In today’s rapidly evolving digital landscape, staying ahead requires organizations to embark on infrastructure modernization initiatives. A new wave of AI-enabled applications is poised to significantly boost worker productivity and speed up economic development on a global scale, just as the mobile-app revolution transformed businesses and technology over the years. We are at the beginning of a new innovation cycle, and this effort is not without challenges. The goal is to make this powerful and emerging technology more affordable, accessible, and reliable. But managing diverse technologies, overcoming human resistance to change, and ensuring profitability can pose demanding obstacles for any successful IT strategy.
In conjunction with our announcement of the initial availability of VMware Private AI Foundation with NVIDIA, we’re excited to announce a new Private AI Automation Services capability, powered by VMware Aria Automation. With Private AI Automation Services, built in as an integrated part of VMware Cloud Foundation, customers can automate private AI service setup and provisioning of GPU-enabled machines for ML workloads.
There is a growing need from enterprises for AI solutions but these solutions can be difficult and time-consuming to deliver. To address this need, a new out-of-the-box integration with VMware Private AI Foundation with NVIDIA will enable organizations to deliver automation capabilities for VMware Cloud Foundation. The integration will come with the new Catalog Setup Wizard, which will provide a quick start experience, automated setup of private AI services, and self-service provisioning of GPU-capable machines, including Machine Learning (ML) workloads and TKG GPU enabled Kubernetes clusters.
VMware Cloud Foundation (VCF) is a full stack private cloud infrastructure solution that delivers a comprehensive, secure and scalable platform for building and operating Generative AI workloads, providing organizations with agility, flexibility, and scalability to meet their evolving business needs. With VMware Cloud Foundation , IT admins can apply governance and control of expensive and high demand resources, such as GPUs, through consumption policies, templates, and user roles. This means that project members can use the infrastructure services required for their AI/ML projects more efficiently, while IT admins enforce resources to be used more optimally and securely. Time to deployment for AI infrastructure will be shortened using supervisor VM and TKG services within a supervisor namespace, and provisioned via the Cloud Consumption Interface. The Cloud Consumption Interface is now available on-premises for VMware Cloud Foundation customers through Aria Automation, enabling them to leverage the benefits of VMware Private AI Foundation with NVIDIA without having to worry about infrastructure management. In addition, Cloud Consumption Interface offers a simple and secure self-service consumption of all Kubernetes-based, desired state Infrastructure as a Service (IaaS) APIs that are available in the vSphere platform. This allows enterprises to easily implement a DevOps experience and develop applications with more agility, flexibility, and modern techniques on vSphere while maintaining control of their infrastructure.
VMware Cloud Foundation helps customers integrate the flexibility and control necessary to power a new generation of AI-enabled applications, which greatly enhances worker productivity, drives transformation across major business functions, and has a significant economic impact.
VMware Private AI environments serve as an excellent base for the new class of AI-powered applications by making it easier to harness private yet highly distributed data. Moreover, private AI automation services capabilities will provide a faster time-to-market by enabling quicker iteration of AI/ML infrastructure changes governed through templates. It will also offer ease of use by reducing the time taken to access GPU-enabled development environments through self-service catalogs. Additionally, it will provide developers and DevOps teams with a Kubernetes-aligned (desired state) approach to managing Day 2 changes to deployments. Finally, it will help to lower expensive GPU resource costs via improved governance and capacity utilization of AI/ML infrastructure, with policy and governance built right into self-service options.
Private AI is gaining popularity because it meets businesses’ emerging needs to utilize AI while adhering to strict data governance and privacy standards. Open AI models may pose potential risks such as privacy concerns, making organizations increasingly cautious. Private AI offers a compelling alternative by enabling enterprises to run AI models near the data source, enhancing security and compliance. VMware Private AI paves the way for a new paradigm where AI’s transformative potential is realized without compromising the privacy of customer and proprietary enterprise data. This cost-effective solution will become more crucial in 2024 as organizations navigate growing regulatory hurdles.
Private AI Automation Services is expected to be generally available in Broadcom’s fiscal second quarter.
: Infrastructure Automation, Q1 2023 Report
