Edge computing is a distributed architecture in which computing occurs near the physical location where data is being collected and analyzed. It involves moving some of the storage and compute resources out of the central data center and closer to the source where the data is generated. By doing this, fewer processes are run in the cloud and instead moved to local places, such as on a user’s computer, an IoT device, or an edge server.
Bringing computation to the network’s edge minimizes the need for long-distance communications between client and server, which reduces latency and bandwidth usage.
In this respect, edge computing is different from conventional cloud-based or on-premises architectures, in which workloads that are hosted in large central data centers of public clouds or on-premises infrastructures are then accessed over the network and remain comparatively distant from users.
In this article, we will learn about edge functions, what they are, their benefits, and their use cases. We will also discuss what edge functions mean for the future of computing.
Edge computing can be incorporated into various applications, products, and services. A few possibilities include:
By leveraging edge computing, cities can manage traffic more effectively. It eliminates the need to transport large volumes of traffic data to the centralized cloud, thus reducing the cost of bandwidth and latency.
By processing real-time data from medical sensors and wearable devices, AI/ML systems aid in the early detection of various conditions, such as diabetes and skin cancers.
By caching content (e.g., music, video stream, web pages) at the edge, content delivery can be significantly improved, and latency is reduced.
Backhaul and roundtrip times are reduced with edge computing, and sensitive information can be processed at the edge. For example, the time it takes for voice-based assistant devices such as Amazon’s Alexa to respond would be significantly reduced.
Cloud gaming companies can build edge servers as close to gamers as possible to reduce latency and provide a fully responsive and immersive gaming experience.
Interactive live video takes quite a bit of bandwidth, so moving backend processes closer to the video source can decrease lag and latency.
Edge architecture minimizes network-related performance issues by reducing the geographical distance between end-users and servers. In fact, with edge computing, only the data that needs to be sent to the central data center or cloud needs to travel back. Using this approach, a rich application experience can be provided while making efficient use of the existing network.
With edge computing, any data traversing the network back to the cloud or data center can be secured through encryption. The edge deployment can be hardened against hackers and other malicious activities.
Edge computing works locally to save data and transmit it to a central server when internet connectivity is available. Edge computing is helpful in environments with unreliable connectivity or limited bandwidth, such as oil rigs, remote farms, ships at sea, rainforests, and deserts. Also, by processing data locally, the amount of data to be sent can be vastly reduced, requiring far less bandwidth or connectivity.
Organizations that collect, process, and store data must adhere to data residency and localization laws. For organizations with remote locations, edge computing can help meet these requirements.
Organizations can achieve fine-tuned control over where different applications and data are hosted by locating processing and storage at edge locations. As a result, they can better comply with regulatory rules specific to a particular country or region. An organization can, for example, use edge servers to keep European-based customers’ data in the EU, where it can be managed in accordance with the EU GDPR regulations, while the data of customers located in other jurisdictions, which are not subject to these laws, is handled differently.
Edge functions enable development teams to more efficiently deliver several features such as A/B testing, custom authentication, dynamic routing, path handling, geolocation, personalization, and more.
The goal of edge functions is to make the developer experience easier by allowing you to simplify experimentation, customize authentication, personalize web content and enhance security.
Some frameworks that support edge functions are:
Gartner states that 91 percent of today’s data is created and processed in centralized data centers and that by 2025, 75 percent of all data will be moved to the edge. According to the IDC Data Age 2025 report, by 2025, 175 zettabytes of data will be generated across the globe. Edge devices will create more than 90 zettabytes of that data.
Despite edge computing existing for many years, the COVID-19 pandemic promoted its widespread adoption across several industries. MarketsandMarkets estimates that the edge computing market will reach $36.7 billion in 2021. According to forecasts, the global edge computing market is expected to reach $87.3 billion by 2026.
Based on these statistics, the adoption of edge computing will become more prevalent in the coming years.
It is becoming increasingly common for cloud providers to offer edge function and edge computing services because they provide the capability to place some critical aspects of application logic closer to the end-user. By using this approach, end users can have a more rewarding and faster experience while also opening up new and unique possibilities.
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