MLflow
MLflow is an open source MLOps framework that aims to be compatible with whatever other tools you might have. It has libraries in many popular languages and can be accessed via the REST API. MLflow has very few opinions and will not dictate anything related to your tech stack. You don’t even need to use the provided libraries; you could choose to use just REST API interactions. This allows teams to customize and pick whatever other tooling they wish. If you want a hosted MLflow, then you can use Databrick’s hosted MLflow.
MLOps benefits
There are many useful benefits to MLOps, and they often focus on features and models. MLOps tooling will often record the details of a series of experiments. This type of documentation can include metrics around model training and performance. MLOps tooling often stores your model and, in some cases, has mechanisms for users to interact with that model. Another useful area of MLOps is around features, which often need to be...
