As applications and workplaces become more complex, an organization must deploy modern server architectures that offer modular components. This allows for future extensibility, easier adoptions of future technologies, and more innovative designs to address customer needs.
In this case study, Dell Technologies PowerEdge MX has been deployed as the composable server hardware infrastructure. It enables customers to break free from the bounds of technology silos and time-consuming, routine operational management while also dynamically assigning IT to optimally match different applications and needs such as VMware Cloud Foundation 4.0.
VMware, the largest HCI (Hyper-Converged) software vendor globally, delivered expertise and advice in deploying VMWare Cloud Foundation 4. Including the latest innovations in vSAN, NSX, and vSphere 7 with Tanzu. By establishing vSphere 7 as a consolidated container and integrating VMs into a single stack with development tools, developers at Grid Dynamics and operators within the Dell Technologies server labs could collaborate in real-time to develop a machine learning framework demonstrated full functionality on two retail use cases.
Grid Dynamics, an engineering services firm, has been commissioned during this project to develop custom machine learning code to operate and demo these technologies based on two common retail customer scenarios. The first scenario is price prediction for marketing (XGBoost), and the second use case is based on visual classification application (TensorFlow).
The PowerEdge MX modular hardware coupled with VCF utilizing vSphere with Tanzu forms the foundation for innovation within this SDDC machine learning container deployment. Our goal is to demonstrate how these readily available standard hardware and software stacks can be commonly used to enable a secure and robust platform of innovation for machine learning.