Simplify IT at the Edge

Edge computing brings computation and data storage closer to where data is generated, enabling faster, more efficient processing. It reduces latency by processing data at or near the source—such as IoT devices, sensors, or branch locations—rather than relying solely on centralized cloud or data center infrastructure. For enterprises, this means quicker decision-making, lower bandwidth costs, and improved resilience. It's especially critical for use cases like real-time analytics, autonomous systems, retail personalization, and manufacturing automation. By handling data locally, edge computing also enhances privacy and supports operations in environments with limited connectivity.

Nutanix Cloud Infrastructure offers a compact, full-featured hyperconverged infrastructure solution that gives enterprises the flexibility they need to deploy and remotely manage any workload at the edge, including AI inference.

The main challenges enterprises face when deploying edge computing include management complexity, security vulnerabilities, limited physical space and environmental constraints, and a shortage of skilled personnel. Managing hundreds or thousands of distributed edge devices, each potentially running different applications and requiring updates, can be incredibly complex without centralized orchestration tools. The distributed nature of edge deployments also expands the attack surface, making securing these remote devices and their data a significant concern. Physical limitations, such as harsh environments, power constraints, and lack of dedicated IT staff at edge sites, necessitate robust and resilient hardware. Finally, finding IT professionals with the diverse skills needed to deploy, manage, and secure edge infrastructure is a persistent hurdle for many organizations.

Nutanix simplifies enterprise edge deployments with a combination of hyperconverged infrastructure(HCI) and full-featured, remote management that eliminates the need for on-site expertise. You can manage dozens or hundreds of edge sites using Nutanix Central and take full advantage of Nutanix Cloud Manager capabilities to ensure your edge deployments are secure, well governed, and cost-efficient.

Edge computing increases the attack surface, requiring robust, distributed security strategies.

Because edge nodes are geographically distributed and often deployed in less controlled environments, they are more vulnerable to physical tampering, unauthorized access, and network-based attacks. Enterprises must secure edge devices with measures like encryption, endpoint protection, and zero trust access controls. Regular patching and remote monitoring are also essential. Network segmentation and secure communication protocols help prevent breaches from spreading between edge and core systems. A well-defined security framework is crucial for safe edge deployment at scale.

Nutanix enhances security for edge deployments with a platform that is hardened by default, including zero trust access. Nutanix management tools simplify remote monitoring and simplify upgrades so it’s easier to keep systems up to date. Flow Network Security enables application-centric microsegmentation to contain breaches. Nutanix Data Lens detects anomalies, blocks access, and accelerates recovery from cyber attacks. In addition, Nutanix integrates with hundreds of security solutions from leading vendors for anti-malware, anti-virus, SIEM, threat detection, layer-7 network security, key management and more.

Containers simplify deploying, scaling, and managing applications at the edge by providing consistency, portability, and resource efficiency. They play a critical role in enabling lightweight, modular, and portable software deployments across distributed environments. Unlike traditional virtual machines, containers package applications and their dependencies into isolated units that can run consistently across diverse edge nodes—regardless of hardware or operating system differences. This makes them ideal for the constrained compute and storage resources typically found at the edge. Containers also support rapid deployment and updates, which is essential for maintaining edge applications across many locations. With tools like Kubernetes (and lightweight variants such as K3s or MicroK8s), enterprises can orchestrate thousands of containerized workloads at the edge, ensuring high availability, resilience, and remote management. This container-based approach brings cloud-native development practices to the edge, accelerating innovation while simplifying operations.

By allowing VMs and containers to run on the same hardware, Nutanix simplifies Kubernetes and container deployments at the edge. Nutanix Kubernetes Platform (NKP) provides advanced Kubernetes management capabilities that further simplify operation of containers in edge environments, including environments with limited connectivity.

Edge AI enhances enterprise operations by enabling real-time, local decision-making, reducing latency, and lowering dependence on cloud connectivity. Artificial intelligence models are run directly on edge systems rather than sending data back to centralized servers or the cloud for processing. This capability allows enterprises to analyze data and take action immediately at the source, which is critical for time-sensitive use cases like defect detection on production lines, fraud prevention at point-of-sale, or predictive maintenance in field equipment. By processing data locally, Edge AI reduces latency, minimizes bandwidth usage, and improves reliability—even in environments with intermittent connectivity. It also strengthens privacy and compliance by keeping sensitive data closer to its origin. In industries like manufacturing, retail, logistics, and healthcare, Edge AI enables faster insights, smarter automation, and more responsive customer and operational experiences.

Nutanix Cloud Infrastructure is the ideal platform for deploying AI inference capabilities at the edge. You can combine NCI with Nutanix Enterprise AI (NAI) to deploy LLMs and endpoints with secure APIs at the edge and run GenAI apps and agents with standardized inference.