Today’s IT landscape contains a growing movement toward micro data centers. These micro data centers are compact, powerful, and designed to meet the needs of edge computing for quick and instant access to data at remote or distributed locations.
What is edge computing? Whether you are new to the term or not, the definition of edge computing is still evolving as solutions emerge. In our experience working with organizations to design and implement edge computing solutions, edge computing can be defined as any computing that takes place outside your centralized data center, away from your IT staff. It can involve only a few remote sites or it can be hundreds or thousands of sites, such as retail locations.
These sites can be across town or around the world. Using only a small or tiny hardware footprint, infrastructure at the edge collects, processes, and reduces vast quantities of data that can then be further uploaded to either a centralized data center or the cloud.
While edge computing is certainly a more recently created term, it encompasses on-premises computing solutions that many distributed enterprises have attempted or sought for decades. With the proliferation of IoT devices and AI, and as more devices connect to the internet and to each other, edge computing solutions are moving to the top of the boardroom agenda for IT.
Artificial intelligence (AI), machine learning (ML), and Internet of things (IoT) technologies are not only driving the need for more advanced edge computing solutions, but they are also changing the landscape of data centers. As AI, ML, and IoT technologies drive more data to and from remote sites to the data center, the data center must adapt to centrally manage the remote computing and the increasing amount of data needing to be collected and analyzed and redistributed.
Edge computing software can offer optimized real-time capabilities, even in remote and restrictive locations. Compared to latency-prone remote network connections to cloud systems, on-premises computing systems can more rapidly respond to monitored data changes in automated systems such as in manufacturing plants to keep production moving.
We see edge computing successful in environments such as smart cities, industrial plants, logistics and transportation companies, retail stores, and healthcare facilities. These organizations might deploy solutions in dozens or hundreds of locations, each needing a minimum of capabilities to operate onsite even with outside network interruption and manage large amounts of data.
What these kinds of environments have in common is that they cannot run solely from a centralized data center. At remote sites, where there is no on-site IT staff, traditional solutions become over burdensome to deploy and manage both in terms of time and cost.
Edge computing is not an environment where traditional servers, networking, and storage make sense, and this is where we are seeing new micro data centers emerge. Smaller systems that are autonomous, highly available, self-healing, easily managed remotely, and with the processing power, storage, and flexibility of virtualization are not only important but essential in making edge computing both practical and affordable.
Scale Computing offers a variety of computing infrastructure appliances for both primary and edge computing. The HC3 Edge appliance series features appliances specifically built to meet the needs of edge computing with high availability, self-healing, intelligent automation, easy deployment, easy management, seamless scalability, and multi-site management options. Find out more here.