> The goal of the Restaurant Edge Compute platform was to create a robust platform in each restaurant where our DevOps Product teams could deploy and manage applications to help Operators and Team Members keep pace with ever-growing business, whether in the kitchen, the supply chain, or in directly serving customers.<p>> (Previous article) Our hypothesis: By making smarter kitchen equipment we can collect more data. By applying data to our restaurant, we can build more intelligent systems. By building more intelligent systems, we can better scale our business.<p>I must admit, from an outsiders perspective, it really sounds like a bunch of buzzwords justifying a solution in search of a problem. Their examples of forecasting waffle fries reminds me of a failed startup that forecasted how many checkout lines to open via computer vision (which I can't find on Google). In the end, it turned out it was a lot easier for a human manager to simply open a new line when required, and the computer vision provided the wrong forecasting to be accurate. I wonder what CFAs success criteria and metrics are for this project.<p>Tech-wise, wouldn't it be a lot simpler to do a single node, single application that gets updated via something like RAUC? Especially if you have a small team (which they emphasized), it seems to me like adding a Kubernetes cluster at the edge adds complication without much benefit, other than "redundancy" (how redundant is a single rack with the same power source anyways?). Also, how would they get an important security update to the host, if it becomes necessary?<p>It's a lot of nitpicks, but the project overall is very cool. Sounds like they solved a lot of hard tech problems and executed well on the ops.