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To download the full report on edge archetypes, and access other edge resources, visit www.VertivCo.com/Edge
Taking a Data-Centric Approach to Edge Infrastructure Despite the magnitude of its impact, there exists today a lack of clarity associated with the term edge computing and all that it encompasses. Consider the example of a similarly broad term: cloud computing. When IT managers make decisions about where their workloads will reside, they need to be more precise than “in the cloud.” They need to decide whether they will use an on-premises private cloud, hosted private cloud, infrastructure-as-aservice, platform-as-a-service or software-asa-service. That does more than facilitate communication; it facilitates decision making. Vertiv has attempted to bring similar clarity to edge computing by conducting an extensive audit and analysis of existing and emerging edge use cases. What emerged was the recognition of a unifying factor that edge use cases could be organized around. Edge applications, by their nature, have a data-centric set of workload requirements. This data-centric approach, filtered through requirements for availability, security and the nature of the application, proved to be central to understanding and categorizing edge use cases.
3. Machine-to-Machine Latency Sensitive The Machine-to-Machine Latency Sensitive Archetype, while similar to the HumanLatency Sensitive Archetype in that low latency is the defining factor in both archetypes, is even more dependent on edge infrastructure. Machines not only process data faster than humans, requiring lower latency, they are also less able to adapt to lags created by latency. As a result, where the cloud may be able to support HumanLatency Sensitive use cases to a certain point as they scale, Machine-to-Machine Latency Sensitive use cases are enabled by edge infrastructure. 4. Life Critical The Life Critical Archetype includes use cases that impact human health or safety and so have very low latency and very high availability requirements. Autonomous Vehicles are probably the best-known use case within the Life Critical Archetype. Based on the rapid developments that have occurred, and the amount of investment this use case is attracting, it is now easy to envision a future in which Autonomous Vehicles are commonplace. Yet, we’ve also had recent reminders of both the criticality of this use case and the challenges that must be addressed before that future vision becomes a reality. Once the technology matures and adoption reaches a tipping point, this use case could scale extremely quickly as drivers convert to autonomous vehicles.
About Vertiv Vertiv designs, builds and services critical infrastructure that enables vital applications for data centers, communication networks, and commercial and industrial facilities. For a more detailed discussion of edge archetypes, read the report, Four Edge Archetypes and their Technology Requirements.
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2. Human-Latency Sensitive The Human-Latency Sensitive Archetype includes applications where latency negatively impacts the experience of humans using a technology or service, requiring compute and storage close to the user. Human-Latency Sensitive use cases fall into two categories: those which are already widely used but supported primarily by cloud or core computing, such as natural language processing, and those that are emerging, such as Smart Security and Smart Retail. In both cases, edge infrastructure will be required to enable these use cases to scale with the growth of the businesses or applications that depend on them.
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The result of our analysis was the identification of four archetypes that can help guide decisions regarding the infrastructure required to support edge applications. These four archetypes are:
These four archetypes are described in more detail in the Vertiv report, Defining the Edge: Four Edge Archetypes and their Technology Requirements. They represent just the first step in defining the infrastructure needed to support the future of edge computing. But it is not one that should be understated. When we shared the archetypes with industry analyst Lucas Beran of IHS Markit, he commented that, "The Vertiv archetype classification for the edge is critical. This will help the industry define edge applications by characteristics and challenges and move toward identifying common infrastructure solutions." Edge computing has the potential to reshape the network architectures we’ve lived with for the last twenty years. Working together, we can ensure that process happens as efficiently and intelligently as possible.
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Defining Edge Archetypes
1. Data Intensive The Data Intensive Archetype encompasses use cases where the amount of data is so large that layers of storage and computing are required between the endpoint and the cloud to reduce bandwidth costs or latency. Key uses cases within this archetype include High-Definition Content Delivery and IoT applications, such as Smart Homes, Buildings, Factories and Cities. With bandwidth the limiting factor in Data Intensive use cases, these applications typically scale by the need for more data to improve the quality of service.
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Martin Olsen, Vice president, global edge and integrated solutions E: Martin.Olsen@VertivCo.com VertivCo.com Martin Olsen brings more than 15 years of experience in global mission-critical infrastructure design, innovation and operation to his role as vice president of global edge and infrastructure solutions at Vertiv.