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MLRun vs. Seldon: What's the difference?

Seldon is an MLOps solution but it is not a serverless technology. Users will need to provide Seldon with code, containers, YAMLs, etc. Then, Seldon can be used as a framework for launching them. It will build the entire service, including auto-scaling and APIs.

MLRun, on the other hand, orchestrates ML and MLOps end-to-end, including pipelines and serving capabilities. In addition, MLRun has metadata services for saving objects, like models, datasets, features, etc. When training, MLRun automatically builds a survey with the file and information about the data schema, statistics, for drift analysis, parameters, and more.

In other words, MLRun supports glueless integration with the serving layer and the monitoring layers without having to write a single line of code.

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