While AI workloads are becoming more pervasive, challenges with deploying AI have slowed adoption. Blockers like data complexity, data silos, and lack of infrastructure contribute to the difficulty of deploying AI workloads, and to address these issues, organizations need an integrated, scalable, and high-performing solution.

VMware Tanzu Kubernetes Grid, is a multi-cloud Kubernetes footprint that you can run both on-premises in VMware vSphere and in the public cloud on Amazon EC2 and Microsoft Azure. As part of VMware’s dedication to providing an enterprise-class, multi-cloud Kubernetes distribution, we are excited to announce one of the most requested Tanzu Kubernetes Grid features of all time—GPU support for Tanzu Kubernetes Grid, supported in vSphere, Amazon Web Services (AWS), and Azure environments.

VMware is announcing Tanzu Kubernetes Grid Service support for GPUs on vSphere with Tanzu, enabling customers to integrate AI into their containerized workloads. Additionally, VMware is announcing Tanzu Kubernetes Grid support for GPUs on AWS and Azure, bringing multi-cloud capabilities to customers for GPU support in public cloud, for increased flexibility and scalability. This allows enterprises to avoid AI silos and simplify management by leveraging virtualization to fold-in AI deployments into existing enterprise infrastructure, accelerating AI adoption in the enterprise.

NVIDIA AI Enterprise on vSphere with Tanzu

In March 2021, VMware and NVIDIA teamed up to provide an end-to-end, AI-ready enterprise platform that’s easy to deploy and operate. This joint platform includes the NVIDIA AI Enterprise software suite, which has been certified, optimized, and supported by NVIDIA for VMware vSphere. VMware is now announcing that Tanzu Kubernetes Grid service, included in VMware vSphere with Tanzu, now supports GPUs, enabling customers to automate the delivery of containerized workloads, and proactively manage apps in production.

Customers can now trial their AI projects on NVIDIA AI Enterprise with vSphere with Tanzu. IT operations teams can use their existing vSphere environment to deliver Kubernetes clusters to AI developer teams at a rapid pace, while still enabling enterprise-class governance, reliability, and security. NVIDIA plans to provide full certification, optimization, and support of Tanzu with vSphere in a future release of NVIDIA AI Enterprise.

VMware vSphere transforms bare-metal servers (including CPU- and GPU-based resources) into centrally managed AI and machine learning infrastructure pools that can quickly provision virtual machines and containers on demand. This integration simplifies the development and deployment of container-based AI applications with leading AI frameworks and tools from NVIDIA, to run at scale in your data center.

Tanzu Kubernetes Grid support for GPU on AWS and Azure

VMware strives to achieve a consistent performant modern apps platform that can run anywhere. With Tanzu Kubernetes Grid 1.4, we are announcing support of GPU instances available from AWS and Azure.

Developers can now create and manage the lifecycle of GPU-enabled clusters in Tanzu Kubernetes Grid for AWS and Azure. Cluster API, the upstream technology we use for cluster lifecycle management, supports GPU instance types for AWS and Azure. This solution is tested and validated by VMware, and VMware provides support for customers (see documentation for deploying a GPU-enabled cluster on Amazon EC2 and for deploying a GPU-enabled cluster on Azure).

Learn more at VMworld

To find out more about Tanzu Kubernetes Grid support for GPUs, attend VMworld session Tanzu and NVIDIA AI deliver AI-Ready Enterprise Platform [APP2170]. See the full session catalog for more interesting sessions on VMware Tanzu. In the meantime, learn more about Tanzu Kubernetes Grid, vSphere with Tanzu, and stay tuned for more information about NVIDIA AI Enterprise Suite.