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Edge Computing

Noun
|
Sounds like: "edge com-put-ing"

Edge computing brings workloads closer to the end user to reduce latency and improve the customer experience. Edge computing is done in edge data centers which are small, local, mission-critical data centers that are part of a complex network that deliver cloud computing resources and cached content as close as possible to the populations they serve.

Latency has always been a problem for data center managers, but recently it’s become a massive concern due to technology trends such as big data, the Internet of Things (IoT), and cloud and streaming services. End users and devices demand anywhere, anytime access to applications, services, and data, and latency is no longer acceptable. As a result, organizations across many industries are leveraging edge computing as a high-performance and cost-effective way to provide customers with content and functionality.

Top Use Cases of 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.

Edge Computing and DCIM Software

Edge computing, by definition, occurs in many, small, remote locations. This presents many specific challenges in edge data center management such as being able to direct technicians to complete changes properly, monitoring data center health across all locations, and managing all assets and connections across the entire edge deployment.

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.

Want to see how Sunbird’s world-leading DCIM software makes it easy for you to remotely manage all your edge sites? Get your free test drive now!

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WORD OF THE DAY:

Data Center Infrastructure Efficiency (DCIE)
Data Center Infrastructure Efficiency (DCIE) is a metric developed by The Green Grid used to measure the energy efficiency of a data center.
Learn even more about this term