Enterprises are pushing the edge—edge devices, edge clouds, local systems on the edge. Proceed with your eyes wide open. Credit: Thinkstock Big companies such as General Electric, Siemens, and Robert Bosch are using edge computing technology to optimize production. Manufacturing is a large consumer of edge approaches and technology. Typically, these edge systems are powered by artificial intelligence (AI) systems that parse production data at the source of the data. This enables them to make instantaneous decisions, such as adjusting the cooling systems in a factory so the welding robots can make more precise welds. Although the value of edge computing is well understood at this point, it’s still being used to solve problems where it’s not needed. We’re back to ensuring that whatever technology is being hyped right now is still a good choice. So, when is edge a good fit and when is it not? That’s really something to determine yourself, but I do have some general guidance. The first and larger mistake that I’m seeing is deploying edge computing out of a desire for control more than need. If you think back to when private clouds were popular, they were the desired end state of those who pushed back on giving up physical control to public cloud providers. The same seems to be occurring now. Some are using edge computing for control reasons, to keep most data local and off a public cloud. Also to keep the source of data closer to the processing for efficiency, which is the primary objective. The reality is that edge computing is not cheap. In most cases, you need to purchase, maintain, and fix your own hardware and software stack (the edge). Multiply this times the number of edge systems, and the edge computing bill is likely to be much higher than non-edge systems. Security is the second concern. It is easier and cheaper to secure data on the public cloud than on most edge-based systems. The more edge computing you have, the more the data is distributed, and the more difficult and costly it becomes to secure properly. Normally this means a higher risk of breach. Many justified the additional security risks because of the physical proximity of the data. I mean if I can see and touch the storage device then it’s secure, right? That’s not the way it works; most major breaches during the past year have been on systems the owners were standing next to. I’m not saying you need to be overly cautious. Just that you need to evaluate any new technology with both eyes open and an objective view of the technology’s value and purpose. Edge is just our latest challenge. Related content analysis Generative AI won’t fix cloud migration You’ve probably heard how generative AI will solve all cloud migration problems. It’s not that simple. Generative AI could actually make it harder and more costly. By David Linthicum Jul 12, 2024 5 mins Generative AI Artificial Intelligence Cloud Computing analysis All the brilliance of AI on minimalist platforms Buy all the processing and storage you can or go with a minimum viable platform? AI developers and designers are dividing into two camps. By David Linthicum Jul 09, 2024 5 mins Generative AI Cloud Architecture Artificial Intelligence analysis The next 10 years for cloud computing Despite AI's explosive growth, the industry still needs to face facts that customers are unhappy about costs and vendor lock-in. By David Linthicum Jul 05, 2024 5 mins Amazon Web Services Google Cloud Platform Microsoft Azure analysis Serverless cloud technology fades away Serverless was a big deal for a hot minute, but now it seems old-fashioned, even though its basic elements, agility and scalability, are still relevant. By David Linthicum Jul 02, 2024 4 mins Serverless Computing Cloud Computing Software Development Resources Videos