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Average Ratings 0 Ratings
Description
Empower both developers and operations teams with the self-service capabilities and automation they crave, while maintaining an optimal balance of standardization and governance that the organization necessitates. Manage and define configurations centrally using Git for clusters that include security policies and software enhancements like service mesh, ingress controllers, monitoring, logging, and backup and recovery solutions. The management of blueprints and the lifecycle of add-ons can be seamlessly implemented for both new and existing clusters from a central point. Additionally, blueprints can be shared among various teams, ensuring centralized oversight of the add-ons utilized throughout the organization. In dynamic environments that demand rapid development cycles, users can transition from a Git push to an updated application on managed clusters in mere seconds, achieving this over 100 times daily. This approach is especially advantageous for development settings where changes are made with high frequency, thus fostering a more agile workflow. By streamlining these processes, organizations can significantly enhance their operational efficiency and responsiveness.
Description
NVIDIA Run:ai is a cutting-edge platform that streamlines AI workload orchestration and GPU resource management to accelerate AI development and deployment at scale. It dynamically pools GPU resources across hybrid clouds, private data centers, and public clouds to optimize compute efficiency and workload capacity. The solution offers unified AI infrastructure management with centralized control and policy-driven governance, enabling enterprises to maximize GPU utilization while reducing operational costs. Designed with an API-first architecture, Run:ai integrates seamlessly with popular AI frameworks and tools, providing flexible deployment options from on-premises to multi-cloud environments. Its open-source KAI Scheduler offers developers simple and flexible Kubernetes scheduling capabilities. Customers benefit from accelerated AI training and inference with reduced bottlenecks, leading to faster innovation cycles. Run:ai is trusted by organizations seeking to scale AI initiatives efficiently while maintaining full visibility and control. This platform empowers teams to transform resource management into a strategic advantage with zero manual effort.
API Access
Has API
API Access
Has API
Integrations
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
Integrations
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
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Rafay
Founded
2017
Country
United States
Website
rafay.co
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
www.nvidia.com/en-us/software/run-ai/
Product 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
Product 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