You’ve started a web app business. You have the idea, but the architecture is crucial.
This post explains web architecture, its concepts, and how to choose the proper architecture and technologies for your project. By the end of this post, you won’t be in the dark while designing a bare-bones app.
Web Application and Software Architecture 101 is a thorough course on the subject. This course is good for improving software architecture expertise.
Software architecture explains a system’s components, linkages, and interactions.
It’s a guide. It provides an abstraction for managing system complexity and coordinating components.
Architecture defines a solution to meet all technological and operational criteria, optimizing for performance and security.
Architecture design requires balancing the organization’s and development team’s needs. Every decision affects quality, maintainability, performance, etc. Ralph Johnson’s definition of software architecture is one of my favorites.
Creating a solid foundation is crucial. Whether building or baking pizza. If the base is wrong, we must start anew.
Web app development is similar. The architecture must be well-planned to avoid large design and coding modifications later. Many engineers advise against re-designing. It’s time-consuming. It could delay your shipment by months or longer. This wastes engineering and financial resources.
It depends on when we hit an impasse due to hasty design decisions. Before touching the code, we must fix the architecture.
Software development is iterative and evolving, so we don’t always get it right the first time. Still, we can’t avoid our assignments.
Software design vs. architecture
We’ll differentiate between software design and architecture.
Software architecture defines a system’s skeleton and high-level components and how they function together. Do you need serverless architecture that splits an app into BaaS and FaaS? Or do you need a microservice design with discrete modules/codebases for features/tasks?
Performance, fault tolerance, scalability, and dependability are affected by architecture.
Software design is responsible for code-level design, such as module functions, class scope, and function purposes. When utilized strategically, they allow programmers to avoid recreating the wheel by employing approaches refined by others. They give a common language to discuss and manage code in larger teams. This course will help you use software design patterns in your code.
Here’s a good article about software design and developer patterns: Software design patterns.
Request-response architecture. The client requests information from the server, which answers.
Every website you visit, from WordPress blogs to Facebook and banking apps, uses client-server architecture.
P2P networks allow nodes to connect without a central server. A central server eliminates single points of failure. The network’s computers are equal. A node can both seed and leech. Even if certain computers/nodes fail, the network and communication remain up.
Blockchain is P2P.
MVC architecture divides application logic into three functional components. These are: Models represent database data storage. Views are user-facing components like an output or GUI. Controllers interface models and views.
MVC is used for mobile, web, and desktop apps.
Microservice architecture splits features/tasks into discrete modules/codebases that work together to produce a huge service.
This architecture makes app maintenance, feature development, testing, and deployment easier than monolithic.
Reactive or Event-driven architectures are non-blocking. Modern web development favors event-driven systems.
They can handle many concurrent connections with few resources. Scalable modern apps must be asynchronous. Modern web frameworks offer more stable distributed behavior.
This pattern can be used to structure programs with decomposable subtasks. Each layer serves the next.
- Logic business
- Data layer
It has three parts:
Domain This architecture makes application components independent, loosely linked, and testable.
The architectural pattern’s heart is business logic. Ports & Adapters are on the outside. Ports are interfaces, like APIs. The app’s interface receives all input.
- No latency
- Quickly accessible data
- No network data transfer ensures data safety.
- Little control over the program; hard to add features or update code after it ships.
- Thorough testing with few errors is required.
- Single-tier apps can be changed or reverse-engineered.
- Code and UI on the same computer means fewer network calls.
- Physically close database and business logic boosts performance.
- Since the client contains most of the application functionality, controlling and redistributing software versions is difficult.
- Its restricted user base limits its scalability. Multiple client requests impede application performance because clients need separate connections and CPU memory.
- Since application logic is tied to the client, reusing logic is challenging.
- The data passed in the intermediate layer for database updates prevents data corruption from client apps.
- Business logic on a centralized server secures data.
- Due to the dispersed deployment of application servers, the system’s scalability is improved because a separate connection from each client is no longer needed.
Creating 3-tier applications requires more effort since communication points are added (client to middle tier to server, instead of client to server) and tools like Visual Basic, PowerBuilder, and Delphi diminish performance.
- Three-tier architecture’s advantages
- Off-loading the database and client tiers increases performance, making it suitable for medium to high-volume industries.
Complex structure is hard to develop and maintain due to tier componentization.
If you require no network latency, adopt a single-tier architecture. Two-tier applications lessen network latency and provide you more data control. When you need control over your application’s code/business logic and data, adopt a three-tier architecture. N-tier design is best for scalable, large-data applications.
Scaling… My app needs which?
Your app may not be mission-critical if it receives limited continuous traffic. For example, a company’s internal tool. Why disseminate it? When you know the traffic load won’t increase considerably, vertical scaling is sufficient.
If your app is a social network, fitness app, or anything similar, traffic will rise soon. You need high availability and horizontal scalability. Always build for cloud deployment and horizontal scalability. This webpage explains scalability.
Microservice or monolith?
Let’s compare the two.
Monolithic apps are suitable for simple use cases with little traffic. An internal tax app or equivalent public tool is an example. These are use cases where the firm knows user base and traffic won’t grow exponentially.
Dev teams sometimes start with a monolithic architecture and then switch to microservices. This helps them handle the application’s complexity step-by-step. LinkedIn did this.
Microservice architecture when
Microservice design is suitable for complicated use cases and apps with exponential traffic growth, like a social network.
Typical social networking apps include messaging, real-time chat, LIVE video streaming, image uploads, Like, Share, etc. In this circumstance, I’d propose building each component individually using Single Responsibility and Separation of Concerns.
Every feature in one codebase would be a mess. We’ve tried three techniques to monolithic and microservices:
Starting with a monolithic architecture, scale to microservices.
Use case determines whether we choose monolithic or microservice architecture. Keep things simple and know the rules. Learn the landscape, build just when needed, and evolve code iteratively. This is correct.
NoSQL or SQL?
Why use SQL?
If you’re creating a stock trading, banking, or finance software or a social networking program like Facebook that has to store many relationships, choose a relational database. Why?
If your software involves money or numbers, transactions, ACID, and data consistency are crucial. Relational databases excel at transactions and data consistency. They’re ACID-compliant, battle-tested, and old.
Which of your pals live in a certain city? Which friend has already eaten at today’s restaurant? etc. Relational databases are best for storing this data.
Relational databases store connections. Facebook uses them as its user-facing database, so they’re tried and true.
- MS SQL
- NoSQL database selection
- Why choose a NoSQL database?
- Read/write operations
NoSQL databases scale quickly. NoSQL databases are suitable for websites with many read-write operations and massive amounts of data. They can manage more concurrent traffic and big volumes of data with low delay since they can add nodes on the fly.
- NoSQL databases are suitable for data analytics use cases with huge data influxes.
If you’re interested in NoSQL databases like MongoDB, I recommend Nikola Zivkovic’s course.
Choosing appropriate technologies
Interactive real-time data
If you need:
Real-time backend server interaction, such as a messaging app or audio-video streaming service like Spotify, Netflix, etc. Persistent client-server connection and nonblocking back-end technology.
NodeJS and Tornado are popular technologies for writing apps. Spring Reactor, Play, and Akka.io are Java ecosystem options.
Spring MVC, Python Django, Ruby on Rails, PHP Laravel, and ASP.NET MVC can be used for simple CRUD-based apps.
If you’re writing a simple program like a blog, online form, or social media app that runs in an IFrame, choose PHP. Free PHP tutorial.
You can also use web frameworks like Spring boot, Ruby on Rails to reduce verbosity, configuration, and development time. PHP hosting is cheaper than other types. Simple use cases are best.
CPU- and memory-intensive programs
Do you need to conduct CPU- and memory-intensive backend operations like Big Data Processing, Parallel Processing, and Monitoring & Analytics on a significant volume of data?
Web frameworks and programming languages aren’t designed for math. C++ is used to develop scalable, performant distributed systems. It helps developers write distributed systems by facilitating low-level memory manipulation. This language is used for most cryptocurrencies. Free C++ training.
Rust is C++-like. It’s designed for speed and safety. Developers are embracing it. Java, Scala, and Erlang also work. Java is used for most enterprise-level systems.
Go is a Google programming language for multi-core devices and huge data. How to begin Go programming.
Julia is a dynamic programming language for high-performance computations and analytics.