News

Dell Announces $1 Billion IoT Effort and Partner Program

• By Keith Ward
• October 11, 2017

Dell Technologies is investing more of its resources on the booming Internet of Things (IoT) space, this week announcing a new IoT-focused division that includes a partner program, product development, labs, consumption models and ecosystem-building.

CEO Michael Dell announced the IoT Solutions Division at a New York City event on Tuesday. At its helm is Ray O'Farrell, former executive vice president and chief technology officer of VMware. O'Farrell's new title will be "general manager for Dell Technologies IoT division."

In a press release, O'Farrell explained Dell's vision for the new group: "Our new IoT Division will leverage the strength across all of Dell Technologies family of businesses to ensure we deliver the right solution -- in combination with our vast partner ecosystem -- to meet customer needs and help them deploy integrated IoT systems with greater ease."

To fulfill that vision, Dell said it will be investing $1 billion into its IoT efforts over the next three years. The product range that will be affected is wide, and includes Dell servers; storage, both on-premises and in the cloud; Pivotal Cloud Foundry and Pivotal Container Services for developing new cloud-based analytics applications; and Virtustream cloud management software.

The company's IoT Solutions Partner Program, which currently has 90 members including Microsoft, SAP and Intel, will be central to growing Dell's IoT presence, according to the announcement. "The program will now support partners across all Dell Technologies businesses, allowing for easier collaboration and implementation of blueprints," Dell said.

The groundwork for some of this was laid last May, when VMware announced its Pulse IoT Center during the Dell EMC World conference. Pulse IoT Center is an edge-to-cloud management platform for enterprise-scale computing. It includes technology from its AirWatch endpoint management solution and vRealize Operations software for infrastructure monitoring and troubleshooting.

Gartner Inc. has estimated that there will be 8.4 billion IoT devices in use by the end of this year, a number that's expected to grow to 30 billion by the end of the decade. That means there's a huge opportunity for Dell, and it's significant that a VMware executive was put in charge of the crucial new business unit.

Edge computing is at the heart of IoT. Trevor Pott, a columnist for RCP sister magazine Virtualization & Cloud Review, described it as "a solution in which compute and storage are offered hyperlocally...Many proposed use cases for IoT devices rely on the ability to make quick decisions based on sensor data, decisions that may take too long if the data has to be trucked back to a centralized data farm and then back again."

The press release highlighted some of the initial development initiatives for the IoT Solutions Division:

• Dell EMC 'Project Nautilus': Software that enables the ingestion and querying of data streams from IoT gateways in real time. Data can subsequently be archived to file or object storage for deeper advanced analytics;
  
  
• 'Project Fire': a hyper converged platform part of the VMware Pulse family of IoT solutions that includes simplified management, local compute, storage and IoT applications such as real-time analytics. 'Project Fire' enables businesses to roll-out IoT use cases faster and have consistent infrastructure software from edge to core to cloud;
  
  
• RSA 'Project IRIS': Currently under development in RSA Labs, Iris extends the Security Analytics capability to provide threat visibility and monitoring right out to the edge;
  
  
• Disruptive technologies like processor accelerators will increase the velocity of analytics closer to the edge. Collaboration with industry leaders like VMware, Intel and NVIDIA and the Dell Technologies Capital investment in Graphcore reflect opportunities to optimize servers for AI, machine learning and deep learning performance.
  
  
• Project 'Worldwide Herd': for performing analytics on geographically dispersed data -- increasingly important to enable deep learning on datasets that cannot be moved for reasons of size, privacy and regulatory concern.