaling Kubernetes to 7,500 Nodes
Hi, kube-scheduler maintainer here, currently looking into enabling MPI use cases in k8s.
We started a discussion in https://github.com/kubeflow/mpi-operator/issues/315
kubeflow
Posts with mentions or reviews of kubeflow.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-03-23.
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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?
When comparing mpi-operator and kubeflow you can also consider the following projects:
kube-batch - A batch scheduler of kubernetes for high performance workload, e.g. AI/ML, BigData, HPC
kserve - Standardized Serverless ML Inference Platform on Kubernetes