¿Qué es Edge Cloud?

An “edge cloud” refers to a middle ground between cloud computing and the edge of a network. This is often not a precise definition because the area between the edge and the cloud is ambiguous. While a cloud embodies core centralized compute and storage resources available via the internet, the edge of a network, sometimes more specifically described as the device edge, is a term that refers to the furthest physical and/or logical aspect from the core—for example, where there are IoT devices.

The edge can be described in other terms, by the burdens it places on a network. Specifically, the edge is an endpoint whereby latency, bandwidth, and network congestion become significant enough to warrant placing compute and storage resources closer to the data producing device rather than rely on backhauling data to the core for processing. Imagine several regional data center substations replacing a single central data center, commonly known as a distributed system.

In this way, the edge cloud is formed (the cloud core in the above example somewhat disappears by edging outward towards the device edge via multiple stations), and instead of a single brain with many very long latent connections, these edge devices now transmit data to the most available station (read closest or least congested).

Edge cloud is a common enterprise practice today, and may simply go by another name, redundant distributed systems. Companies that want to maintain a high level of available services, like streaming, cannot rely on a single central data center to meet demands, and so distribute their cloud content in strategic locations.

Yet, because it serves a purpose similar to the device edge, the edge cloud is different from redundant content delivery systems. The device edge challenges networks by introducing latency, bandwidth, and network congestion issues. Before IoT and the proliferation of devices, data was still generated in relatively low amounts. Today, these devices and other demands have overburdened the internet as a whole. Data transiting the internet is now exponentially more voluminous every year leading to the device edge challenges mentioned. The net effect is slower Internet infrastructure, and greater inefficiency for businesses that rely on the Internet for backhauling their data.

One solution is to avoid the data backhaul. For edge devices, placing storage and compute on the device, or local network, can eliminate the need to “fetch” compute power. For example, a small server in a smart home could collect and process device data, eventually relaying a summary back to the cloud. However, homes with their own servers may be overkill.

But, in smart cities, where the edge is more diffused, edge clouds find a use case. This diffusion has earned edge clouds another name, “fog”. In a fog, the physical edge falls off and the logical edge remains, for smart cities the logical edge may be the city limits, but edge devices can be everywhere. In these cases, maintaining focus on the purpose of edge computing is necessary: moving compute and storage resources closer to where the data is created offering local processing so as to reduce latency, bandwidth, and congestion issues.

The edge is a colloquial term that refers to the devices or infrastructure away from an organization's core cloud resources, respectively, device edge and infrastructure edge. While the edge can be a physical location, the simplest model, the edge can also be demarcated by logical separations. Logical separation may look like a warehouse within a compound of warehouses. Many IoT devices may be deployed throughout each warehouse, and each warehouse may be equipped with a server to process data, sending summaries to the cloud (a data center potentially in a different region).

Cell towers are a case of infrastructure edge, providing the connectivity for edge devices, say for autonomous vehicles. A self-driving truck may make thousands of calculations in the moment, but also rely on fast 5G connectivity to understand other circumstances, like where other vehicles are, the road conditions, and how its payload fits into the larger supply chain in real-time. While these are all important, latency seriously curtails the actual driving of the vehicle, and is the reason compute and storage are placed on the vehicle itself. Backhauling data used in driving to the core cloud is simply an unwanted latency risk that can lead to accidents and the loss of life..

The edge plays a security role in the total network. While the edge does open new points of attack, it offers companies a way to limit backend exposure. Placing controls closer to those edge areas enhances visibility into requests. At this point, applying security policies have the effect of creating a drawbridge between the edge and cloud core. 

Cloud edge security prioritizes these kinds of gateway policies, and important security fundamentals such as data encryption. But the edge demands modern security practices, such as automated authentication of requests. One way to achieve edge security is through software-defined technologies. Secure Access Service Edge (SASE) is used to deliver these security controls and policies as a cloud computing service directly at the edge rather than at the data center. SASE rests on the concepts of digital identities, zero-trust, and real-time context—always verifying access and authentication rather than opening the door to “trusted” entities. For instance, if all security checks pass, but a request comes from a contextually ambiguous IP-address, then the request could be flagged, prevented, and later followed up on.

The main benefit of edge cloud is to reduce latency, bandwidth, and network congestion issues inherent in the continued proliferation of devices, and the subsequent volumes and velocity of data generated into today’s cloud world. This is achieved through a variety of architectures. The model is to place compute and storage resources where data is generated, namely on those data generating devices, like IoT devices.

In the case of edge clouds, the aim is to place compute and storage resources very close to those devices, but this does not have to mean more data centers. For example, Micro Modular Data Centers (MMDC) are self-contained compute, storage, and networking resources that can be placed in close proximity to edge devices. This is highly applicable in disaster situations where deployment is impromptu and immediate. Another application is in areas where the internet is not available or poor connectivity curtails bandwidth.

Other benefits besides overcoming bandwidth, latency and congestion challenges: autonomy, data sovereignty, edge data security.

• Autonomy from the Internet — Edge cloud allows for autonomous operations, which can be particularly useful in areas where internet connectivity is limited. As pointed out by the features of MMDCs, edge cloud architectures are suited for remote locations, like monitoring devices deep in the wilderness, or on vessels or facilities out at sea such as oil rigs.
• Data Sovereignty — Data protection and security, especially that of personal information, is regulated. Because of these regulations technology must now accommodate and prioritize the semantic aspect of data over the physical aspect. In terms of regulations, personal information typically cannot reside on servers outside the country of the person it refers to. Yet as the edge continues to grow, and diffuse, these data sovereignty issues will challenge the transit and storage of data. In some cases, placing compute and storage closer to or on edge devices provides a solution.
• Edge Security Enhancements — Edge cloud will provide new opportunities for attacks, it is the nature of changing technology. However, it also provides new opportunities for defenders who can architect security packages that bolster protection. Data transiting between edge and core can be encrypted, while endpoints can be hardened against attack.