What's your approach to designing software architecture that is both scalable and maintainable over the long term?

I have been active Developer/Architect on Salesforce ecosystem over 12 years, Here are the key topic that you might want to consider on maintenance and scalability.
1- Embrace the change :  

There is one thing that can not change is the change itself, business processes are being evolved and getting complex and complex, tailored to the core and needs. Therefore focus on adaptability and implement declarative solution whereas possible

2- Bulkification :

It might be a simple term when you are dealing with enterprise data but it is key foundation of scalability. Implementation should always consider bulk data in context. It is in fact sometime bounded to database design , it has to go hand to hand.
 

3- Idempotent design :
Maintenance is super costly activity when it comes to enterprise level system, Idempotent design are super crucial in order to make maintenance easier. Separating domain and service level jobs and single responsibility considerations are pillars of strong and easy maintenance.

4- Monitoring:
This is must. In general NFRs are must to have thing whatever you design, But be cautious about  what you are logging, relevant, understandable and traceable loggings are crucial.

My strategy focuses on creating designs that allow for development and scaling of different parts of the system independently. I place importance on having organized interfaces and comprehensible documentations that stick to established design principles. Using microservices can improve scalability while keeping an eye on monitoring and feedback mechanisms helps the architecture evolve over time to uphold performance levels and make updates smoother. 
 

I often adhere to a few fundamental ideas when creating software architecture that must scale and remain maintained since they have worked successfully for me in the past, particularly on projects whose scope significantly expanded after launch.

Begin with a basic yet organized
I make an effort to avoid over-engineering at first. In order to allow individual components to change without having to completely redo everything, I try to keep everything modular and disconnected. This entails appropriately separating concerns, such as utilizing services or handlers in place of controllers for business logic.

Prioritize clarity above cunning.
Overly optimized solutions that save a few lines are more difficult to maintain than readable code. I understand the value of simplicity because I've inherited enough disorganized codebases. In order to improve the communication of the code itself, I usually modify anything that requires a remark to clarify its purpose.

Make good use of layers.
I divide the system into distinct layers, such as data access, display, and domain. This facilitates the integration of caching, APIs, and even future front-ends. When it makes sense, I also use Domain-Driven Design (DDD) principles in larger projects, particularly when defining boundaries between system components.

Create with change in mind.
Despite careful planning, requirements are subject to change. Therefore, I concentrate on creating things that are adaptable and simple to expand. For async processes that may eventually scale, this may entail the use of interfaces, feature toggles, or message queues. Even within a monolith, I also attempt to steer clear of close coupling between services.

Automate and observe beforehand
In the early stages of development, it is simple to ignore testing and monitoring. However, I've seen that even simple logging and unit testing can save hours of debugging in the future. As the project develops, I often add coverage gradually after setting up lightweight CI/CD from the beginning.

As you proceed, refactor
Scalability encompasses more than just managing traffic. It also concerns how simple it will be for the next developer—or myself in the future—to incorporate a feature without causing any issues. Refactoring, in my opinion, is a typical step in the development process rather than something you do only when the code becomes "bad."

Select the appropriate tools for the task.
I base my decision on the team and the situation, but some tech stacks scale better than others. For instance, I've used Go for services that require a lot of performance, Laravel for projects requiring complicated administrative tasks, and Node.js for quick APIs. Designing with your limitations in mind is crucial.

Last reflection
I make an effort to plan ahead, not only for how the app functions now but also for how it might appear in six months if usage doubles or the product changes. Although it need not be flawless, the architecture should allow for expansion without requiring frequent rewrites.

Having that mentality has enabled me to create systems that, even after being worked on by several teams, remain reliable and change with the product.

I use a principles-first approach to architecture: I identify what components are necessary, and what their "virtues" are, e.g. speed, durability, availability etc. I keep notes on priorities and trade-offs; as a project progresses, I aim to keep things consistent with previous choices. Sometimes major changes are warranted, but it helps to know what will be impacted (and how).

I'm careful when picking (external) tools, libraries, frameworks, services etc; they should be actively maintained, well documented and aligned with my goals and designs. I tend to pick low-level things that do one thing and do it well.

Abstractions are good, but only in moderation; e.g. not everything needs to be a separate module, but all code should be easy to move and/or reimplement, as needed.

I have been in software engineering for over a decade, I’ve learned that scalable and maintainable architecture starts with clarity and restraint not over-engineering from day one.

My approach usually begins with understanding the core business requirements. I focus on building something that solves the problem today but is modular enough to adapt tomorrow.

When it comes to scalability, I lean towards horizontal scaling and stateless services where possible, with well-defined APIs. For maintainability, clean code and strong documentation are the keys, but more than that, it’s about clear ownership, sensible conventions, and consistency across the codebase. 

Starting with a well-structured monolith is often underrated but can go a long way if done right.

Don’t overcomplicate in the name of architecture. Keep things clean, modular, and close to real-world logic.

I usually start with a simple monolith, break it into layers properly, and only go for microservices when it really makes sense.

In short: Solve today’s problem, but don’t block tomorrow’s growth.

Designing Scalable and Maintainable Software Architecture: A Long-Term Approach

Rapid, Concise, and Clear as Always – Let’s Dive In!

Modular Design:
Start with a modular architecture, breaking down the system into smaller, independent components. This makes it easier to scale by adding new features or updating existing ones without disrupting the entire system.

Separation of Concerns:
Ensure a clear separation between different layers of the system, such as the data layer, business logic, and presentation layer. This makes maintenance more manageable and helps with debugging and testing.

Microservices Architecture:
For larger systems, consider using microservices. By dividing the application into smaller, autonomous services, you can scale individual parts independently, improving both scalability and flexibility.

Database Scalability:
Choose a database design that allows for scalability, such as sharding or replication. This ensures that the system can handle increased load and data volume without affecting performance.

Code Quality and Documentation:
Prioritize clean, well-documented code. Write clear, consistent documentation and implement coding standards that are easy to follow. This reduces the learning curve for new developers and aids long-term maintainability.

Pro Tip:
Consider adopting an agile development approach to allow for continuous iteration and improvement. Regular code reviews and refactoring also help ensure the software remains adaptable to future needs.

Lorenzo | Casios Visual Studio

Designing scalable and maintainable software architecture requires adherence to clean code principles and a well-normalized data structure. These foundational elements ensure long-term sustainability and scalability. Your project doesn’t have to be perfect from the start, but if you follow these principles, it will naturally evolve towards excellence. However, neglecting them will lead to increasing complexity, making the system unscalable and difficult to maintain over time.

Prioritize modular design, use design patterns, and ensure clear separation of concerns. Leverage scalable technologies, implement proper documentation, and adopt automated testing. Regularly refactor and monitor performance to address evolving needs.