Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Vertiv Research Defines Standard Models for Deploying Edge Infrastructure

Vertiv a global provider of critical digital infrastructure and continuity solutions, released the results of an in-depth research project to identify edge infrastructure models to help organizations move toward a more standardized approach to edge computing deployments, with the intent to improve costs and deployment times.

Recommended AI News: NTT DATA Empowers Work, Workers and Workspaces

The report, Edge Archetypes 2.0: Deployment-Ready Edge Infrastructure Models builds on the edge archetypes research and taxonomy  Vertiv introduced to the industry in 2018. The new research further categorizes edge sites based on factors including: location and external environment, number of racks, power requirements and availability, site tenancy, passive infrastructure, edge infrastructure provider, and number of sites to be deployed.

  • Device Edge: The compute is at the end-device itself, either built into the device or in a standalone form that is directly attached to the device, such as AR/VR devices or smart traffic lights.
  • Micro Edge: A small, standalone solution that can range in size from one or two servers up to four racks. It can be deployed at the enterprise’s own site, or could be deployed at a telco site, with common cases including real-time inventory management and network closets in educational facilities.
  • Distributed Edge Data Center: This could be within an on-premise data center (either a pre-existing enterprise data center or network room or a new standalone facility). It also could be a small, distributed data center or colocation facility located on the telco network or at a regional site. Distributed Edge Data Centers are currently common in manufacturing, telecommunications, healthcare and smart city applications.
  • Regional Edge Data Center: A data center facility located outside core data center hubs. As this is typically a facility that is purpose-built to host compute infrastructure, it shares many features of hyperscale data centers e.g. is conditioned and controlled, has high security and high reliability. This model is common for retail applications, and serves as a intermediary data processing site.

The introduction of edge archetypes three years ago advanced the understanding of the edge. It was the first formal attempt – using information gathered across the industry – to group edge applications in a way that would help organizations avoid reinventing the wheel with every edge deployment. Since then, other organizations and industry bodies have been working in parallel – and often with Vertiv as a collaborator – to create standard processes and technologies to advance the understanding and effectiveness of the edge. These latest edge infrastructure models represent the logical next step.

Related Posts
1 of 40,360

Recommended AI News: Acxiom Builds Innovative Marketing Platform for Toyota’s Move Away From Cookies

“As the edge matures and edge sites proliferate and become more sophisticated, creating edge infrastructure models is a necessary step toward standardized equipment and design that can increase efficiency and reduce costs and deployment timelines,” said Martin Olsen, global vice president, edge strategy and transformation for Vertiv. “Edge sites will continue to require some customization to meet users’ specific needs, but these models streamline many fundamental choices and introduce some much-needed repeatability into edge environments. This research is especially useful for specifiers, such as channel partners, and IT management professionals.”

The research, developed with the support of analyst firm STL Partners, makes clear that edge sites will require refinements based on factors that may include environment, use case, legacy equipment, security and maintenance, enterprise data center operations, and communications capabilities. These adjustments are possible within the framework of the edge infrastructure models, however, and do not diminish the benefits of standardization the models provide.

“By adopting the four infrastructure models, edge players across the ecosystem can derive an array of benefits, including accelerating go-to-market and expediting deployment of sites,” said Dalia Adib, director, consulting and edge computing practice lead, STL Partners. “The edge market is experiencing growth and this can only be bolstered by introducing some level of standardization to the language we use for describing the edge.”

The report also examines the edge infrastructure requirements of some key verticals, including manufacturing, retail, and telecommunications, and assesses their preferred edge infrastructure models. In addition to identifying edge infrastructure models, the report provides recommendations for enterprises and solution providers deploying edge infrastructure.

Recommended AI News: Adshares.net web3 Protocol Disrupts Digital Advertising Market

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.