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What is NVIDIA Run:ai?

NVIDIA Run:ai is a powerful enterprise platform engineered to revolutionize AI workload orchestration and GPU resource management across hybrid, multi-cloud, and on-premises infrastructures. It delivers intelligent orchestration that dynamically allocates GPU resources to maximize utilization, enabling organizations to run 20 times more workloads with up to 10 times higher GPU availability compared to traditional setups. Run:ai centralizes AI infrastructure management, offering end-to-end visibility, actionable insights, and policy-driven governance to align compute resources with business objectives effectively. Built on an API-first, open architecture, the platform integrates with all major AI frameworks, machine learning tools, and third-party solutions, allowing seamless deployment flexibility. The included NVIDIA KAI Scheduler, an open-source Kubernetes scheduler, empowers developers and small teams with flexible, YAML-driven workload management. Run:ai accelerates the AI lifecycle by simplifying transitions from development to training and deployment, reducing bottlenecks, and shortening time to market. It supports diverse environments, from on-premises data centers to public clouds, ensuring AI workloads run wherever needed without disruption. The platform is part of NVIDIA's broader AI ecosystem, including NVIDIA DGX Cloud and Mission Control, offering comprehensive infrastructure and operational intelligence. By dynamically orchestrating GPU resources, Run:ai helps enterprises minimize costs, maximize ROI, and accelerate AI innovation. Overall, it empowers data scientists, engineers, and IT teams to collaborate effectively on scalable AI initiatives with unmatched efficiency and control.

What is Rafay?

Enable both development and operations teams to harness the self-service tools and automation they desire while achieving a careful equilibrium of standardization and governance required by the organization. Utilize Git for centralized management and definition of configurations across clusters, incorporating essential elements such as security policies and software upgrades, which include service mesh, ingress controllers, monitoring, logging, and solutions for backup and recovery. The lifecycle management of blueprints and add-ons can be effortlessly executed for both new and existing clusters from a unified location. Furthermore, these blueprints can be distributed among different teams, promoting centralized control over the add-ons deployed throughout the organization. In fast-paced environments that necessitate swift development cycles, users can swiftly move from a Git push to an updated application on managed clusters within seconds, with the capability to execute this process more than 100 times a day. This method is particularly beneficial in development settings characterized by frequent changes, thereby promoting a more agile operational workflow. By optimizing these processes, organizations can greatly improve their efficiency and adaptability, resulting in a more responsive operational structure that can meet evolving demands. Ultimately, this enhances collaboration and fosters innovation across all teams within the organization.

Media

Media

Integrations Supported

Amazon EKS
Amazon Web Services (AWS)
Azure Kubernetes Service (AKS)
Cisco CX Cloud
Google Cloud Platform
Google Kubernetes Engine (GKE)
HPE Ezmeral
Kubernetes
Microsoft Azure
Rancher
VMware Tanzu

Integrations Supported

Amazon EKS
Amazon Web Services (AWS)
Azure Kubernetes Service (AKS)
Cisco CX Cloud
Google Cloud Platform
Google Kubernetes Engine (GKE)
HPE Ezmeral
Kubernetes
Microsoft Azure
Rancher
VMware Tanzu

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

www.nvidia.com/en-us/software/run-ai/

Company Facts

Organization Name

Rafay

Date Founded

2017

Company Location

United States

Company Website

rafay.co

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Virtualization

Archiving & Retention
Capacity Monitoring
Data Mobility
Desktop Virtualization
Disaster Recovery
Namespace Management
Performance Management
Version Control
Virtual Machine Monitoring

Categories and Features

Container Management

Access Control
Application Development
Automatic Scaling
Build Automation
Container Health Management
Container Storage
Deployment Automation
File Isolation
Hybrid Deployments
Network Isolation
Orchestration
Shared File Systems
Version Control
Virtualization

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