How to Choose the Most Appropriate Architecture for Your Software Products
When developing a new project, we often gravitate toward certain technology stacks for various reasons. Throughout my career, I've noticed that one of the most common motivations is simply following trends - similar to what happens in fashion or entertainment. Developers and companies always want to use what's new and trendy.
In software engineering, this can be dangerous - actually, it is dangerous. Just check X (formerly Twitter) and you'll see hundreds or thousands of developers using the newest framework or tool that comes out every weekend in Web Development. While this drives innovation in certain ecosystems, I want to focus on explaining why this approach is risky when developing software professionally.
The Stability Factor
The primary reason large companies move slowly in adopting new technologies (besides their bureaucracy) is stability. A company won't invest hundreds of thousands or millions of dollars in a library or framework that might disappear months after its launch. So they often opt for older but stable technologies, which creates another problem - their technical debt becomes enormous as time passes.
How to Solve This Dilemma?
Imagine you're a project leader at a company, and they ask you to determine which stack, architecture, and work methodologies to implement for a specific project.
This is where a technical leader must be pragmatic and set aside personal preferences, focusing solely on finding tools that solve the problem in a scalable and maintainable way, regardless of trends.
Software engineers tend to follow trends believing that using the latest X technology makes them smarter than other engineers - many suffer from ego problems. A true software engineer, in my humble opinion, is someone who can set aside this ego and adopt what I call an "Eternal Student" mindset - always seeking continuous improvement, emptying their cup, and staying ready to learn new things and adapt to the changes this profession brings.
Focus on Business Value, Not Technical Preferences
With this mindset, the questions you should ask when choosing tools and methodologies must be oriented toward solving the problem with minimal effort without sacrificing the maintainability and scalability of the project's architecture.
According to recent trends reported by InfoQ, complex analytical platforms and ML models are no longer considered secondary components as they shift towards becoming core parts of transactional systems. This means your architecture decisions need to account for data as a major force.
Studies have shown that even with all the investments in automation, shifting left, full-stack development, and AI tools, developer productivity continues to plummet year after year. Until teams start proactively managing not just simple source code tech debt but deeper architectural technical debt, we'll never improve developer productivity.
The Microservices Trap
This is precisely why I'm against Microservices in the vast majority of cases. This architecture adds a layer of complexity that in many (or all) instances creates too much work that's very difficult to justify.
Hence the internet memes: "My 10-service architecture with Kubernetes is ready for my two active users."
A Real-World Example
As described in the case study of a WhatsApp CRM development, one founder realized that talking to real businesses using WhatsApp revealed they were struggling with clunky interfaces, wasting time managing conversations, and missing opportunities because their tools weren't adequate.
The irony is that while developers obsess over architecture decisions and code quality, most users couldn't care less about beautiful microservices or elegant code patterns. They just want something that makes their work easier and helps them close more deals.
Making Better Choices
When considering architecture options, remember that your choice depends on project needs. For simpler applications with well-defined requirements and smaller teams, a monolithic approach might be appropriate. For applications requiring scalability, designs like Actor Model or Modular Monolith could be a good option.
The software as a service (SaaS) market was valued at $261.15 billion in 2022 and is predicted to grow at 13.7% annually through 2030. This growth demonstrates the importance of choosing architectures that allow for subscription-based delivery models when appropriate.
Conclusion
A wise architect is one who can set aside their personal biases and evaluate each project's unique requirements. Sometimes a monolith is the right answer. Sometimes microservices are justified(in rare cases). The key is to constantly educate yourself on emerging patterns while maintaining a pragmatic approach to selection.
The best engineers are those who remain "eternal students," always ready to learn and adapt, making decisions based on what will truly solve business problems rather than what will impress others.