Edge Networking gets smarter: AI and 5G in action

Organizations everywhere are pushing AI and networks closer to the edge. With that expansion comes a challenge: how do you ensure reliable performance, efficiency, and security outside of the data center? Worker safety, healthcare automation, and the success of mobile private networks depend on a robust technology stack that can withstand real-world challenges and still deliver results. Canonical has partnered with Dell Technologies, Intel, Druid, Airspan and Ecrio to publish a new solution brief addressing this question. The brief highlights how a fully integrated, edge-ready platform can meet the growing demand for intelligent, secure, and real-time computing at the edge. 

The brief showcases how to build a strong foundation for edge AI and networking by using a Dell PowerEdge XR8000 ruggedized edge network+compute platform consisting of two server sleds powered by Intel Xeon Scalable processors. Both sleds are running Canonical’s software infrastructure stack, which combines Ubuntu, MicroCloud, and Canonical Kubernetes. On the first sled, MicroCloud hosts two VMs: Airspan Control Platform (ACP) manages the 5G radio units, and Druid Raemis provides the cloud-native 5G core orchestrated by Canonical Kubernetes. The second sled hosts Ecrio’s iota-e platform, also managed by Canonical Kubernetes, which enables AI-powered real-time image-recognition, voice, video, and messaging services. These capabilities support critical business processes such as worker coordination in industrial settings, emergency response in healthcare, and secure team communications in remote or hazardous environments.

Download the solution brief to learn how this integrated platform supports advanced use cases, including AI-driven safety monitoring, smart factory operations, and 5G connectivity at the edge.

In the solution brief, you’ll discover how to:

• Deploy AI and event detection workloads on optimized, securely designed infrastructure
• Operate private 5G and RAN control software on edge-virtualized environments
• Streamline orchestration and lifecycle management with Canonical Kubernetes and MicroCloud
• Detect safety and operational risks in real time using integrated AI inference

Download the full solution brief

For more information on how Canonical supports your edge and AI journey, visit our related content:

• Open source AI for the enterprise
  Discover how Canonical enables AI workloads from cloud to edge with tools for model training, trusted deployment, and lifecycle management. This webpage outlines Canonical’s full AI stack, from Ubuntu-optimized hardware acceleration to MLOps best practices, with links to blogs, whitepapers, and deployment guides.
• Canonical Telco solutions
  Learn how Canonical helps telecom operators modernize their infrastructure using open source technologies. This hub covers solutions for 5G core networks and Radio Access Networks (RAN) built on Ubuntu, Canonical Kubernetes, OpenStack, MAAS and Juju. You’ll find case studies and insights into telco-grade performance and security.