As organizations continue to push data processing to the edge, Gartner® predicts that by 2025, more than 50% of enterprise-managed data will be created and processed outside traditional data centers or the cloud. With the increasing adoption of edge computing and the rise of artificial intelligence (AI) workloads, there is a growing demand for agile, connected, and secure systems that can efficiently deploy and manage AI models across multiple edge locations.
Dell Technologies is addressing this need with advancements in its Dell NativeEdge software, part of its broader Dell AI Factory capabilities. These advancements are designed to provide organizations with AI software integrations and high-availability (HA) features that ensure resilient and reliable deployment and management of AI workloads at the edge. By offering high-availability capabilities, NativeEdge ensures that critical business processes and edge AI applications remain operational even in the event of network disruptions or device failures. With features such as virtual machine migration and automatic failover for applications, compute, and storage, businesses can maintain continuous operations and reduce downtime.
One of the key strengths of Dell NativeEdge is its ability to simplify the management of edge AI workloads across a wide range of environments, from retail stores to utility companies. By enabling easy clustering of NativeEdge Endpoints—such as Dell PowerEdge servers, OptiPlex and Precision workstations, and Dell Gateways—NativeEdge software allows these devices to operate as a unified system, ensuring seamless and highly available operations. Additionally, it supports integration with external storage solutions like Dell PowerStore and Dell PowerVault, offering flexible storage solutions that can scale as needed to support AI model training and deployment at the edge.
Dell NativeEdge also offers pre-built Blueprints that streamline the deployment of AI applications and solutions. These Blueprints automate the setup of AI applications across hundreds or even thousands of edge locations, significantly reducing manual configuration efforts and minimizing errors. With more than 55 pre-built Blueprints available, businesses can quickly deploy AI workloads, improving their time to value. These Blueprints support various AI frameworks and applications, ensuring that organizations can implement AI inferencing at the edge with minimal complexity.
The expansion of the NativeEdge Blueprint catalog includes additional open-source tools like Apache Spark™, Apache Airflow®, and MLflow, enabling organizations to implement continuous machine learning operations (MLOps) workflows at the edge. Furthermore, tools such as Aveva Unified Operations Center for smart city infrastructure modernization, EPIC iO for enhancing the in-store shopper experience, and Dell Data Collector for real-time data transfer from IoT devices are now part of the catalog, offering even more solutions for edge AI deployments. Additionally, the catalog includes the Intel® Geti™ software solution for computer vision AI models and updates to the NVIDIA AI Enterprise software platform, which includes microservices for more efficient and secure AI deployment.
Dell Services for NativeEdge Blueprints provide organizations with expert guidance and support in designing and deploying custom Blueprints for Dell-validated and customer-owned applications. This ensures a smooth and seamless deployment process using Dell NativeEdge software, empowering organizations to quickly and efficiently adopt AI solutions at the edge and drive their digital transformation forward.
In summary, Dell NativeEdge is at the forefront of transforming edge computing and AI deployments. By offering high-availability capabilities, simplifying AI application deployment, and providing a broad catalog of pre-built solutions, Dell NativeEdge ensures that organizations can effectively leverage the power of AI at the edge. This suite of tools, combined with Dell’s expertise in edge computing, provides a reliable foundation for businesses to innovate and scale AI applications across diverse environments while maintaining operational resilience.