Edge computing is a modern IT architecture to bring data analytics closer to the source of data. It’s useful for IoT technology, remote work and transmitting data as efficiently and rapidly as possible. This type of networking is provided by Amazon Web Services, Dell, Cloudflare and other tech giants. Here are important points to know about edge computing for improving your business network.
Part of venturing into big data involves managing a high volume of data transmission to prevent or reduce network latency. The more congested a network becomes with data exchanges, the less reliable transmission performance and speed will be. The amount of bandwidth you use plays a major role in how much data you’re able to transmit or receive on a network.
A solution to this big data congestion problem is edge computing. The term “edge” may refer to a network hub that collects IoT data from various sensors. It may also refer to gateways and bridges between local infrastructure and the public internet. Edge computing is the second of six layers of IoT architecture. The other layers involve IoT platforms and devices, connectivity, data management and applications.
Components of an app that collect real-time data from IoT sensors can be embedded in edge servers. That was the way edge computing began to evolve commercially earlier this century to make video and web content closer to users. Today, edge computing solutions include online shopping carts and web widgets that present data in real time.
If your goal is to manage big data more efficiently, edge computing might be the solution for you. Not only does it provide cost efficiency, it delivers faster response times.
Watch the replay of our Living on the Edge webinar where our speakers break down the complexities of edge computing and provide strategies for successfully deploying edge solutions.
Edge computing has been embraced by organizations that regularly transmit a high volume of data. Industrial firms use edge computing for their robust control systems. This architecture has also become common with the telecommunications and media industries. Other industries that use this method to streamline operations include retail, manufacturing, healthcare, construction, transportation and agriculture.
A factory or warehouse is likely to use edge computing as a way to manage daily high volumes of data without sending it to the cloud. Farms are starting to embed sensors in fields to monitor crop development and environmental conditions. Autonomous vehicles that are being developed for industrial use are full of IoT sensors, in which keeping data localized is more practical than cloud computing.
The more a business collects big data without sending it to the cloud, the faster it can learn how to streamline its operations without slowing down the network. Any business using applications that require immediate insights or control based on real-time analytics can be enhanced with edge computing. Collecting high-volume data in multiple remote locations is another scenario in which edge computing is the more effective selection.
Edge computing has been around for about as long as the web, as it developed throughout the nineties. It started with remote computing, such as branch offices connecting with a central location. Traditionally, data was processed at the user or client-side, then was transmitted over the internet to a LAN, where it was stored. The data could then be processed using an enterprise app. Ultimately, the data was sent back online to a client device.
In a more updated paradigm, IT architects have reimagined how edge computing can be even more efficient. Instead of relying on the centralized data center model, a more modern solution is to design an edge infrastructure. While an edge infrastructure may include cloud solutions, it typically comprises many small data centers.
The focus has sharpened more on building an infrastructure full of business intelligence. Here are some of the most valuable forms of business intelligence associated with IoT sensors:
The more concern you have for managing quantity of data, the more you should consider edge solutions in your networking. Here are some of the main reasons for adopting the edge that cross all types of business:
Four top benefits when deploying an edge computing solution are latency reduction, bandwidth conservation, cybersecurity solutions and increased reliability. Big data can eat up limited bandwidth, so the solution is to transmit data more efficiently.
Edge computing is all about reducing the distance data has to travel from point A to point B. It’s ideal for organizations that prioritize data speed, as an edge solution reduces network latency. Any business that profits from streaming live data can benefit from edge strategies.
In the process of data transmission, data can get intercepted by third parties without a strong cybersecurity solution. The more IoT devices and data occupy a network, the more you increase risks of a cybersecurity breach. Even the best cybersecurity technology can be compromised if a hacker is persistent. Processing data at network edges is safer than across multiple internet hubs.Reliability of data transmission is another key concern when using edge computing. If connectivity is lost, do you have a backup plan? Keep in mind, it’s possible for data to be corrupted or lost without hackers involved. When network connectivity becomes unreliable, it can be at the expense of profits, such as with trading stocks online. Edge computing improves reliability, as long as you have a backup plan if your main network goes down.
Some of the main reservations business managers have about edge adoption is that its purpose typically is limited, compared with the multi-purpose nature of the cloud. The issue of connectivity is a big factor that drives certain businesses to cloud services that are “always on.” A 24-7 online ecommerce site cannot afford much downtime. In that sense, the cloud is usually more reliable.
Even though edge computing provides strong security, the more devices you put on a network, the more vulnerable it becomes. Many businesses don’t want the trouble of handling cybersecurity issues with in-house personnel, so they outsource to reputable data centers. IT specialists at the data centers take care of network monitoring, making the cloud a turn-key solution for many companies.
There’s no reason to view the edge as competing with the cloud, since both computing solutions have advantages for certain scenarios. You may decide to adopt a hybrid “cloud edge” strategy. FedEx, for example, uses a cloud edge strategy that supports IoT, robotics and automated processing.
While edge computing has storage limitations, cloud computing offers unlimited storage possibilities for websites. At the same time, edge computing provides faster data transmission and greater data protection. Overall, the edge is more efficient for remote tracking, whereas it takes more time to send data to the cloud.
If your goal is to manage big data more efficiently, edge computing might be the solution for you. Not only does it provide cost efficiency, it delivers faster response times.