When discussing topics such as digital transformation, the IoT, software development, or data analytics, it is indispensable to also talk about the infrastructure behind the various applications and software being used. These days, many people think that storing and analysing data in the cloud is the best course of action. A more recent term used in this sense is “edge computing.” There’s a common misconception that cloud and edge computing are incompatible; that choosing one will necessitate abandoning the other. Despite the fact that the two serve distinct purposes, they actually enhance one another rather than compete with one another.
Latency Matters
Cloud computing, to quickly refresh the unwary, is the practice of transferring, storing, processing, and analysing large datasets on distributed servers located in data centres, typically over the internet. A significant delay, or high latency, occurs between the data being gathered and the data being processed because data centres are often located far from where the data is being generated and collected. This delay may only be a few hundred milliseconds but it can have a significant impact on time-sensitive applications which rely on real-time data for optimal performance. More importantly, bandwidth is significantly taxed when a huge amount of data must be transferred back and forth across the network. Because of this, processing and transmission speeds may be slowed even further. For time-critical applications, like in the case of driverless vehicles, this delay could be fatal.
“Edge computing” is often said to be the solution.
When compared to cloud computing, edge computing functions in direct opposition by relocating the processing and storage of real-time data closer to its point of origin. A portion of the application is relocated to be physically closer to the location of either the data source or the end-user. It greatly shortens the time it takes for data to travel and makes it possible for processing to occur in real-time, bringing latency down to almost nothing. Data-intensive programmes will benefit greatly from this development.
A Continuum Rather Than a Difference
To be effective, edge computing must be integrated into an organisation’s existing data operations. According to Wayne Duso, AWS Vice President, Storage, Hybrid-Edge, & Data Services, “We look at it as not the difference between cloud computing and edge computing but rather, we looked at it as a continuum of capabilities.”
In other words, edge computing must exist on a continuum with other forms of computation, from locally hosted hardware and software to public and private cloud infrastructures. To adapt to the new IT landscape, businesses will need to move their workloads to the locations where they make the most financial sense to run. All of the elements on the continuum will collaborate to supply whatever is needed to complete the current task. Data created by digital transformation efforts and the interconnection of devices and machines are often analysed in on-premises and near-edge settings.
The use of edge computing is an obvious development from other types of distributed systems, such as hybrid cloud setups. Combining the cloud with edge computing offers significant advantages, which helps to explain the growing interest and adoption.
However, this benefit does not come without a price, as distributed IT settings inevitably involve an increased degree of complexity. It is not a good enough reason to go against the grain but it should serve as inspiration to continue to plan, plan, and plan.
“Like anything else, there are always interesting challenges and we at AWS, live for interesting challenges,” Wayne said while trying to explain the disadvantages that might come with edge computing, despite its high-benefit returns. Some of the typical downsides of edge computing include:
- There must be additional space for storing it.
- The massive amounts of data provide significant security challenges for edge computing.
- Usually, all it does is analyse the data.
- The expense of using edge computing is substantial.
- It calls for high-tech facilities.
Providing Consistency from Edge to the Cloud
As the interview went on, Wayne mentioned that from AWS’ perspective, customers may now deploy Application Programming Interfaces (APIs) and tools outside of AWS data centres thanks to AWS edge services, which perform data processing, analysis, and storage, closer to the endpoints. In order to achieve ultra-low latency, intelligence, and real-time responsiveness, it is necessary to construct high-performance applications that can process and store data close to where it is generated. Now that apps can be developed once and deployed both in the cloud and on the edge, users can enjoy a unified experience regardless of where they are located. AWS is allowing the cloud’s infrastructure, services, APIs, and tools to be brought to any on-premises data centre or co-location facility.
Wayne also claims that by using AWS’s architecture and services, you will improve your security by ensuring continued security and compliance at every stage, from the network’s edge to the cloud. When processing data that must be kept on-premises or at the edge, users can now employ protective techniques like encryption and access control to ensure the data’s safety. Secure edge computing capabilities are extended to metro regions, 5G networks, on-premises sites, and ruggedised devices by the most trustworthy cloud provider, thanks to managed hardware installed in locations outside AWS data centres. He added that currently, no other service provider can match AWS’s worldwide reach in terms of physical infrastructure.
Wayne highlights that the Internet of Things (IoT), hybrid cloud, 5G, and industrial machine-learning are just some of the edge use-cases that can benefit from AWS’ extensive and in-depth set of capabilities. It is simple to grow to billions of devices and deploy apps at the edge with the help of 200+ built-in device services.
AWS for the Edge
As mentioned, you can now place the most powerful and safe cloud even closer to your endpoints and users with the help of AWS for the Edge. For almost every on-premises data centre, co-location space, or edge facility, AWS offers the same architecture, services, APIs, and tools found in the cloud as a fully managed service.
As a result, users can take advantage of managed hardware that has been deployed in places other than AWS data centres, bringing the benefits of secure edge computing to urban regions, 5G networks, on-premises installations, and disconnected or rural areas. Customers can use more than 200 integrated device services and capabilities designed for specific edge use-cases to rapidly deploy edge applications to billions of devices.
Some of the ways in which AWS can facilitate edge computing are as follows:
- With AWS Outposts, you can bring your AWS resources and services to any location while still benefiting from the seamless hybrid experience you’ve come to expect from AWS.
- With AWS Storage Gateway, users have on-premises access to Amazon Web Services’ nearly infinite cloud storage
- AWS Snow Family devices function outside of traditional data centres and in areas with spotty or no internet access.
- By optimising, securing, monitoring, and maintaining machine-learning models on distributed edge devices, Amazon SageMaker Edge Manager has become a popular tool.
According to Wayne Duso, edge computing is rapidly becoming a focal point, and with more and more businesses allocating resources to it, its promising future appears inevitable.
Wayne predicts a tenfold increase in both capacity and market size thanks to the emergence of the edge computing market as the next natural point in the evolution of the internet.
