Operationalizing AI Fabrics with Aviz ONES, NVIDIA Spectrum-X, and Rafay
Discover the new AI operations model available to enterprises that enables self-service consumption and cloud-native orchestration for developers.
EVENT
DevOps Con 2023 - New York
Attending DevOpsCon this year? Don't miss out on Zero Trust or Bust: How to Secure Access to Kubernetes Infrastructure session by Mohan Atreya, Rafay's SVP of Products & Solutions!
About the Session:
As organizations increasingly rely on Kubernetes to run their business-critical applications, the ability to operate and secure clusters in a standardized way is essential but still remains a challenge—many platforms, DevOps and DevSecOps teams are burdened by an assortment of tooling or having to manually configure and manage Kubernetes role-based access control cluster by cluster.The solution? A zero trust security approach that can be enforced across multiple clusters in multiple locations, to be managed by teams of developers, operators, contractors, and partners who require varying levels of access when new difficulties arise with ever-changing enterprise policies and industry regulations.This session will cover how to reduce complexity and eliminate the risk of security breaches and loss in productivity by leveraging zero trust when securing Kubernetes. By attending, you will gain an understanding of:
- The core tenets of zero trust and how they can be applied to Kubernetes clusters
- Best practices for providing access control for fleet of clusters
- Approaches for single sign-on authorization and auditing for compliance purposes
- How a zero-trust approach will reduce the risk of security breaches
DevOpsCon 2023 will be a hybrid event that will be held from September 25 - 28 in New York and online with speakers across dozens of sessions and workshops to facilitate learning about the latest in continuous delivery, microservices, docker, cloud, lean business, SRE metrics, and more. Register Now!
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AI Factory FAQs
Learn how Rafay helps companies go from idle and expensive GPUs to building fully-scaled AI factories to accelerate AI and ML innovations.
Who uses AI factories?
AI factories are used by enterprises, cloud service providers, and sovereign AI clouds that need to scale AI workloads efficiently, maximize GPU utilization, and deliver AI as a production service rather than isolated projects. You can see how Rafay worked with Canadian telecommunications provider Telus in this case study.
What role does Rafay play in AI factories?
Rafay provides the control plane for AI factories, handling orchestration, multi-tenancy, governance, and self-service access to AI infrastructure across cloud, on-prem, and sovereign environments.
Is Rafay an AI factory?
Rafay is not a GPU manufacturer or model provider. Rafay provides an infrastructure orchestration and consumption platform that enables organizations to operate AI factories by turning AI infrastructure into a governed, self-service platform.
Does Rafay support NVIDIA NIMs/NIM?
Yes, Rafay supports NVIDIA NIM (NVIDIA Inference Microservices). NIM is NVIDIA’s proprietary solution for delivering packaged inferencing capabilities. It comes pre-configured with NVIDIA’s in-house models and has been optimized for use with a wide range of open-source models, including Meta’s Llama variants. While NIM is often viewed as an alternative to the open-source kServe package, Rafay’s platform supports both NIM and kServe. This flexibility allows customers to choose their preferred inference endpoint and deploy it effortlessly on GPU instances using the Rafay platform. By supporting multiple inferencing solutions, Rafay enables organizations to leverage the most suitable tools for their specific AI/ML needs while maintaining a consistent and manageable infrastructure.
How is Rafay different from Run.AI?
Run:AI focuses on providing fractional/virtualized GPU consumption and a proprietary scheduler optimized for AI/GenAI workloads, replacing the default Kubernetes scheduler. Rafay, however, provides a more comprehensive platform that manages the full lifecycle of underlying Kubernetes clusters and environments. Rafay offers an out-of-the-box experience to deploy and consume Run:AI on Rafay’s GPU PaaS, while also providing its own GPU virtualization and AI-friendly Kubernetes scheduler for customers preferring a single-vendor solution. Essentially, Rafay can either complement Run:AI’s offerings or provide a standalone solution that covers similar functionalities along with broader infrastructure management capabilities, giving customers flexibility in their AI infrastructure choices.
Does Rafay offer a GPU PaaS?
Yes, Rafay provides infrastructure orchestration and workflow automation for cloud-native (Kubernetes) and AI use cases for enterprises, cloud providers, neoclouds, and Sovereign AI clouds. Rafay helps companies deploy a Platform-as-a-Service (PaaS) experience that supports both CPU-only and GPU-accelerated compute environments. Platform teams can quickly set up and deliver customized self-service experiences for developers and data scientists, typically within days or weeks. This flexible platform allows end-users to easily access the computational resources they need, whether it’s standard CPU processing or more powerful GPU capabilities. Rafay’s solution streamlines the deployment and management of diverse computing environments, making it easier for organizations to support a wide range of applications, from standard software to complex AI/ML projects.
