The explosion of smart devices is compelling organizations to seek new ways to deliver IT services to their employees and customers. This is driving the adoption of edge computing — an architectural model in which applications and data are located at the network edge, near the end-user. Gartner predicts that by 2025, 75 percent of data will be processed at the edge rather than in centralized data centers or the cloud.
Edge computing is proven to enhance performance, improve response times, reduce bandwidth costs and enable scalability. It is most beneficial for latency-sensitive applications, such as the Internet of Things (IoT), artificial intelligence, and artificial and virtual reality technologies.
Software-defined WAN (SD-WAN) plays a role in edge computing solutions. SD-WAN can streamline WAN deployment and management across multiple edge sites and provide intelligent routing of network traffic to maximize efficiency. It also enables the use of multiple WAN transport options for greater flexibility, cost-efficiency and resilience.
SD-WAN at the Edge
Edge computing is the common name for several deployment architectures. Although it’s closely tied to the IoT, this approach has been used for decades to manage remote sites. In essence, edge computing provides remote compute and storage capacity to capture and analyze data close to where the data is acquired. It can be as simple as a Raspberry Pi running custom software all the way up to a container data center.
Edge devices come in all sorts of form-factors with different connectivity requirements. On top of that, they are deployed all over the place, and it’s not always possible to drop a rack of network equipment and a secure connection in an edge location. Imagine deploying a server at an oil rig or a remote medical clinic that lacks reliable network connectivity.
Whether deployed as a physical or virtual appliance, SD-WAN simplifies WAN connectivity for edge devices. It allows for a relatively straightforward way to create a secure link to your internal network using any available connection type.
Edge Computing Use Cases
Edge computing is being used in a wide range of industries to gain real-time insight into data. Use cases include smart utility grid analysis, streaming video optimization and drone-enabled crop management. Edge computing is used in healthcare to support and IoT devices.
Smart cities are using edge computing to support facial recognition systems, automatic number plate recognition and intelligent video analytics. Edge computing also enables bus frequency optimization based upon demand patterns, vehicle flow control and lane management. Because huge volumes of data don’t have to be transmitted to the cloud for processing, smart cities systems at the edge can reduce bandwidth costs by 60 percent to 70 percent.
Financial services organizations are using edge computing to gain competitive advantages. Edge computing can help banks deliver faster, more secure services while assuring regulatory compliance and fraud detection. Processing data locally enables hedge funds and high-frequency algorithmic trading businesses to optimize profitability by minimizing data delays.
Edge computing has reached its inflection point due to huge computing demand at the edge and a massive increase in data volumes. This doesn’t mean that cloud usage will go down — the future network infrastructure will simply be balanced between the edge and cloud computing systems. If your organization relies on data and analytics, edge computing combined with SD-WAN can provide the performance and efficiency you need while reducing costs and increasing flexibility.
SD-WAN has become increasingly popular over time, creating a lot of products in the IT market. As a leading global IT solutions provider, Rahi can help define your needs and select a solution that will reduce costs, enhance performance, and simplify IT across your multisite network.