Worldwide revenues for the AI market are slated to surpass $300 billion in 2024, with a five-year compound annual growth rate (CAGR) of 17.1 percent, according to IDC. That’s the big AI picture. When you zero in, you see a parallel trend. Today, there is growing momentum for moving AI workloads to the edge, where data is captured, allowing for real-time feedback and decision-making.
Whether you’re addressing emerging problems on a fast-moving manufacturing line or keeping a self-driving car on a safe path, AI needs to take place at the point of action — at the edge. AI at the edge delivers powerful, real-time insights to organizations looking to drive actionable results at lower costs. With lower latency than cloud platforms, edge platforms are quickly becoming the go-to scalable infrastructure for organizations deploying time-sensitive AI applications.
That’s one side of the coin. On the flip side, there are challenges. It’s not necessarily easy to securely deploy, manage, and scale AI across distributed edge environments. In fact, this is an undertaking that can be both complex and challenging. And this is where NVIDIA Fleet Command comes into play.
Secure, Simple, Scalable Edge Management
NVIDIA Fleet Command is a hybrid-cloud platform for managing and scaling AI at the edge. It combines the benefits of edge computing with the ease of software-as-a-service. From a single Fleet Command control plane, anyone with a browser and Internet connection can deploy applications, update software over the air and monitor location health.
Fleet Command allows IT departments to securely and remotely manage large-scale fleets of deployed edge systems. Administrators can add or delete applications, update system software, and monitor the health of devices spread across vast distances — all from a single control plane.
NVIDIA Fleet Command has built-in, end-to-end security to help ensure that intellectual property including applications and sensor data are always protected. And this starts with the application. Applications are scanned for vulnerabilities and malware before they’re deployed. In addition, signed containers help ensure that only authenticated software is deployed to the edge.
At the location, all processed data is encrypted at rest, and the AI runtime is protected from tampering with a secure boot loader. And because all systems can be housed on premises, organizations have more control over where sensor data is stored.
A Powerful Engine to Drive it All
Dell Technologies offers a wide range of NVIDIA Certified Systems to drive NVIDIA Fleet Command and AI at the edge. These offerings include the Dell PowerEdge XE2420 edge server, engineered to deliver powerful performance for harsh environments with up to four NVIDIA T4 Tensor Core GPUs.
The PowerEdge XE2420 is a dual-socket, 2U, short-depth, front-accessible server that is ready to support a wide range of demanding edge applications, such as manufacturing logistics, 5G cell processing and streaming video analytics. Like other servers in the PowerEdge XE family, the PowerEdge XE2420 is purpose-built for complex, emerging workloads that require high performance and a large storage capacity.
Even better, every PowerEdge server is designed with a cyber-resilient architecture, with security integrated deeply into every phase in the server lifecycle, from design to retirement. And with the iDRAC9 Datacenter option, the PowerEdge XE2420 provides streaming telemetry capability with enhanced integrated security for emerging edge applications.
Moving forward with Trusted Partners
Dell Technologies and NVIDIA are focused on helping customers realize the value of their data with innovative AI solutions. Today, we’re ready to do the same for your organization with Dell PowerEdge servers with NVIDIA Fleet Command.
Our combined solutions portfolio and expertise help your organization reduce the risk, cost and complexity of IT projects by leveraging comprehensive solutions tailored to your business requirements. Working with your organization, we can help guide you through your AI and edge-computing journey to mitigate risk while decreasing the time to value — today and well into the future.
For a deeper dive into the capabilities of NVIDIA Fleet Command, read the data sheet.