The amount of data being created and copied on a daily basis is quickly growing beyond recognized standards of measurement. A 2018 industry report indicates a staggering 5 quintillion bytes of data are produced every day (that’s 2.5 followed by 18 zeros) with IDC predicting that by the end of the year our digital universe will contain nearly as many digital bits as there are stars in our physical universe.
Some companies have a plan in place for handling the ever-increasing pool of available data, but for many, it remains an unresolved challenge. Companies migrating operations to the cloud to take advantage of efficiencies and innovation opportunities are finding when their IoT-enable processes push data nonstop to the cloud are exposed to risk in the form of security gaps, poor response times due to the distance between devices and where data is being stored, and rising cloud costs.
For many organizations wrestling with the data challenge, edge computing is becoming a powerful tool.
Edge computing has evolved from buzz-status to become a key trend in the IoT age. In fact, Gartner identifies it as one of its top tech trends for 2019. A recent Micron/Forrester survey found that within the next few years more than half of respondents expect to be analyzing complex data sets at the edge. Such results have compelled Gartner, through its Maverick Research arm, to declare that “the edge will eat the cloud.”
In simple terms, edge computing is computing data at the edge of a network — close to where it’s produced. Storing and processing data locally — at “the edge” as opposed to on some cloud server halfway around the world — has some distinct advantages. The security and privacy angle is an obvious one: It’s just easier to ensure your data is locked down and secure when it’s close to hand (i.e., not stored on a cloud server in Singapore). Apart from that, there’s also the speed and latency factor. When data is stored and processed locally, computing can be done in real time as opposed to in a series of communications back and forth between device and cloud server.
IoT spending isn’t slowing down — it’s predicted to soon go storming past the $1 trillion mark — and almost half of businesses now have edge computing implementations underway. Edge computing installations are becoming increasingly business-critical. This will only become more so the case in a world where it’s predicted there will be 80 billion connected devices by 2025 — a staggering leap from approximately 11 billion back in 2016.
One study predicts the edge computing market will be worth almost $30 billion by 2025. While research like this study says a great deal about the rapidity at which edge computing is emerging, it may obscure the present reality that many companies today place themselves in the “early adopter” phase when it comes to this technology. These organizations want answers to certain questions of edge deployment before they commit to a full rollout.
The Schneider digital guide “Solving Edge Computing Infrastructure Challenges” describes a new, emerging model that involves an integrated ecosystem of cooperative partners, vendors, and end users. This ecosystem and the integrated micro data center solution it produces help mitigate the unique challenges of edge applications.
Among the topics covered in the digital guide:
- The challenges of edge sites – Selecting and configuring infrastructure components; deploying all the parts to each site; and operating and maintaining multiple micro data centers from afar
- An integrated ecosystem of partners – The ecosystem should be centered around the end user and their technology needs for their business at the edge, also including IT and physical infrastructure vendors, MPSs and systems integrators
- Key elements – The three key elements of an effective micro data center solution, which are that it is preconfigured and tested, that it includes the necessary infrastructure to maintain IT resiliency, and that it uses open APIs & cloud-based software management tools