What is an Edge Data Center?

Edge data centers are smaller facilities located close to the populations they serve that deliver cloud computing resources and cached content to end users. They typically connect to a larger central data center or multiple data centers. By processing data and services as close to the end user as possible, edge computing allows organizations to reduce latency and improve the customer experience.

Why Do We Need Edge Data Centers?

Latency has always been a problem for data center managers, but in recent years it’s become a critical concern due to big data, the Internet of Things, cloud and streaming services, and other technology trends. End users and devices demand anywhere, anytime access to applications, services, and data housed in today’s data centers, and latency is no longer tolerable. As a result, organizations across many industries are establishing edge data centers as a high-performance and cost-effective way to provide customers with content and functionality.

Key Characteristics of Edge Data Centers

Edge data centers may be defined differently by different data center professionals 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. Edge data centers are placed near the areas they serve and are managed remotely.

Small. Edge data centers have the same components of a traditional data center but packed into a much smaller footprint.

Part of a larger deployment. An edge data center is one of many in a complex network including a central enterprise data center.

Mission critical. Edge data centers house mission-critical data, applications, and services for edge-based processing and storage.

Infographic

What is an Edge Data Center?

New applications driven by AI and Machine Learning are pushing the limits of the internet as we know it. By moving data centers and compute to the edge, or more regional, we are making the distance shorter between the data and the end user. Edge data centers are used to speed up web page downloads, stream content, and support Internet of Things (IoT) networks.

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Top Use Cases of Edge Computing

Currently, about 10% of data is created and processed outside a centralized data center or cloud, but by 2025, this figure will reach 75% (Gartner, 2018). Here are some of the top use cases for edge computing.

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.

 

The Role of DCIM in an Edge Data Center

There are many challenges specific to edge data center management, such as being able to direct technicians to complete changes properly, monitoring data center health across multiple locations, and managing all assets and their connections across the entire data center deployment. Having to manage edge data centers remotely usually involves a combination of multiple remote management tools, analytic capabilities, and databases. This can easily lead to inaccurate data, incorrect work orders, and poor decision making.

Data Center Infrastructure Management (DCIM) software provides data center managers with a central system where they can view the assets, power, connectivity, cooling, and physical security across multiple locations and accurately make changes to their data centers wherever they are located. The remote management and business intelligence capabilities of DCIM software helps edge data center managers achieve their goals of reducing latency while maintaining availability and uptime.

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