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Concurrent for MLflow is an Apache Licensed open source project for running MLflow projects, in parallel, in Kubernetes. It enhances MLflow with two important capabilities:

  • Effortlessly run MLflow Projects in Kubernetes, without the hassle of dealing with docker
  • Design a DAG of MLflow Projects and then execute the DAG in Kubernetes

Concurrent for MLflow is ideal for complex pre-processing of AI data and for batch/micro-batch inferencing. It is not suitable for distributed training or real time inferencing.

Simple MLflow Project Use Case

  • Wrap your AI code in MLflow projects and store in git
  • Run MLflow Project in Kubernetes

Sophisticated Parallelized DAG Use Case

  • Wrap your AI code in MLflow projects and store in git
  • Define a DAG of MLflow projects in Concurrent using the Concurrent Web UI
  • Run the DAG in Kubernetes