Dell Technologies has worked closely with cnvrg.io to deliver MLOps for AI/ML adopters through a jointly engineered and tested solution to help organizations capitalize on the benefits of MLOps for ML and AI workloads, as shown in the following figure:

Figure 4.   Overview of components of the Dell Validated Designs for AI: MLOps

The Optimize Machine Learning Through MLOps with Dell Technologies and cnvrg.io Design Guide provides guidance for architecting, deploying, and operating MLOps in the data center.

The design guide validates the cnvrg.io MLOps platform on two Kubernetes orchestration platforms:

• Dell Validated Design for AI provided by Virtualizing GPUs for AI with VMware and NVIDIA, which uses VMware vSphere with Tanzu for the Kubernetes layer and NVIDIA AI Enterprise software for additional applications, frameworks, and tools that researchers, data scientists, and developers can use to build ML models and analyze data
• Dell Validated Design for Analytics─Data Lakehouse, which uses Symworld Cloud Native Platform and open-source NVIDIA GPU operator

Powered with Dell PowerEdge servers for compute (with optional NVIDIA GPUs) and coupled with Dell PowerScale storage, the solution provides the analytics performance and concurrency at scale critical to consistently feeding the most data-hungry ML and AI algorithms.

Note: Additional Dell Validated Designs for container platforms can be used with similar results, but they have not been validated by Dell Technologies as of the publication of this white paper.