NVIDIA Fleet Command, a cloud-based service for deploying, managing, and scaling edge AI applications, now includes features that improve the seamless management of edge AI deployments worldwide.
With the scale of AI deployments at the edge, organizations can have up to thousands of independent edge locations that need to be managed by IT teams – sometimes in remote locations like oil rigs, gauges weather, distributed retail stores or industrial facilities.
NVIDIA Fleet Command offers a simple, managed platform for container orchestration that makes it easy to provision and deploy applications and AI systems across thousands of distributed environments, all from a single console cloud-based.
But deployment is only the first step in managing AI applications at the edge. Optimizing these applications is an ongoing process that involves applying patches, deploying new applications, and rebooting peripheral systems.
To make these workflows seamless in a managed environment, Fleet Command now offers advanced remote management, multi-instance GPU provisioning, and additional integrations with industry collaborator tools.
Advanced remote management
IT administrators can now access systems and applications with sophisticated security features. Remote management on Fleet Command provides access controls and timed sessions, eliminating vulnerabilities associated with traditional VPN connections. Administrators can securely monitor activity and troubleshoot issues at remote sites from the comfort of their office.
Edge environments are extremely dynamic, which means administrators responsible for AI Edge deployments must be very agile to keep up with rapid changes and ensure minimal deployment downtime. This makes remote management an essential feature for every edge AI deployment.
See a comprehensive overview of new remote management features and how they can be used to help administrators maintain and optimize even the largest edge deployments.
Multi-Instance GPU Provisioning
Multi-Instance GPU, or MIG, partitions an NVIDIA GPU into multiple independent instances. MIG is now available on Fleet Command, allowing administrators to easily assign applications to each instance from the Fleet Command UI. By enabling organizations to run multiple AI applications on the same GPU, MIG enables organizations to right-size their deployments and get the most out of their edge infrastructure.
Learn how administrators can use MIG in Fleet Command to better optimize edge resources to easily scale new workloads.
Working together to develop AI
Fleet Command’s new collaborations also help companies create a seamless workflow from development to deployment to the edge.
Domino Data Lab provides an enterprise MLOps platform that enables data scientists to collaboratively develop, deploy and monitor AI models at scale using their favorite tools, languages and frameworks. The Domino platform’s integration with Fleet Command gives data science and IT teams a single system of record and a consistent workflow with which to manage models deployed in edge locations.
Milestone Systems, a leading provider of video management systems and elite partner of NVIDIA Metropolis, has created AI Bridge, an application programming interface gateway that allows AI applications to easily access consolidated video feeds from dozens of camera feeds. Now integrated with Fleet Command, Milestone AI Bridge can be easily deployed to any edge location.
IronYun, an elite partner of NVIDIA Metropolis and a premier member of the NVIDIA Partner Network, with its Vaidio AI platform, applies advanced artificial intelligence, evolved over generations, to security, safety and operational applications in the whole world. Vaidio is an open platform that works with any IP camera and immediately integrates with dozens of market-leading video management systems. Vaidio can be deployed on-premises, in the cloud, at the edge, and in hybrid environments. Vaidio goes from one to thousands of cameras. Fleet Command makes it easy to deploy Vaidio AI at the edge and simplify management at scale.
With these new features and expanded collaborations, Fleet Command ensures that the daily process of maintaining, monitoring and optimizing edge deployments is simple and painless.
Test Drive Fleet Command
To try these features on Fleet Command, check out the free NVIDIA LaunchPad.
LaunchPad provides immediate, short-term access to an instance of Fleet Command to easily deploy and monitor real applications on real servers using hands-on labs that walk users through the process, provisioning, and deployment. infrastructure optimization to application deployment for use cases such as vision deployment. AI at the edge of a network.