How do you compare software architecture patterns?

While identifying or finalizing any design patterns or principles we should always focus on performance and code maintenance in long run. That the key. There might be other interests as well like security, testability etc which are specific to applications but thinking about performance and code maintenance is the key to sustain the software in long run.

When choosing design patterns, emphasizing performance and long-term maintenance is paramount. While aspects like security and testability matter, the emphasis on performance and upkeep ensures software longevity. Architects must understand that different patterns highlight diverse quality attributes due to inherent design nuances. The right pattern choice requires aligning these nuances with the project's needs and limitations. To compare patterns effectively, pinpoint the project-specific quality attributes. Since every project has unique goals and audiences, assessing how a design impacts these attributes is critical to optimal architectural decisions.

QA or NFR are essential part of Architecture. Each Strategic Design has NFRs associated, NFR are measured through Scenarios & Tangible/Measurable out come. You can compare Architecture through NFRs & measurable outcome.

Architectural patterns are not one size fits all. Different patterns are focused on solving different problems. Quality attributes are indeed important to consider while comparing architectural patterns. Between monoliths and microservices, a monolith could still be a better choice in terms of performance if you cannot afford additional latency or communication overhead. From a simplicity and maintainability standpoint as well, if you don't have enough budget or resources, then a monolith architecture could still be a better choice. The same applies to other architectural patterns, such as choosing between client-server and P2P architecture

It's imperative to thoroughly analyse the project's requirements, constraints, and goals before deciding on an architecture pattern. Monolithic architectures are often simpler to develop & test but might suffer from scalability and maintenance challenges. Microservices offer flexibility and scalability at the cost of increased complexity. Event-driven architectures are well-suited for real-time and highly responsive systems, but they introduce challenges in maintaining event consistency. Further, hybrid approaches that combine elements from different patterns can also be used to address specific needs and strike a balance between trade-offs.

Without thinking of NFR, design is not complete. But scope of NFR has become very subjective and most ignored element in design process. Now a days, each product is having some kind of cloud touch, it is mandatory to have design in place to control cloud wastages thereby its not only saving cost but carbon footprint to help reducing environmental issues. With that said, I recommend to incorporate observability, predictability, telemetry in design for accurate and timely business decisions. In long run, it will help to have self-healing in place and also help saving engineering effort on unused features etc. Such savings contribute to profitability by reducing operational cost. Also frees up the team to focus on most important things.

Architects must acknowledge that various architecture patterns prioritize distinct quality attributes due to their inherent assumptions, constraints, and design choices. Selecting the appropriate pattern for a project requires comprehending these trade-offs and aligning them with the project's unique needs and priorities. To make well-informed decisions while comparing architecture patterns, it is crucial to pinpoint the most vital quality attributes for the specific software project. Each project may have distinctive focuses based on its intended usage, target audience, and business objectives. Assessing how each architecture pattern bolsters or hampers these prioritized attributes is vital for making optimal architectural decisions.

Agree on "different architectural patterns emphasize different quality attributes" since it is common for decisions to have some kind of trade-off (to improve this we may need to reduce that). But it doesn't mean we sacrifice (by purpose) one of the attributes because we actually need all these qualities. In the case of Microservices Architecture (MSA), scalability is an attribute of quality that is supported (easy to do) by (architecture) design, needs a little extra work for interoperability (service communication), and maybe a different approach for testability (integration-test). Nevertheless, we need to make sure that the architecture keeps relevant to the product and organization for their growth (continuous/evolutionary design).

Architectural styles are flexible design toolkits, each with its benefits and trade-offs. Savvy architects meld these styles to fit unique project needs. Technologies sometimes dictate preferred architectures. Utilizing native features accelerates development while forcing unfit architectures adds complexity. It's a good idea to follow platform-specific best practices before diverging. No one-size-fits-all exists; projects demand varied patterns. Balancing pattern combination, development speed, and stability creates a masterful design.

In reality like humans, every application is unique and need todo some customization for architecture patterns. The best architecture design is the design which can easily adopt or connect with other architecture patterns and respect the communication.

Some technologies require leaning towards a certain architecture or set of architectures that best fit that technology. A clear example to that is mobile development, where native technologies provided by technology owners (Apple and Google) are favoring certain architectures (ex: MVVM for Android). Making use of what is provided natively boosts development speed, while enforcing a certain architecture that is not meant for those platforms could produce a lot of unneeded complexity. It's always wise to follow the guidelines and common practices of a certain platform before taking a bold decision to break out of the fence.

Architectural styles are High level Strategic Decision which are Important Decisions, costly & Hard to change. In Beginning of Project, It is considered well thoughtfully. It is impacted by Domain, Business Drivers and Organization. Architectural styles impacted by Data Storage, Usability, Performance etc Testability of Architecture.

It is essential to view architectural styles not as rigid templates but as a toolbox of design principles. Each style offers a set of benefits and trade-offs, and a successful architect knows how to blend these styles creatively to meet specific project requirements.

If I want to talk about this I'll write it in one sentence: Architectural styles provide the high-level guidelines for structuring a system, and architectural patterns offer practical implementations that demonstrate how to apply those guidelines in real-world scenarios.

There is such a thing as the best (architectural) style. Every pattern is a specific suggestion for a certain problem (sometimes with a particular philosophy). Understanding is really crucial part of adoption. Over-engineering is the same dangerous (if not more) as not using any design.

Design principles, no matter which are chosen, will mirror the team's structure as per Conway's Law. If system architecture clashes with organizational structure, the organizational structure always prevails. Thus, aligning your organizational framework with your design is imperative.

Design principles is part of Architecture Governance. Define principles that guide developers to take tactical or local(narrow scope) decision. It helps to follow Key Design Decisions. Well Defined Design principles help to Avoid Architecture Erosion & Identify tech debt if introduced. E.g 1. Avoid UI to Data layer accessibility. 2.Promote good practices. e.g central memory release management. 3. Use certain type of data structure. 4. Dependency Injected. 5. Use Central Domain Object lifecycle management. 6. Loosely couple components. Extensible or Replicable component. 7. Use appropriately Late binding vs Compile time binding. 8. Design Testability.

I firmly believe that design principles are the bedrock of successful software architecture. The challenge lies in knowing when to apply, bend, or even challenge a design principle. Blindly following principles without considering real-world scenarios can lead to suboptimal outcomes. The goal is to achieve a balanced, sustainable architecture that supports the system's growth and evolution.

Behavior is not defined by great achievements, but by habits, and habits are made of details. Design principles, just like habits, will shape the overall system on how it should be understood rather than what it is.

Common examples serve as invaluable illustrations of how architectural patterns operate in real-world applications. These instances provide tangible insights into the advantages & trade-offs associated with each pattern within technologies & settings. Consider the following common examples: Netflix for Microservices: This exemplifies the microservices architecture in action. WordPress for Monolithic: WordPress serves as a classic example of a monolithic architecture. Twitter for Event-Driven: Twitter's event-driven architecture demonstrates how real-time updates and notifications can be efficiently managed using this pattern. Each architectural pattern finds practical application in various domains, platforms, and markets.

Common examples often refer to someone or a group of people who once dared to explore a way of doing with enough exposure, which then became a reference point for that practice.

Project-specific attributes could lead to more realistic choices. For example, a low-budget tight-timeline project could lead to a simple architecture which might not necessarily focus on full extensibility. Such a tradeoff must be explicit for stakeholders during decision making. Also the size of the team and the expected growth rate of project features could be more factors to consider. Applying a multi-layer architecture on a one-developer POC might not be a wise decision.

Comparison matrix by attributes helps budding architects to use the best of architecture. Example:Microservie is easy to manage but complexity increases.

The patterns and the choice of tech stack affect whether your design follows "evolutionary architecture" principle. Keeping those principles in decision tree would allow to skip many mistakes when project is growing Even more, whether design defines small project or enterprise scale endeavor, the future-prof solutions would pay back pretty soon just because its side effects would align the development lifecycle, infrastructure and many other aspects in compliance with modern industry practices.