How can you align programming language choices with stakeholder needs in Systems Design?

To start, it's essential to gather requirements for the system by talking to stakeholders and figuring out what the system needs, such as performance, security, and user interface. Next, you should analyze the problem space to decide which programming language to use; for data-heavy tasks, Python or R could work, but for real-time systems, C++ or Rust might be better. Think about long-term maintenance, as some languages are easier to maintain, so pick one that fits your team's skills and the future. Also, consider scalability needs; if the system will grow, look into languages and frameworks that can handle it, like Node.js for web apps or Go for microservices.

As what my great mentor Matt Whiteley once told me, as long as it works don't sweat the small stuff. Understand the requirements well. And ship a working product (up to certain standards of course). We may tend to over-engineer things during the beginning rather than just getting it to work exactly as needed. Of course, we mustn't forget to strive to find a technology stack that is up to modern day standards, maintainable, and cost effective!

Since the question is specific to programming language, I will try answer to answer it from business and technical stand point - Select a language which is mature in terms of support and resources available. - Also depends on What resources are available at your disposal, Do we have the people who know the language or do they need to be trained which ties in with how fast do you want to get the product to the market. - As others have mentioned language is a tiny detail in a product but needs to be chosen wisely. For example if we are building a real time chat a good language selection would be Node JS in my opinion.

Aligning programming language choices with stakeholder needs in system design is crucial. Understand stakeholder requirements, consider technical constraints, evaluate team expertise, and balance performance, scalability, and development time. Assess maintainability, community support, security, and compliance. Keep stakeholders engaged throughout the process to ensure alignment.

A thorough analysis of the problem domain unveils essential features and challenges. These insights for direction, for instance, Golang could be ideal for performance-intensive tasks, while Python may excel in data processing and analysis. Ultimately, understanding the problem domain simplifies and refines your choice.

When evaluating details around crafting solution, the development team needs to take their develope hat off and need to put their solution hat on. An application or a solution developed with best, latest or optimal tools/service is not necessary the best solution for the client. The solution should be able to get the required task done with simplicity and ease. This should be the most focused goal towards creating a resolution for client. To orient this approach with the current available skillset of development team; that is what drives the project to success or its struggle.

I feel this will become antiquated with time because AI allows code to be translated with a high degree of accuracy. Really, programming is simply sequential statements, decision statements, and logical statements. If you understand that much, you can be pretty dangerous with a generative AI. Translating between programming languages shouldn't be an issue in this day and age with AI to assist. The data structures, the concepts, and the semantics are what is important going forward with many projects in my view.

The programming language choices can be aligned with stakeholder needs in system design by engaging with stakeholder’s team. One needs to understand thoroughly the project's goals and requirements from business analysts, project managers and end-users. The skills and expertise of the development team is evaluated and considered to choose a programming language. Naturally a team who is comfortable with a language will deliver more efficient and quality product. The performance and scalability requirements of the system should be also be considered to align programming language choices with stakeholder needs in system design for high-performance, real-time systems or web applications or data processing tasks.

We always want the best or right approach but let' consider how many failures it might take to get there. Expertise comes through many lessons learnt. If you aren't willing to experiment and fail you will never be able to say "This is the way" with absolute certainty. Likewise, you might not offer your team the correct guidance if you hadn't gone down the wrong way before. Be willing to experiment, and fail fast. Embrace failure and you'll be able to add massive value to future projects.

Active listening to feedback is key. It can help one to truly learn the stakeholders' needs and desires. Make sure voices are heard and they know you value feedback.

Engaging with the stakeholders and involving them in the decision-making process by discussing the pros and cons of the programming language's choice and how they can relate to the project goals. The choice should be made based on several points not only on the views and user friendly, but overall the decision should be made based on the whole vision of the software lifecycle and the mission behind the project, it should be considered from the beginning, since we don't know if the project will live for years or decades, the maintenance could be different than a project of months.

In principle, don't even raise terms like "C", "C++", "JavaScript" or "Swift" in your conversation with stakeholders such as clients. You will be speaking a foreign language. If you feel confused while explaining something, how do you think your stakeholders feel? Respect your stakeholder's time and learn how to speak on the same level as them. Being a software engineer we might find ourselves in a kind of "technical lingo echo chamber" where we always have all the technical answers, estimates and solutions. It's a skill to learn how to get out of that mindset when speaking to stakeholders. E.g. "Stakeholder: our users cannot register. Engineer: the token has expired." That isn't helpful. It's important to enter into their shoes.

When evaluating trade-offs, balance performance, scalability, maintainability, and ease of development. High-performance languages like C++ or Rust offer speed but increase development time, while Python or JavaScript enable rapid development at the cost of performance. Languages like Java or Go scale well but may be complex to learn. Strongly-typed languages like C# or Java boost maintainability but require more initial effort. Consider community support, developer availability, and the language's long-term viability to ensure the choice aligns with both immediate and future needs.

No technology is perfect. Everything has some tradeoffs that we must do wisely. For example, the Laravel framework in PHP offers a good developer experience and rapid development times but is very fat. Also, PHP is also an interpreted language just like NodeJS which would run slow whereas Java and ASP .NET are compiled languages having greater speeds. We also look at how integrating different technologies is easier and more reliable with the chosen framework. For example, JSON with PHP and Python is slower so MongoDB is not a good option. To sum up, we have to define an architecture that integrates well and provides the required scalability, security, and robustness level required by the client as well as possible to deliver on time.

Micro-services is an interesting angle here. There was a popularized idea of building micro-services written in a variety of "best-suited" languages. Careful! The end result of a large variety of "pros" may result in one large "con" which is maintainability. Uber ran into large trouble with the above approach when over 1300 micro-services written in a variety of "better-suited" languages resulted in large outages and impossible maintenance. There was no standardized approach. It's better to be consistent even if that means sometimes choosing a less efficient option for some scenarios. Choose one or two core languages your company is proficient in. In addition, implement standards such as documentation for everything and fault tolerance.

Assess the trade-off between programming languages that offer high performance and those that expedite development. Evaluate languages in terms of scalability. Some languages may excel in building scalable systems, while others are easier to maintain. Weigh the costs associated with using specific languages. Some languages may require expensive licensing or specialized expertise. Consider the strength of the programming language's ecosystem and community support. Examine how well a programming language supports security and compliance requirements. Evaluate whether the chosen language aligns with existing systems and technologies in use by stakeholders.

Evaluating tradeoffs is key. Architectural criteria will often not be the same amongst projects and stakeholder groups. Be sure to find a great balance with the tradeoffs to ensure business goals, functional requirements, and stakeholder needs are met.

Select testing frameworks and tools that are compatible with the chosen programming language. Ensure that these tools can effectively validate the system's functionality and meet stakeholders' quality expectations. Use unit testing, integration testing, functional end to end testing, performance testing, and security testing.

as we design a system to solve a problem, the priority is to understand the problem as a whole, and this is an iterative process, because it’s very rare that we can understand a problem entirely before working on it. It’s fundamental to validate as early as possible the solutions are effectively in sync with the stakeholder’s expectations, and we can achieve this by prototyping. Sometimes it’s worth to make a trade off with the language prototyping capabilities to decrease risks.

When making an architecture we start with a Proof of Concept. We select the different proposed architectures and tech stacks and make pilot projects with smaller services. Once we make a POC of the components of the system, we have to benchmark the performance. For the front end, we can go with a subjective user experience score included in the benchmarking. After this decision is very easy and the pros and cons of using a specific architecture become clear.

If there is time it is nice to build prototype of the system and perform load testing to ensure that the chosen approach can handle the required amounts of data. Information systems today are increasingly more and more data driven, meaning that every other system produces huge amount of data from the global usage.

Hiring Philosophy: Prioritize hiring individuals with a problem-solving or "hacker" mindset. These individuals are likely to be adaptable and open to experimenting with different technologies to find the best solution. This mindset can be considered a valuable resource in itself. Language Experimentation: Be open to trying and prototyping with various programming languages to assess which one aligns best with the system's needs and requirements. This iterative approach ensures that you are not confined to a particular technology and can make informed choices.

One addition that is missing in this article is that there are experienced people who can tell you which tech stacks can be used to build your system based on your requirements and their experience and knowhows, as opposed to regular software developers who rarely deal with building systems from scratch. Architect position requires keeping up with the newest updates in all the various things related to system design, be it databases or cloud technologies.