Know your technical debt, the understanding and management of which is key for a sustainable architecture. Lack of awareness of technical debt will eventually result in a software product that cannot respond to new feature demands in a cost-effective manner.

We recommend leveraging the utility tree technique from the architecture tradeoff analysis method, or ATAM.15 Documenting architecture scenarios that illustrate quality attribute requirements is a key aspect of this technique. 15. Software Engineering Institute, Architecture Tradeoff Analysis Method Collection.

Continuous Architecture states that the unit of work of an architect is an architectural decision.

Drive architectural decisions, which are the primary unit of work of architectural activities. Continuous Architecture recommends explicitly focusing on architectural decisions because if we do not understand and capture architectural decisions, we lose the knowledge of tradeoffs made in a particular context. Without this knowledge, the team is

A simple but good example for such an architectural principle is “Buy before build.” It has the following characteristics that make a good principle: Clear: Principles should be like marketing slogans—easy to understand and remember. Provides guidance for decisions: When making a decision, you can easily look to the principle for guidance. In this

Consequently, we must design our systems with recovery from security incidents in our mind and must think about preventing the incidents in the first place. We discuss system resilience in Chapter 7, but from a security perspective, an important part of ensuring resilience is to work closely with the security specialists and SOC personnel while

Implement feedback loops, which enable us to iterate through the software development life cycle and understand the impact of architectural decisions. Feedback loops are required so that the team can react quickly to developments in requirements and any unforeseen impact of architectural decisions. In today’s rapid development cycles, we need to be

Let us briefly touch on the concepts of data science and data engineering. If we go back to the DIKW triangle, we can say that data science focuses on extracting knowledge and wisdom from the information we have. Data scientists combine tools from mathematics and statistics to analyze information to arrive at insights. Exponentially increasing

As software engineers and architects our job is to try to use our technical and logical thinking skills to identify which is which and to challenge those that are not useful. Which activities help us to really be secure and which are outdated or simply useless “security theatre”? If we don’t do this then all security activities will be devalued and