What Really Makes a Good Tech Stack

Technology is omnipresent today, and in the world of software development, hardly a day goes by without a new framework, programming language, or tool being hyped. But while many developers make decisions driven by the hype, the true value of a tech stack often lies in unglamorous factors: maintainability, simplicity, team compatibility, infrastructure suitability, and the reality of day-to-day operations.

In this article, I share my personal perspective on technology decisions based on over ten years of professional experience in web development. I want to demonstrate that a good tech stack doesn't consist of the latest and most popular tools, but of those that make a project sustainable, efficient, and well-maintainable in the long run.

How I choose tools for my tech-stack

My decisions for or against specific technologies are based on a clear set of criteria – independent of trends or what’s currently going viral on Hacker News. Instead, I systematically ask myself the following questions when evaluating a tool:

  1. Maintainability: A tool is only as good as its long-term maintainability. I ask myself: Is it actively developed? Are upgrade paths between versions clear? Is the code structured in a way that someone else can quickly understand it in six months' time? Maintainability also means: few "magical" shortcuts, transparent state management, and the ability to solve problems using common sense.

  2. Documentation: Documentation is more than a manual – it's a benchmark for professionalism. I check: Is it up to date? Are there examples of real-world use cases? Are common pitfalls mentioned or glossed over? Tools like Tailwind CSS excel here because they not only offer function references, but also visual previews, code examples, and clear explanations behind design decisions.

  3. Community and Ecosystem: An active community means more than just answers on StackOverflow – it also includes ecosystem health: plugins, integrations, and extensions. Who are the maintainers? If a library has issues – how quickly do maintainers respond? Are there well-maintained alternatives that integrate seamlessly?

  4. Productivity: A tool is good if it helps me reach my goals quickly – without sacrificing code quality. I measure this by how many standard problems I can solve using built-in features – without having to search for 15 plugins or convoluted workarounds. Otherwise, it may not be the right tool for my use case after all.

  5. Team and Project Context:: Decisions are never absolute. What’s perfect for a solo project can cause chaos in a team. I ask: Does the tool require prior knowledge, or is it intuitive to use? How well can roles (e.g., frontend vs. backend) be separated? And: What does onboarding look like for new team members? What skills are present in the team, and at what level?

  6. Infrastructure and Operation: Tool choices don’t just affect coding – they also impact operations. I look at: Are there existing Docker images? How well does the tool integrate into CI/CD pipelines? How easy is it to set up monitoring? What about logging, scaling, and backups? A tool that feels great locally but causes deployment issues regularly is not viable in the long term.

  7. Learning Curve and Exit Costs: An often underestimated factor: How much time do I need to invest before I become productive with a new tool? And what happens if I need to switch later on? Are there migration tools? Can data or structures be exported? I tend to avoid proprietary solutions with high lock-in potential. Instead, I prefer tools that use open standards or well-separated layers.

  8. Stability and Maturity: A tool can be powerful – but if the API changes fundamentally every three months, it's a no-go. I analyze release notes, GitHub issues, and SemVer compliance. How many breaking changes were there in recent releases? Is there a clear roadmap? Are there tools that assist with upgrades? Mature software is predictable and doesn’t introduce a new paradigm every six weeks.

  9. Licensing and Legal Clarity: Especially for commercial projects, I check the license: Is it compatible with my business model? Who stands behind the tool? Are there financial backers, and in what form? What is the maintainers’ stance on commercial use?

  10. Personal Experience: In the end, it also comes down to: Do I really know the tool? Have I tested it in practice – not just in a tutorial? Can I explain it to someone else? The better I understand a tool, the more confident I am in using it – which benefits the project. Gut feeling doesn’t replace analysis, but it's an important filter after all the objective criteria.

With these criteria, I evaluate new tools not in isolation, but in context. A "cool" tool that only performs well on a few of these questions has a hard time competing with a "boring", but stable and proven piece of software.