In this article, we explore the tools and process for (1) training a machine learning model on a given dataset using the H2O Driverless AI (DAI) tool, and (2) deploying a trained model, as part of a scoring pipeline, to a REST server for use by business applications. All of the infrastructure requirements for this Read more...
In part 1 we introduced the solution and its deployment. In part 2 we will look at the validation of the solution and the results. Testing Methodology: The goal of the testing is to validate the vSphere platform for running Caffe2 and PyTorch. Some of the capabilities such as sharing GPUs between containers was Read more...
Introduction Kubernetes is a popular platform to deploy modern applications. In an earlier blog we look at how Tensorflow can be leveraged in the vSphere platform for common ML use cases. In this series we will look at running Caffe2 and PyTorch which are popular open source ML platforms. This solution focused on validating Caffe2 Read more...
In part 1 of the blog series we looked at the challenges of running Kubernetes and how VMware Enterprise PKS can help alleviate them. In this part, we will look at the deployment of the solution with MongoDB Enterprise Operator on VMware Enterprise PKS and its validation. Virtual Infrastructure Components: The virtual infrastructure used Read more...
Introduction: Kubernetes is a popular platform to deploy modern applications. MongoDB is a commonly used database for these cloud native applications. There is an ongoing need to deploy and use MongoDB with Kubernetes in Enterprise scale production environments. VMware provides an enterprise class Kubernetes platform in the form of VMware Enterprise PKS. MongoDB Enterprise is Read more...
