Any MLOps platform you use?

1. neptune-client

   1 26 592 8.9 Python

   📘 The experiment tracker for foundation model training

   

   Neptune.ai, which promises to streamline your workflows and make collaboration a breeze.

2. SaaSHub

   www.saashub.com featured

   SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

   

3. manifests

   2 8 845 9.1 YAML

   A repository for Kustomize manifests

   

   That said I personally use Kubeflow hosted on a local baremetal kubernetes cluster (8 nodes, 4 gpus), but a lot of it is a bit of a bear to get installed correctly in a multi-machine environment (specifically this issue is still open and exposing the built-in dashboards outside of the cluster is a problem). Also because it's a Google product it's very clearly intended to run in the cloud with self-hosting being very much an afterthought

4. polyaxon

   3 9 3,592 8.4 Python

   MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle

   

   If you're not concerned about self-hosting, WandB is one of the more fully featured training monitoring tools (I've used it in the past without any issues but the lack of data and training privacy and lack of self-hosting possibilities makes it a hard no for anything that isn't scholastic). Polyaxon is an alternative but rewriting all your variable logging to conform to their requirements makes it very difficult to switch to it in the middle of a project so you have to commit to it from the get-go.

5. MLflow

   4 71 19,220 9.9 Python

   Open source platform for the machine learning lifecycle

   

   I have an old labmate who uses a similar setup with MLFlow and can endorse it.

6. aim

   5 70 5,302 8.6 Python

   Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

   

   Check out Aim: https://github.com/aimhubio/aim

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