Edge Computing Essay
Edge Computing’s Role in the Cloud Architecture
Edge Computing is a distributed information technology network that places data processing and storage capabilities at the source. This concept challenges the paradigm in cloud computing of using centralized data centers to offer a suite of services. While it runs counter to the original model in cloud computing, edge computing can serve as a supplement to the cloud for specific use cases. The rise of the internet of things (IoT), a network of sensors to collect data, has made edge computing an appealing solution within cloud architectures. This distributed network can help to address challenges in bandwidth, latency, and congestion that arise in a typical centralized framework.
IoT has vastly increased the amount of data collection done by businesses and placed strains on centralized cloud compute networks. Without edge computing, all the data must be transferred to and from data centers over a wireless network. While these networks are extremely quick and efficient, accelerating data collection can push up against the limits of bandwidth availability. Furthermore, the billions of devices sending data can cause congestion over the network and increase latency. By shifting some data storage and computing resources on premises, businesses can limit the use of wireless networks and eliminate concerns over bandwidth, congestion, and latency. Edge computing addresses these issues of cloud computing but has its own limitations and drawbacks. There will be fewer resources at the edge location when compared to a centralized data center, reducing the available compute capabilities and services. Moreover, the internet of things and edge computing pose security challenges for a firm as they must account for more physical locations and devices in their network.
With their own advantages and challenges, edge computing and the cloud will best be used in tandem to address specific use cases. When implementing edge computing technology, it will be vital for companies to have well-defined goals for what they want to achieve. The nature of edge compute means it will need to have a limited scope and let the cloud handle more resource-intensive tasks. A possible implementation could be for sensors monitoring temperature in a cold-storage facility. The thermostat sensor may send data every five minutes to an on-premises data center that can process the information. This edge compute model will have two benefits over a cloud solution: the temperature can be adjusted without latency if it is out of range and the sensor will not send redundant data to the cloud when the temperature is within range.
AWS now offers edge computing services, called ‘AWS edge services’, to supplement its array of cloud solutions. Volkswagen is an example case of a firm using both AWS cloud and edge compute services to drive cost-savings. The carmaker uses the edge compute services for its manufacturing IoT so it can quickly identify problems and inefficiencies in its production process. On the factory floor, low latency is essential to respond to issues in a timely manner, making edge computing the optimal solution. However, Volkswagen uses more traditional cloud frameworks for most of its other business platforms and processes where edge computing is not necessary. This architecture may be become increasingly popular as IoT networks grow, making edge computing a critical complimentary service for cloud providers.
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