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Have you ever wondered how large applications like Facebook or Uber are built?
Behind the slick interfaces and seamless user experiences lies intricate application architecture.
For the uninitiated, application architecture refers to the overall structure of an app — how different software components interact to enable various features.
Whether you're building a simple web app or a complex enterprise system, the architectural approach you choose to go with profoundly impacts the development process.
In this post, we'll explore the key concepts around application architecture in simple terms.
Specifically, we'll look at common architectural patterns like monolithic, microservices, event-driven, and more.
5 Main Types of Application Architectures
When building an application, developers have to make key architectural decisions upfront.
Let's look at some of the popular architectural patterns used today:
1- Monolithic Architecture
A monolithic architecture is when an application is built as one large, self-contained unit. All the code for the UI, business logic, and data access is part of a single executable program.
Some key characteristics of monolithic apps are:
- Unified codebase - The entire app lives in one code repository as a standalone program. All changes and updates impact the monolith as a whole.
- Tightly coupled - Components within the monolith cannot be separated. The web UI layer, for example, calls business logic code directly.
- Shared database - Components access the same centralized database instance. There is no separation of data storage.
Monoliths are simple to develop as new features can be added to the core codebase. Testing is also straightforward since all code and components are accessible in one place. What’s more is that monolithics are easy to deploy too — you just need to bundle the executable and dependencies into a package.
However, as the monolith grows, there is a lack of flexibility. In other words, scaling will require replicating the entire app stack rather than just a portion.
That means even minor bug fixes and changes will impact the whole monolith. These dependencies between components will often lead to fragility.
In a nutshell, monolithic apps are harder to understand, navigate, and scale as new features are added to the project.
2- Microservices Architecture
Microservices break down an app into a set of smaller, decoupled services. Each service has a focused capability and can function independently from others.
Some key characteristics of microservices-based apps are:
- Modular services — Services are built and updated independently, while changes are localized.
- Loosely coupled — Services interact via well-defined APIs rather than direct calls. Adding or modifying services has a lower impact.
- Independently deployable — Each service can be deployed, upgraded, and scaled without affecting others.
- Owned by small teams — Services are maintained by dedicated teams, enabling productivity.
Simply put, microservices are flexible since services can be developed with different tech stacks. They are also easier to scale by deploying instances of a service across servers. Since services are isolated, failures are also isolated.
However, microservices trade simplicity for complexity. Distributed systems involve inter-service coordination, networking, and security hurdles. There is also duplication of effort across different teams.
3- Service-Oriented Architecture (SOA)
SOA aims to build reusable services that can integrate together to enable complex workflows and data flows. The key emphasis is on interoperability between services.
Some key characteristics of SOA-based apps are:
- Services expose APIs — In other words, other components can access service functionality via well-defined interfaces.
- Protocol-agnostic — Services can integrate regardless of implementation language or platform.
- Loose coupling — SOA-based apps have minimal dependencies between services. This allows services to evolve independently.
- Composability — Services in SOA-based apps can be orchestrated together to enable complex business processes.
Benefits of SOA include flexibility in assembling solutions, reusability of services, and interoperability between heterogeneous environments.
However, SOA can introduce complexity in managing distributed services. There is also runtime performance overhead of API calls vs direct function execution.
4 - Serverless Architecture
Serverless architecture relies completely on cloud services and abstracts away servers. That means, developers need to just deploy app code, while cloud providers manage server resources automatically.
Some key characteristics of serverless apps are:
- No server management — Developers are abstracted away from all infrastructure decisions. Cloud providers automatically handle resource allocation and scaling based on workload.
- Event-driven execution — Code is organized into small functions that run in response to triggers like HTTP requests, database events, etc.
- Usage-based pricing — Organizations pay only for the compute resources consumed per function execution, rather than having to maintain provisioned servers.
- Rapid development — Serverless removes ops complexity like config management, scaling, deployments, etc. This enables faster iterations.
- High scalability — Serverless apps can handle sudden spikes in traffic since compute expands and contracts instantly based on load.
Thanks to these characteristics, the serverless architecture allows you to build highly scalable applications with low overhead.
However, serverless architecture also comes with some challenges. The lack of control over the underlying infrastructure can make debugging and monitoring more difficult.
Overall, it is certainly a promising and innovative approach to building cloud-native applications. The auto-scaling, pay-per-use model, and abstraction of server infrastructure provide undeniable benefits.
5- Event-Driven Architecture
Event-driven architecture (EDA) is a software architecture pattern that promotes the production, detection, and consumption of events between software components.
In an EDA, components communicate by generating and listening for events, instead of directly calling each other.
Some key characteristics of event-driven architecture include:
- Loose coupling — The event producers and consumers are loosely coupled and typically do not know about each other.
- Asynchronous — Events are delivered asynchronously without blocking the event producers. This allows for highly scalable and performant architectures.
- Reactive — Consumers react to events and take action as needed. The consumers are notified rather than having to poll for changes.
- Distributed — Event producers and consumers can be distributed across servers, networks, or even organizations.
Overall, event-driven architecture facilitates the development of systems that are highly scalable, resilient, and flexible. It is well-suited for modern applications that require real-time data processing and reactive workflows.
However, it does introduce complexity around asynchronous flows and can be challenging to debug and test.
Uses of Application Architecture in Software Systems
Different application architecture patterns enable the building of different types of software systems.
Let's look at some common use cases:
Web Applications
Web applications like social networks, e-commerce sites, and webmail services need to support massive user bases and huge data volumes. Their architecture focuses on scalability, reliability, and performance.
To scale out web apps, monolithic architectures are generally avoided. Instead, microservices and service-oriented approaches are preferred. This allows independent scaling of resource-intensive functions like recommendation engines, search, image processing, etc.
Serverless architectures are also well-suited for web apps because of dynamic scaling. It lets you instantly add extra computing resources to handle sudden spikes in traffic. After the surge, you can choose to automatically deactivate the extra resources to optimize costs.
Mobile Applications
Mobile applications have unique architectural constraints compared to the web. Mobile apps need to deliver robust performance despite flakiness in wireless connectivity. They also deal with limited local resources on devices.
Accordingly, mobile app architectures optimize for factors like low latency UI experiences, seamless offline usage, background processing, syncing data with servers, etc.
For example, mobile backends are often designed as lightweight API servers. They return JSON data rather than server-rendered HTML pages. This reduces bandwidth usage and speeds up response times.
Client-side processing and caching also improve performance compared to server-side rendering. Features like offline caches and background sync keep apps functional without continuous connectivity.
Desktop Applications
Desktop applications like office suites, media editors, and CAD software need to offer rich responsive experiences. Users expect seamless interactions and quick feedback. Accordingly, desktop app architectures often lean towards monolithic designs.
Desktop apps also leverage access to local devices like GPU, large memory, multiple cores, etc. This enables high-performance rendering and computations.
So in summary, desktop app architectures focus on delivering seamless UX and harnessing local machine resources. But unlike web and mobile apps, the network distribution in desktop applications is comparatively limited.
IoT (Internet of Things) Systems
The Internet of Things (IoT) connects physical devices and objects to the Internet to collect and exchange data. IoT systems comprise of sensors, connectivity modules, data storage, analytics, and visualization.
Application architecture is key to handling the scale and diversity of IoT ecosystems. It enables:
- Seamless integration of numerous devices, networks, and interfaces
- Efficient data aggregation from distributed nodes
- Real-time analytics and insights generation on streaming data
- Rapid application development and minimal downtime
With a sound application architecture, IoT systems can scale on demand and provide actionable insights from sensor data.
Big Data Systems
Big data systems process high volumes of structured and unstructured data from multiple sources. Application architecture enables:
- Ingestion of heterogeneous data from various sources
- Efficient data storage in databases like Hadoop
- Complex analytical modeling and statistical analysis
- Intuitive visualization of insights using BI tools
The modular structure of application architecture supports the rapid development of big data pipelines. It also allows scaling individual components like data warehouses as data volume increases.
That means by taking a thoughtful application architecture approach, enterprises can build flexible and high-performing big data systems.
Conclusion
Application architecture is a foundational part of software development.
The structural patterns you choose profoundly impact how well your applications scale, perform and evolve over time.
In this post, we looked at common architectural styles like monolithic, microservices, service-oriented, serverless, and event-driven. Each approach carries unique tradeoffs between simplicity, flexibility, and complexity.
Hopefully, this beginner-friendly overview gave you a better grasp of core application architecture concepts.
