Data harvesting is the automated, large-scale collection of data from sources sensors, cameras, and IoT devices, organized so it can be turned into insight. In modern operations, the speed at…
For decades, IT and OT have run on separate tracks. IT focused on data, applications, and the cloud, while OT kept the machines running on the factory floor. This separation…
Keeping software, firmware, and applications up to date across a large set of distributed sites and devices is becoming one of the central challenges in modern deployment models. As more…
At Avassa, we believe in thinking about the world in abstractions. Specifically, abstractions defined as “a mechanism which permits the expression of relevant details and the suppression of irrelevant details”…
The EU Cyber Resilience Act, or CRA, makes cybersecurity a legal requirement for products with digital elements sold in the European Union. It changes how teams design, build, ship, and…
OEM. Three letters, many interpretations. In this article, we define Original Equipment Manufacturer (OEMs) as a company that designs, builds, integrates, and delivers a complete machine or production system under…
As data volumes continue to grow at the device edge, sending all data to the cloud is no longer feasible. Increasingly large amounts of data are generated at edge locations,…
Kubernetes changed how software is built and operated in the cloud. It excels in data centers with stable networks, elastic resources, and teams that can respond quickly when something goes…
Forward-looking retailers are increasingly relying on an in-store combination of data collection through IoT devices with various types of sensors, AI for decisions and transactions on live data, and digital…
Industrial automation has long relied on hardware PLCs that are reliable but rigid. Control logic is tightly bound to specific devices, updates are slow and manual, and scaling across multiple…