An edge data center is a small facility located near the population it serves that delivers cloud computing and cached content to end users. Typically, edge data centers are connected to a large central data center or multiple data centers.
As big data, the Internet of Things (IoT), cloud and streaming services, and other modern technology trends increase the demand for anytime, anywhere access to applications, services, and data housed in today’s data centers, latency is no longer acceptable. Edge data centers offer a high-performance and cost-effective way to reduce latency and improve the customer experience by processing data and services as close to the end user as possible.
Edge data centers may be defined differently by various sources based on their roles, industries, or priorities, and due to the relative infancy of edge data centers as an established trend. However, most definitions share the following key characteristics:
- Local. Placed near the areas they serve and are managed remotely.
- Small. Contain the same components of a traditional data center but packed into a much smaller footprint.
- Part of a larger deployment. One of many sites in a complex network including a central enterprise data center.
- Mission critical. House mission-critical data, applications, and services for edge-based processing and storage.
Common Use Cases for Edge Data Centers
- Autonomous vehicles. Self-driving vehicles can collect process, and share data in real time, making transportation safer.
- Smart cities. Real time gathering and analysis of data on traffic, utilities, and infrastructure allows city officials to immediately respond to problems.
- Manufacturing. Equipping industrial IoT devices with data storage and computing capabilities allows for better predictive maintenance and energy efficiency.
- Financial institutions. With reduced latency for high-volume banking firms, trading algorithms are executed quicker, potentially making more profit.
- Telemedicine. Healthcare providers can have immediate access to critical patient data collected from personal health monitoring devices and fitness bands.
- Augmented reality. AR technology, which requires real time data processing, is being deployed by retail chains to create a more immersive in-store shopping experience.
- AI virtual assistants. The processing burden of household virtual assistants is distributed locally for improved performance and reduced latency.
- Video monitoring. Video cameras, especially those equipped with motion detection or facial tracking, record massive amounts of data that can be collected and processed locally.
- Gaming. Multi-player gaming relies on high bandwidth, low latency, and local matchmaking, leading to the emergence of cloud gaming.
- Content delivery. Content cached at the edge can be delivered to the end user in a matter of single milliseconds.
Edge Data Center Infrastructure Management
Edge infrastructure managers often leverage Data Center Infrastructure Management (DCIM) software as a central system where they can view and manage their assets, power, connectivity, cooling, and physical security across multiple locations and accurately make changes in their data centers no matter where they are located. DCIM software provides remote management and business intelligence capabilities that enable edge data center managers to achieve their goal of reducing latency while maintaining availability and uptime.
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