Deployment Diagrams

Deployment is everything that happens between writing software and actually using that software by its intended users. And as we get more software and more users, deployment becomes more complex. Why deployment diagrams? Deployment diagrams are a great technique for communicating about important decisions in deploying software. Decisions such as who is going to do what, how are things connected, and so on. There are many ways to draw deployment diagrams and many standards to choose from. UML and Archimate are just a few of them. To me, there is no single right way to create deployment diagrams. In that sense, these diagrams are more like maps. And the usefulness of a map depends on the journey that you are going to make. A map for a mountain walk is pretty useless if you want to make a railroad journey and vice versa. ...

March 9, 2025

What are AI Digital Infrastructures?

The AI landscape has many digital infrastructures. Let’s explain this step by step and focus on which data is stored where and how it is processed. A core element of AI systems is a trained model. This is especially true for the dominant form of AI these days: deep learning neural networks. A trained model is the result of processing a lot of training data by a specific neural network. These models are fixed in size, but typically very big. The smallest useful models are close to a gigabyte, while recent public chat models run into multiple terabytes. LLM training costs hundreds, thousands, or more hours of compute time on specialized hardware. ...

March 8, 2025

AI Roles and Responsibilities

AI systems, like most cloud systems, are composed of models, servers, software, and more, each of which can be provided by a different role. We follow the roles outlined in the CSA AI Controls Matrix (AICM). Each role also has promises associated with them (read more on promise theory here). Together these run AI systems, from image recognition systems to Large Language Model based customer support systems. AI Customer (AIC) End users of AI applications. This includes the actual users as well as their organizational units. Even though they are only providing a service to themselves, they are still responsible for certain security and control functions. Some of responsibilities are in the interest of their providers, and those are typically included in an AUP (Acceptable Usage Policy). For example, customers should maintain appropriate authorizations of users, and refrain from overloading their providers. Customers are also responsible for the business use of the data that is returned by the AI application. ...

August 26, 2025

A Unified Framework

The units so far have explored quite a few, seemingly unrelated, concepts and observations. Here we’ll embed them in a unified framework that illustrates how they fit together. From the title of this book you can see that the main pillars of that framework include value, power, and risk. To get there, we need a fourth pillar: change. For now, we’ll call these pillars layers, though there is no implied hierarchy between them. ...

May 12, 2025