So much has changed since digital transformation started gaining traction in the late 1990s. Businesses saw and adapted to the rise of the Internet, e-commerce, cloud computing, and big data analytics. The pervasive use of social media, mobile technology, artificial intelligence (AI), and machine learning (ML) has since shaped their digital strategies.
Data center solutions, in return, responded to each stage of digital evolution, transforming simple server rooms into massive and dynamic infrastructures that address the primary goal of digital transformation—the need for speed.
The latest solution to achieve this goal is edge computing. This post tackles the specific impacts edge computing has on data center infrastructures.
What Is Edge Computing?
Edge computing is a distributed computing approach where data storage and processing are moved closer to the data source, rather than relying on a centralized cloud or data center. Since data processing is closer, the latency or the time it takes for data to travel to a distant server and back, is reduced.
Edge computing also enables real-time responsiveness for critical applications, such as industrial Internet of Things (IoT) devices, remote patient monitoring systems, and autonomous vehicles.
How Is Edge Computing Transforming Data Centers?
Edge computing is leading to a more distributed, intelligent, and responsive data infrastructure. It pushes data processing closer to the data source and is reshaping how data centers are designed, located, and managed. Below are three specific impacts of edge computing on data centers.
From Centralized to Localized Data Processing
Imagine you have a smart security camera. In the traditional cloud computing model, the camera records video and sends all the raw data over the Internet to a distant cloud server (often hundreds or thousands of miles away). The server analyzes the video to detect movement or recognize faces. As you can imagine, this process can be slow and prone to latency, as it requires a significant amount of bandwidth and ultimately depends on the speed of your Internet connection.
With edge computing, the camera can process data and analyze a video immediately. If it detects something suspicious, the camera then sends a smaller piece of data to the cloud (e.g., a notification that says, “Motion detected at 9:15 A.M.” instead of the entire raw video).
Processing data locally reduces latency and enables applications to respond in real time. The demand for these capabilities has forced data center solutions to change data center architecture designs and move processing power closer to the data source.
The Rise of Edge Data Centers
To address the need for localized data processing, edge data centers have been developed and continue to rise. Unlike their massive, centralized counterparts, edge data centers are smaller and strategically located closer to the points where data is generated.
While traditional data centers are typically located in remote areas, the locations of edge data centers range from a few racks of servers in a repurposed telecommunications facility that is closest to purpose-built, modular units deployed in urban areas.
Because the data centers are moving closer to communities, providers have redesigned their data centers to address common risks. Data centers in Texas, for example, are built to resist hurricanes, avoid flooding, and prevent overheating.
It’s important to note that while some edge data centers can operate independently, others need to form a decentralized network of smaller facilities that complement (not replace) traditional cloud data centers.
Growing Reliance on Automation and Remote Management
Traditional data centers often have dedicated on-site IT staff. Edge data centers, on the other hand, are typically managed round-the-clock remotely since they are numerous and in dispersed locations. However, emergency IT personnel are often available on call.
Edge data centers also rely on lights-out operations, where facilities can largely manage without manual intervention. Therefore, automation plays a crucial role in edge data centers. It allows organizations to automatically perform routine maintenance tasks and even self-heal in response to minor issues.
Conclusion
Organizations need to develop applications that can process data and respond in real time, and edge computing allows that. The need for speed has impacted how data center infrastructures are designed and even located, leading to the rise of edge data centers.
These smaller, decentralized facilities bring computational power closer to the data source, helping minimize latency and conserve bandwidth, especially as more devices connect to the application.
