A Linux kernel for each developer team, which uses it to bring up target boards. Bespoke, built, issued, and maintained over years by the vendor. Teams that focus on building great apps, rather than figuring out hardware dependencies. Happy developers that bootstrap smart devices in no time. This is what highly productive embedded systems development should look like. Let’s unpack that vision.

Cybersecurity attacks on industrial IoT solutions can have detrimental consequences. This is the case because IoT devices record privacy-sensitive data and control production assets. Therefore, demonstrable trustworthiness is prerequisite to IoT adoption in industrial settings. Fortunately, IT security is a mature field. Experts have identified classes of threats devices may be subject to. Let’s discuss these threat patterns and mitigation strategies in the IIoT context.

“The King is dead, long live the King.” It might be my french roots speaking, but it seems that actual use cases are replacing King Edge, and it might be for the best. Warning; do not read this blog if you’re particularly sensitive about edge computing (and if you don’t know what this is about, read the “What’s the deal with edge computing?” blog first).

Kubeflow, the ML toolkit on K8s, now fits on your desktop and edge devices! 🚀 Kubeflow provides the cloud-native interface between Kubernetes and data science tools: libraries, frameworks, pipelines, and notebooks. > Read more about what is Kubeflow To make Kubeflow the standard cloud-native tool for MLOps within the AI landscape, the open-source community has accomplished the aggregation and integration of many projects on top of Kubernetes.

The Internet of Things (IoT) is a term for the ever growing number of internet connected devices that fall beyond the realm of your typical laptop, desktop computer or smartphone. Many of us already own and use IoT devices on a daily basis, these could be anything from "smart" versions of appliances like refrigerators, thermostats and coffee machines through to your expected IoT devices such as Amazon’s Alexa & Google’s home speakers.

Downsampling is the process of aggregating high-resolution time series within windows of time and then storing the lower resolution aggregation to a new bucket. For example, imagine that you have an IoT application that monitors the temperature. Your temperature sensor might collect temperature data. This data is collected at a minute interval. It’s really only useful to you during the day.