mlflow-tracking-server
This repository hosts the code to make it easier to deploy a customizable and flexible MLflow tracking server solution to your Kubernetes cluster. (by wjayesh)
kubeflow-bootstrap
🪐 1-click Kubeflow using ArgoCD (by treebeardtech)
| mlflow-tracking-server | kubeflow-bootstrap | |
|---|---|---|
| 1 | 1 | |
| 1 | 20 | |
| - | - | |
| 0.0 | 9.3 | |
| almost 2 years ago | about 1 month ago | |
| Shell | Shell | |
| 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.
mlflow-tracking-server
Posts with mentions or reviews of mlflow-tracking-server.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Not just another MLflow on Kubernetes article
The code in this article is taken from my repository at GitHub. Feel free to experiment with it 🧪
kubeflow-bootstrap
Posts with mentions or reviews of kubeflow-bootstrap.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Show HN: Kubeflow's Missing Helm Chart
Kubeflow is an ML platform like Sagemaker or Databricks that you can self-host in a Kubernetes cluster.
Installing/deploying it is as complicated as it sounds, but we've put together an infrastructure project that lets you '1-click' install it even in tiny environments.
The GH repo (also linked in blog) allows you to start Kubeflow in a codespace or small device using a docker container -- this is both good for trying it out and developing it into your own internal ML platform.
https://github.com/treebeardtech/kubeflow-helm
What are some alternatives?
When comparing mlflow-tracking-server and kubeflow-bootstrap you can also consider the following projects:
mlflow-easyauth - Deploy MLflow with HTTP basic authentication using Docker