Despite the COVID-19 pandemic’s setbacks, edge computing is likely to spread at a breakneck pace over the next decade, boosted by advances in 5G and IoT technology.
Due to the massive amount of data created and the ineptitude to backhaul it, compute is pushed to the network’s edge to pre-process it. When multiple devices transfer data at the same time, however, issues develop. Sending a large amount of data generated by devices to a centralized data center or the cloud might cause bandwidth and latency problems. It is critical to have the ability to leverage the power of data from any location in order for a digital transformation program to succeed. As a result, edge computing has emerged as a more efficient option.
Here are some edge computing stumbling blocks that enterprises may encounter.
Fortifying data management and analytics
One of the compelling characteristics of this ecosystem is the ability to examine data at the edge and derive insights from analytics, but the process is not simple for businesses. The edge is essentially a problem statement for large-scale distributed data management.
To an organization’s business success, data management and data science are just as crucial as security. It should be unsurprising that the firm that can extract nuggets of knowledge from the mountains of data generated every second has the best chance of winning.
Data science, like security, is difficult to master and practitioners are rare. And industry experts feel it’s a blend of science and art. To get the most out of data, businesses will need the right tools. A smart data scientist, on the other hand, is aware of the intricacies of what data is most essential to the company. People, who are competent at this, like security, are in high demand.
Enterprises can reap benefits from an outside perspective in this area. There are consulting firms, VARs, and specialists who are well-versed in this area and have successfully deployed the data edge.
Overlook change management at own peril
This is more of a gentle reminder than startling news for experienced IT directors, but it’s still worth printing: Ignoring the implications of a big edge computing initiative on people’s day-to-day jobs isn’t a good idea.
Failure to incorporate all relevant stakeholders is one of the most significant flaws in an edge strategy. Moving workloads to the edge is not a “lift-and-shift” exercise, but rather a project involving many teams.
Almost every major job inside IT will necessitate some learning and/or adaptation, particularly if firms do not currently run a large number of workloads in edge architecture and can draw on previous expertise.
Having an open mind on open architecture
The most cost-effective edge solution combines the three components comprising compute, connection, and storage into a single box. Edge solutions are now focused on specialized application use cases, which seem to be ideal when there is no other system in place. The edge must be flexible enough to accommodate new systems as well as existing systems if it is to become the new standard.
The easiest method to overcome these challenges is by employing an open architecture platform that decreases technological sprawl, security vulnerabilities and exposures, and expenses. The idea is to keep the system design as simple as possible. Modularity and openness are the cornerstones of open edge architecture. It’s critical to be able to link to every network or communication device interface, including cellular, Wi-Fi, LoRA, or GPS, and to execute numerous different software stacks as a single entity, such as firewall, data analysis, machine learning (ML), or telemetry.