Architectural Decision Records - A Guide to Better Software Decisions

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Earlier in my career, I realized that the way software was built in industry projects was often based on personal opinions and tastes. For example, familiarity with frameworks, programming languages, and deployment pipelines. As I advanced in the software development lifecycle, I came across this standard that focuses more on what needs to be done and the alternatives that might exist to tackle the same problem.

Moving to a discussion based on pros/cons and architectural features leads to a shared goal and understanding of what needs to be done and how it will be done. Architectural Decision Records (ADRs) come into play to facilitate the dynamics for teams to make decisions that are important and cannot be changed in an afternoon (Brown, 2014).

Throughout ADRs and their different templates, it is possible to discuss and put into perspective different profiles that need to be involved in the decision-making process for architectural changes.

What is the problem with taste

As normal as it might sound, personal preferences exist and they should not be avoided but rather controlled. This is because they get in the way of focusing on the objective that the architectural change needs to accomplish.

Favoring taste over objective measurements and options leads to a poorly defined metric or change that might not fulfil the needs of the architecture that aims at targeting the business impact.

It comes from different places, but in my experience most personal tastes come from one’s own experience. Experience is important and should not be neglected. However, when it gets in the way by lacking arguments to defend one idea over another, it is time to evaluate again whether taste is coming first instead of the solution.

Why ADRs

The reason ADRs became part of my daily work is their simplicity and effectiveness in structuring architectural discussions. They provide a lightweight way to explore ideas, focus on the proposed change, and evaluate the pros and cons of different approaches(Van der Ven et al., 2006). Beyond just comparing alternatives, ADRs also offer a space to propose concrete implementation strategies, helping teams align on how a decision will be executed. Importantly, they shift the conversation from personal preferences such as “I prefer X” to reasoned arguments based on context, trade-offs, and long-term impact.

ADRs play a crucial role in improving communication within the team. By documenting decisions in a shared, accessible format, they ensure that everyone understands the rationale behind key architectural choices(Tyree & Akerman, 2005). This transparency fosters trust, reduces misunderstandings, and promotes a culture of shared ownership. Rather than relying on memory or verbal agreements, teams can refer to ADRs as a single source of truth to stay aligned and make informed future decisions.

Knowledge Preservation and Team Scalability

One of the most significant benefits of ADRs is their ability to preserve architectural knowledge over time(Kruchten et al., 2006). Software projects often suffer from knowledge loss when team members leave or when decisions are forgotten. ADRs act as a form of architectural memory, capturing not just what was decided, but why it was decided and what alternatives were considered. This is particularly valuable for onboarding new team members, who can understand the evolution of the system architecture by reading through the decision history.

Research shows that architectural knowledge vaporization is a real problem in software projects(Shahin et al., 2014). When important decisions are not documented, teams often rediscover the same problems, repeat past mistakes, or inadvertently violate architectural constraints. ADRs mitigate this by creating a traceable decision history that survives organizational changes and team turnover.

Improved Decision Quality

ADRs encourage more thorough decision making processes. When teams know they must document their reasoning, they tend to consider alternatives more carefully and evaluate trade-offs more rigorously(Zimmermann et al., 2009). The act of writing forces clarity of thought and helps identify gaps in reasoning before decisions are finalized.

Moreover, ADRs facilitate asynchronous decision making, which is increasingly important in distributed and remote teams. Stakeholders can review proposed decisions, provide feedback, and contribute their perspectives without needing to be in the same room or time zone. This democratizes the decision making process and ensures that diverse viewpoints are considered.

Alignment with Modern Practices

ADRs align well with modern software development practices such as continuous delivery and DevOps. They can be stored alongside code in version control systems, reviewed as part of pull requests, and evolved iteratively as understanding deepens(Woods, 2016). This integration into existing workflows makes them more likely to be adopted and maintained over time.

Furthermore, ADRs support agile principles by documenting “just enough” architecture without creating heavyweight documentation. They strike a balance between no documentation which leads to chaos and excessive documentation which becomes outdated and ignored.

ADRs history

Before ADRs, architectural decisions were often:

• Discussed verbally or in meetings
• Scattered in emails or chat threads when recorded at all
• Stored in different formats across multiple tools
• Maintained as many sources of truth for the changes done

ADRs were popularized by Michael Nygard (Documenting Architecture Decisions). They provide a lightweight, structured way to capture key architectural choices, the context in which they were made, and their consequences.

The motivation behind ADRs is to avoid losing the reasoning behind important decisions—especially as teams grow or change. Rather than revisiting the same discussions or repeating mistakes, teams can review past ADRs and understand what led to a given decision.

ADRs are de facto standard in many engineering teams. They are used to onboard new developers, revisit decisions, and align architecture with business needs. Often integrated into pull requests.

ADRs in practice

ADRs are typically written in Markdown and stored in a version control system (like Git). They can be organized in a directory structure that reflects the project’s architecture or decision-making process. The following is an example of such a structure:

docs/
  ├──
    adrs/
      ├── 0001-background-processing-of-heavy-workload.md
      ├── adr-template.md

The first file is the ADR itself, while the second one is a template that can be used to create new ADRs. GitHub hosts one of the most popular ADR templates, which is a simple Markdown file. Each template has a title, a status (proposed, accepted, rejected, etc.), and a context (the problem being solved). However, they differ in the number of sections and the level of detail. At this same place, there is a list of ADR examples, such as Monorepo vs multirepo, Programming languages, Environment variable configuration, etc.

I personally prefer to use the MADR project template as a base and add sections that I find useful for the project I am working on. Often, I add sections with proofs of concept and pieces of code to compare options.

Resources

• Why you should be using architecture decision records to document your project
• A personal project built to edit ADRs
• Design It!

References

1. Brown, S. (2014). Software Architecture for Developers (1st ed.). https://leanpub.com/software-architecture-for-developers
2. Van der Ven, J., Jansen, A., Avgeriou, P., & Hammer, D. K. (2006). Using Architectural Decisions. 10.
3. Tyree, J., & Akerman, A. (2005). Architecture Decisions: Demystifying Architecture. IEEE Software, 22(2), 19–27. https://doi.org/10.1109/MS.2005.27
4. Kruchten, P., Lago, P., & van Vliet, H. (2006). Building Up and Reasoning About Architectural Knowledge. Lecture Notes in Computer Science, 4214, 43–58. https://doi.org/10.1007/11966104_4
5. Shahin, M., Liang, P., & Babar, M. A. (2014). A systematic review of software architecture visualization techniques. Journal of Systems and Software, 94, 161–185. https://doi.org/10.1016/j.jss.2014.03.071
6. Zimmermann, O., Koehler, J., Leymann, F., Polley, R., & Schuster, N. (2009). Managing Architectural Decision Models with Dependency Relations, Integrity Constraints, and Production Rules. Journal of Systems and Software, 82(8), 1249–1267. https://doi.org/10.1016/j.jss.2009.01.039
7. Woods, E. (2016). Software Architecture in a Changing World. IEEE Software, 33(6), 94–97. https://doi.org/10.1109/MS.2016.144