System Architecture: Tutorial & Best Practices

System architecture is the high-level conceptual structure of a software system, defining its essence, organization, and operations. It specifies interactions between system components to ensure reliable data transmission and processing and to align system behavior with business goals.

System architecture can take various forms, from detailed architecture diagrams to more high-level blueprints. Ultimately, system architecture guides everything from component selection to interface design. Each system architecture decision can profoundly impact a system's performance and design.

There are rarely one-size-fits-all answers regarding system architecture. When designing complex systems, architecture decisions are not binary, and architects must consider a variety of tradeoffs to find effective solutions given business requirements. This article will help teams make quality system architecture decisions by exploring system architecture in depth, including system architecture components, types, and best practices.

Summary of key system architecture concepts

The table below summarizes three system architecture concepts this article will explore in detail.

Components of a system architecture

System architecture is the high-level blueprint of a software system and all its major components and interactions. It encompasses all aspects of the system (e.g., software, hardware, data, interfaces, communication protocols, third-party services/APIs, user interactions, and security layers) to ensure that they work together effectively and efficiently to achieve specific goals.

The graphic above shows six common components of system architecture, from user interaction layers to data interfaces. The sections that follow discuss each of these components in greater depth.

System components

A system is comprised of various software and hardware components. Hardware encompasses tangible elements like servers, storage devices, and networking equipment. Software components include the application itself, libraries, databases, and the operating system upon which application code runs. Together, system components collaborate to execute tasks, manage resources, and provide interfaces for user interaction.

Data interfaces

Data interfaces define how data is stored, retrieved, and manipulated. This includes storage mechanisms (e.g., relational databases, NoSQL databases), access patterns (e.g., sequential access, random access), and strategies for optimizing data retrieval and management.

Communication protocols and interfaces

Components within a system rarely operate in isolation. Communication protocols and interfaces establish how they interact and exchange data. These protocols define the language and structure for data exchange, ensuring seamless communication across different components.

Third-party services and APIs

Modern systems often leverage external functionalities offered by third-party services. APIs (Application Programming Interfaces) act as intermediaries, enabling communication and data exchange between the system and these external services, expanding system capabilities without duplicating development efforts.

User interaction layers

User interaction layers define how users interact with the system. They encompass the user interface (UI)–the visual elements for user interaction–and the user experience (UX)–the overall system experience. These layers strive to create an intuitive and user-friendly environment for end users.

Security layers

Security layers implement measures like user authentication (verifying user identity), authorization (controlling access to resources), and data encryption (securing data during storage and transmission) to safeguard the system from unauthorized access, breaches, and other threats.

Six types of system architecture

System architecture styles dictate how multiple components within a system interact and communicate. Understanding these styles empowers developers and architects to select a strategy that aligns best with their project's needs and goals. In this section, we briefly examine some modern system architecture styles. For a more in-depth look into the advantages and considerations of each style, check out our free guide.

Monolithic architecture

In a monolithic architecture, the entire application is deployed either on a single server or across multiple servers with load balancers within a distributed system. In either case, the application functions as a single unit. This approach simplifies development, offers faster execution, and eases testing and deployment processes.

However, monolithic architectures also have limitations. For example, monolithic applications face scalability challenges, as it is difficult to scale only one part of the application in isolation. This often leads to inefficient use of resources and higher deployment costs. In addition, maintaining a large, monolithic codebase becomes cumbersome, and adopting new technologies can take time and effort. Finally, deploying changes in a monolithic architecture often requires maintenance or downtime, impacting user experience.

Diagram of a monolithic architecture. (adapted from Source)

Microservices architecture

Microservices architectures break systems down into independent, business-focused services. This structure boasts scalability, flexibility, and resilience. Teams can scale individual services to meet specific demands, and independent development and deployment cycles accelerate time-to-market. Microservices also isolate failures, preventing system-wide outages.

However, this approach introduces complexity in managing service discovery, communication, and data. Distributed system challenges like latency and data consistency require careful design and robust tooling to ensure smooth operation and reliable communication across services.

Diagram of a microservices architecture. (adapted from Source)

Event-driven architecture

Event-driven architectures decouple components through asynchronous event exchange. This promotes scalability, flexibility, and fault tolerance with isolation as services react to events independently.

However, this approach introduces complexity in managing event flows, eventual consistency, and message ordering. Event-driven systems may experience temporary inconsistencies until events propagate, and special mechanisms are needed to ensure messages are delivered in the proper sequence when message order is crucial. Debugging event-driven systems can also be challenging due to their reliance on asynchronous communication.

Despite these considerations, event-driven architectures offer significant advantages for building loosely coupled, scalable, and resilient systems.

Diagram of an event-driven architecture. (adapted from Source)

Serverless architecture

Serverless architectures empower developers to focus on code, not servers. They build functions triggered by events and deploy them on a cloud provider's platform. These platforms automatically scale and manage infrastructure, which offers significant advantages as applications grow. Serverless applications benefit from seamless scaling, pay-per-use cost efficiency, and faster deployment cycles.

However, serverless comes with several challenges, including:

• Vendor lock-in
• Potential cold start latency
• Limitations in execution environments
• Complexities in monitoring and debugging

Despite these considerations, serverless architectures offer an attractive development approach for building scalable and cost-effective applications.

Diagram of a serverless architecture. (adapted from Source)

Edge computing architecture

Edge computing pushes processing power to the network's edge, closer to devices and users. This minimizes latency, optimizes bandwidth usage, and improves application reliability. Data processing and storage occur locally, reducing reliance on centralized cloud servers.

However, managing this distributed infrastructure requires careful consideration of resource constraints, network connectivity, and security risks. Designing efficient applications and robust security measures are crucial for successful edge deployments.

Diagram of an edge-computing architecture. (adapted from Source)

Peer-to-peer architecture

Peer-to-peer architecture distributes control and resources across participating devices, eliminating central servers. This structure boasts scalability, resilience, and efficient resource utilization. By adding more nodes, the network dynamically scales to handle fluctuating workloads.

However, challenges arise in managing network overhead, data consistency, and security risks. Peer-to-peer networks require careful design to ensure optimal performance and reliable communication across a potentially large and dynamic network.

Diagram of peer-to-peer architecture. (adapted from Source)

Five essential system architecture best practices

The following sections present five system architecture best practices to help developers and architects design robust, scalable, and maintainable systems. These best practices encompass the technical considerations and the creation of clear and comprehensive documentation. Let's explore these best practices in more detail.

Embrace architecture as a shared responsibility

Traditional system architecture design practices often rely on designated architects shouldering the entire responsibility. However, an alternative approach involves engaging developers and business stakeholders from the early design stages. This approach offers two significant advantages.

• Increased collaboration - By involving more stakeholders in the design process, architecture becomes a collaborative effort. The architecture benefits from diverse perspectives, such as developers' practical experience and business representatives' strategic vision.
• Better knowledge sharing - Early developer involvement also fosters a deeper understanding of the system and leads to higher buy-in. This benefit is enhanced when documentation is stored in a central, easily accessible location. This centralized access to architectural artifacts ensures transparency and empowers all parties to contribute to the system's evolution.

In practice, earlier engagement from different stakeholders means actively seeking developer input during decision-making, integrating experienced developers into the design process, and ensuring all architectural documents are readily accessible to developers, architects, and business stakeholders. This fosters a collaborative environment where all parties work together to create a robust and well-understood system architecture.

Manage technical debt effectively

Software development accumulates debt–both architectural and technical. Technical debt reflects the gap between the source code's current state and best practices. Shortcuts, hacks, errors, and poor practices contribute to this debt, negatively impacting code quality, performance, reliability, security, and testability.

On the other hand, architectural debt is the divergence between an application's current state and its desired architecture. It stems from design choices, requirement shifts, external dependencies, or legacy systems. Architectural debt issues can hinder alignment with business goals, compliance, integration, and future-proofing.

Here are some practices that can help manage both kinds of debt:

Identifying system architecture tech debt

To uncover hidden system architecture costs:

• Visualize your system architecture in its entirety, including all components and interdependencies.
• Assess your architecture and code against desired outcomes, best practices, and stakeholder expectations.
• Leverage tools like architecture reviews, code reviews, metrics, benchmarks, and stakeholder feedback to pinpoint areas of concern.
• Document these debt items, their causes, and potential consequences for clear communication and prioritization.

Prioritizing system architecture tech debt

Not all debt is equally urgent. Prioritize architectural and technical debt based on their impact on development efforts and business goals. Utilize frameworks like cost-of-delay to sort debt into critical, high, medium, or low categories. Analyze each debt item's dependencies, tradeoffs, and potential opportunities to inform your plan.

Repaying system architecture tech debt

Develop a structured and iterative approach to address accumulated debt. This might involve refactoring, redesigning, rewriting, upgrading, or replacing components. Align these activities with project goals, scope, budget, and timeline. Open communication with stakeholders, team members, and users throughout the process is crucial.

Preventing system architecture tech debt

Adopt a proactive and disciplined approach to prevent future debt. Before implementing a new system or feature in code, make sure your team has conducted sufficient upfront system design to prevent the need for major architectural rework later. In addition, ensure there is an established process for collaborative and continuous system design reviews to proactively identify areas for improvement. Finally, maintain comprehensive and up-to-date documentation on system design to facilitate better knowledge sharing and empower all team members to contribute to the project.

Document system architecture

Documenting and communicating a system architecture can be challenging. System architecture documentation should explicitly capture architectural requirements, decisions, and tradeoffs, ensuring clear communication and informed decision-making throughout the project lifecycle. While traditional written documentation is vital in this process, it is equally important to visualize the system's core components using different types of diagrams. The table below describes three common types of architecture diagrams.

System architecture, sequence, and network diagrams are powerful tools that can significantly enhance documentation by providing visual representations of system behavior and a targeted focus on key system components. This balances technical detail and business-critical information to foster a shared understanding of the system for all stakeholders.

Example of a system architecture diagram.

Maintain separation of concerns

A fundamental principle for crafting robust and maintainable system architectures is the concept of separation of concerns. This principle advocates for decomposing the system into well-defined modules with clear boundaries. Each module encapsulates a specific functionality or responsibility, minimizing interdependence with other parts of the system. Here is how the separation of concerns benefits system architecture:

• Enhanced modularity - By separating concerns, each module acts as a self-contained unit with a clear interface. This modularity simplifies development, testing, and maintenance. Modifications within a module have minimal impact on other parts of the system, promoting isolation and reducing the risk of unintended consequences.
• Improved maintainability - Well-defined modules with limited dependencies are easier to understand, modify, and debug. Developers can focus on specific functionalities without getting entangled in complex interactions with other modules. This fosters a more maintainable system architecture that evolves efficiently over time.
• Promotes loose coupling - Modules interact through well-defined interfaces, minimizing direct dependencies on each other's internal implementation details. This loose coupling makes the system more adaptable and resilient to changes. Modifications within a module can be implemented without requiring changes throughout the entire system.
• Facilitates easier testing - By isolating functionalities, developers can focus on testing individual modules in a controlled environment, leading to more efficient and comprehensive testing strategies.

A classic example of separation of concerns is utilizing a microservices architecture. This architectural style decomposes the system into distinct services, each with a specific responsibility or business function.

Example of a microservices architecture (adapted from Source)

A microservices architecture is just one example of how the separation of concerns principle can be applied in system design. By following this principle throughout the system design process, developers can create more easily developed, tested, and maintained systems.

Leverage the right tools

Leveraging the right tools empowers architects to design performant, resilient, and scalable applications quickly without sacrificing quality. These tools automate tasks, reduce errors, and improve communication, leading to a more efficient design process. Key features to look for when picking system design tools include:

Architectural observability

Implementing architectural observability equips teams with deep insights into the system's internal behavior and eliminates confusion. This includes monitoring communication patterns to proactively identify and address potential issues. In addition, having a clear and dynamic view of the system's architecture fosters a shared understanding among developers, architects, and stakeholders.

Automatic drift detection

Any change–intentional or otherwise–can cause a system's architecture to deviate from its documented state. When using traditional, static documentation tools, these changes often go unnoticed or undocumented. However, automatic drift detection identifies these discrepancies promptly, allowing for swift corrective action before issues arise. It directly connects to the system infrastructure, actively listening to the components and dependencies and immediately notifying relevant team members of any changes or discrepancies.

Contextual views

Different stakeholders have varying levels of detail needs. Using customized contextual views, developers can deep-dive into technical intricacies, while architects can view the overall structure, and business leaders can gain a high-level understanding of the system's core components.

Version control for architecture diagrams

The ability to visualize system diffs and prototype new architectures with version control provides several benefits, including the following:

• Visual change tracking - Visual diffs within architecture diagrams highlight modifications to your system architecture, providing a clear understanding of how components have evolved. This empowers developers to manage system architecture changes without sifting through lines of code.
• Architecture branching - Create architecture branches to isolate changes and assess potential impact before merging them into the main system. This allows teams to experiment freely with new features or bug fixes.
• Impact assessment and review - Visualize how changes ripple through the system. Architecture version control allows you to predict how modifications in one area might affect other components, promoting informed decision-making during development.

Streamlined collaboration

Effective tools offer collaboration features like knowledge-sharing interfaces and content management systems, ensuring all stakeholders are on the same page.

Modern tools like Multiplayer empower system architects and development teams by providing all the key features mentioned above.

Conclusion

System architecture serves as the blueprint for any software system. By understanding the overall system architecture and system design best practices, developers and architects can make informed decisions that lead to robust, scalable, and maintainable systems.

Following established best practices–such as embracing a collaborative approach, managing architectural debt effectively, and leveraging the right tools–empowers teams to design, document, and evolve their systems efficiently. By prioritizing clear communication and a shared understanding among stakeholders, architects can ensure that the system architecture aligns with business goals and delivers long-term value.