Web application architecture is evolving rapidly, and in 2025, AI will play a more significant role than ever in shaping how we build, scale, and optimize web applications. AI is now deeply embedded into web apps via chatbots, personalization, code assistants, and analytics etc. AI-powered design tools help developers effortlessly create stunning interfaces, while intelligent chatbots and personalization engines enhance user engagement like never before.
Edge computing makes applications faster by processing AI tasks closer to users, and serverless computing streamlines development by eliminating infrastructure headaches. In-browser AI with lightweight models like Phi‑4‑mini in Edge browser and edge computing for low-latency inference are now viable.
Meanwhile, microservices and containerization make applications more modular, scalable, and resilient. But with all these advancements, best practices remain essential; scalability, security, automation, and cloud-native development are the pillars of modern web architecture. Whether designing a new app or upgrading an existing one, understanding these trends will help you stay ahead of the curve.
A web application architecture presents a layout with all the software components (databases, applications, and middleware) and how they interact. It defines how the data is delivered through communication protocols and ensures that the client-side and backend servers can understand. Moreover, it also ensures that valid data is present in all user requests. It creates and manages records while providing permission-based access and authentication.
Choosing the right design defines your company’s growth, reliability, interoperability, and future IT needs. As such, it is important to understand the components comprising the architecture of web apps.
You can also read this blog on Medium
AI is now deeply embedded in modern web applications, revolutionizing both front-end and back-end design. From AI-powered design assistants and intelligent chatbots to personalization engines, these technologies automate complex tasks and enhance user experiences.
Even the web browser is evolving into an intelligent client. For example, Microsoft Edge’s latest APIs let web apps run a built-in 3.8-billion-parameter AI model (Phi‑4‑mini) for on-device text generation and real-time assistance.
Combined with edge computing (processing AI tasks on geographically distributed servers or devices) for low-latency inference, this means web apps can deliver smarter, context-aware features instantly, without always relying on a central server.
What does this mean for web architecture? In 2025, traditional web application architecture must evolve to leverage AI. Developers are weaving AI capabilities into every layer of the stack – from the client-side (with on-device models and adaptive UIs) to the server-side (with AI agent orchestration, GenAI-powered services, and AI/ML data pipelines).
To stay competitive, organizations should realign their architectures to harness AI for scalability, personalization, and automation.
A traditional web application architecture diagram comprises three core components:
1) Web Browser: The browser, client-side, or front-end component is the key component that interacts with the user, receives the input, and manages the presentation logic while controlling user interactions with the application. User inputs are validated as well, if required.
2) Web Server: The web server, also known as the backend or server-side component, handles the business logic and processes the user requests by routing the requests to the right component and managing the entire application operations. It can run and oversee requests from a wide variety of clients.
3) Database Server: The database server provides the required data for the application. It handles data-related tasks. In a multi-tiered architecture, database servers can manage business logic with the help of stored procedures.
Three-tier architecture is a software model that separates an application into three logical layers: presentation, application, and data. Here, the application layer acts as an intermediary where intermediate servers receive client requests and process them by coordinating with subordinate servers applying the business logic. The intermediate application layer manages communication between the client and the database, enabling clients to access data from different DBMS solutions.
The 3-tier web application architecture diagram is more secure as the client does not directly access the data. This abstraction enables stronger security through API gateways, token-based authentication, and Zero Trust principles.
Deploying application servers on multiple machines provides higher scalability, better performance, and better reuse. You can scale it horizontally by scaling each item independently. You can abstract the core business from the database server to perform load balancing efficiently. Is easy and cost-effective.
Building a layered modern web application architecture diagram helps you identify each component’s role and easily change the corresponding layer without affecting the overall application. It enables you to write, debug, manage, and re-use code easily.
Here is an extra Web Application Architecture diagram of layers for you…
Have you started your application modernization strategy? Read the full blog to find out how.
The Application Layer is the core element of our business logic that orchestrates how user requests are processed, routed, and responded to. It includes web servers, application logic, APIs, AI inference layers, serverless runtimes and edge functions.
What is a web server? Simply put, a web server runs one or more websites or web apps. The web server is either a hardware or software system that uses HTTP/HTTPS, QUIC, WebSockets and other protocols to view user requests via a browser. It processes them by applying business logic and delivering the requested content to the end-user.
A Web Server can be a hardware device or a software program.
While a static web server delivers the content to the browser as it is, a dynamic web server updates data before delivering it.
In modern frameworks like Next.js, Astro, or Qwik, these capabilities are now native or available via a plugin.
The client-side component of a web application architecture diagram enables users to interact with the server and the backend service via a browser. The code resides in the browser, receives requests, and presents the user with the required information. This is where UI/UX design, dashboards, notifications, configurational settings, layout, and interactive elements come into the picture.
HTML or Hypertext Markup Language is a popular standard markup language that enables developers to structure web page contents using a series of page elements. Developed by Tim Berners-lee and released in 1993, HTML quickly evolved and became the standard markup language globally.
HTML5 supports multimedia, offline capabilities, and mobile responsiveness out of the box, making it suitable for today’s progressive web apps (PWAs).
CSS or Cascading Style Sheets is a popular style sheet language that lets developers separate website content and layout for sites developed using markup languages. Using CSS, Grid, Flexbox, and variables, you can define a style for elements and reuse them multiple times.
You can use a style for a single element, an entire webpage, or the entire website. Frameworks like Tailwind CSS and Sass further streamline styling workflows.Similarly, you can apply one style across multiple sites. It is simple and easy to learn. It is device-friendly, too.
Browser compatibility and security are two areas that raise concerns. Similarly, different versions of CSS also create confusion. Developers are advised to check the compatibility before making any changes to the design.
JavaScript or JS is the most popular client-side programming language that handles everything from DOM manipulation and animations to API integration. JS is also central to on-device AI inference using WebGPU or WebAssembly (Wasm) for real-time personalization and analytics on the client side.
JavaScript uses a simple, easy-to-learn syntax. The language is so popular that every browser uses a JS engine to run JavaScript code on devices. It is easy to insert JS code on any web page, making it highly interoperable. It allows you to create rich interfaces to deliver a better UI/UX experience. Being on the client side, JS reduces the server load as well.
However, developers should be careful about the security as the code is executed on the client side, which hackers can sometimes exploit.
Popular JavaScript Frameworks and Libraries
React, now maintained by Meta, is an open-source JavaScript that is popular for building front-end libraries. It offers a rich ecosystem that includes Next.js and React Router. React uses a virtual DOM for efficient rendering and promotes a component-based architecture that is ideal for building scalable and reusable interfaces.
React is an open-source JavaScript that has gained popularity in recent years.. React benefits enable developers.
ReactJS is easy to learn and use. There is extensive documentation and plenty of handy tools available for developers. The code is reusable. ReactJS uses a virtual DOM, it improves efficiency and optimizes memory usage.
On the downside, the ReactJS development environment is highly dynamic, so developers should proactively monitor the changes and quickly adapt new skills to leverage React. Moreover, React technologies are improving rapidly.
Vue.js is a lightweight, beginner-friendly JavaScript framework that works for both small apps and large-scale SPAs. It combines the best features of Angular and React while maintaining simplicity.Vue.js comes with handy tools that serve basic programming needs.
The tool is lightweight for downloads and installation. It is easy to learn and use. It uses a virtual DOM so that when a user interacts with an element, the browser does not have to render the entire page, only the element.
It easily integrates with existing apps. The documentation is concise and well-structured. Community support is good.
The toolkit is suitable for basic projects but offers limited support for large-scale projects. Its flexibility can pose quality issues on large projects as well. GitLab, Alibaba, and Adobe are popular companies that use Vue.js.
Angular (formerly Angular.js) is an open-source, TypeScript-based web app framework developed by Google that offers all functionalities for developing enterprise-level applications, such as components, modules, templates, directives, service and dependency injections, routing, etc. It helps developers quickly build prototypes. It uses plain HTML templates. It also includes robust tools for testing, performance profiling, and code scaffolding through the Angular CLI.
Angular uses two-way data binding, which makes DOM manipulations easy and quick. The CPU-performance enhancing features make it a good choice for large-scale apps. It comes with various plugin tools out of the box.
However, the hierarchical structure can sometimes make debugging a challenge. Concepts such as Inversion Of Control, Dependency Lookup, and Dependency Injection require a steep learning curve. It requires Node.js and Angular CLI for local development and build automation.
The server-side component is the key component of the web application architecture diagram that receives user requests, performs business logic, and delivers the required data to the front-end systems. It contains servers, databases, web services, APIs, and AI-driven processing layers. Modern server-side components are increasingly built using microservices, serverless functions, and containerized deployments, with strong support for AI APIs, edge computing, and asynchronous messaging queues.
Among the server-side development tools, Node.js and Python are highly recommended. Node.js is an easy-to-learn, lightweight, developer-friendly, highly scalable, and extensible cross-platform solution. Python uses simple syntax, focuses on natural language, and makes it easy to write and execute code faster. The community is also very supportive.
Node.js is an open-source, cross-platform runtime environment that is built on Chrome’s V8 engine. Developers use JavaScript to build Node.js applications and run them on Node.js runtime using Windows, macOS, and Linux platforms.
Node.js enables developers to build quality applications quickly. Node.js doesn’t buffer data and executes code super fast. It is event-driven, asynchronous, and highly scalable on a single thread. Node.js best suits apps that are data streaming, data-intensive, I/O bound, JSON-API based and microservices-based systems. Paypal, Uber, eBay, and Netflix are some popular applications that Node.js powers. It doesn’t suit apps that are CPU-intensive due to its single-threaded execution. However, it can be scaled using clustering or load balancing.
Java is an object-oriented and class-based programming language that enables developers to write code and run it on any platform using a Java virtual machine (JVM) environment.
Being platform-agnostic, Java programs are cost-effective to build and run. Leveraging OOPS concepts, you can reuse objects in other programs. It supports multi-threading, portability, automatic garbage collection, distributed networking, etc. With its mature ecosystem and features like multithreading, distributed computing, strong tooling, Java best suits large scale enterprise apps. Java is used by companies like LinkedIn, Spotify, and Amazon.
On the downside, Java requires significant memory space owing to the JVM abstraction
Python is a strong alternative to Java for building web applications owing to its clean syntax, developer-friendly design, and rapid development capabilities. It allows you to do more with less code, so you can quickly build and test prototypes that increase productivity.
This dynamically typed language is highly flexible and suitable for small and large web application projects and various segments such as video games, AI programming, automation, and API services etc. It is strong in AI/ML integrations.
Python’s vast standard library and rich ecosystem of frameworks like Django, Flask, and FastAPI cover almost every programming need. With its vibrant community, support is always available. Instagram, Spotify, and Dropbox are a few popular users of Python.
Read our blog about Node.js vs Python and learn which one is better.
Laravel is a popular, open-source PHP framework that helps developers easily build custom web apps. It uses aMVC (Model, View, and Controller)-based framework..
With extensive built-in functions such as routing, middleware, authentication, authorization, Blade templating, and Eloquent ORM—Laravel’s elegant object-relational mapping system, developers can quickly write code, test and deploy apps faster. PHP Laravel offers cross-site request forgery tokens that provide security. It is scalable and cost-effective. Laravel is widely used for eCommerce sites, content platforms, SaaS products, and API backends.
Who knows how to implement PHP frameworks better than an experienced engineer? Read our guide on how to hire a PHP developer.
Go is a statically typed, compiled programming language designed for simplicity, speed, and concurrency. It is similar to the C language and is easy to learn and build, especially for developers coming from C or Python backgrounds.
With no virtual runtimes, Go code compiles faster and produces smaller binary, making it ideal for cloud-native development, microservices, and CLI tools. The standard library offers a range of built-in functions along with testing support. Garbage collection is available. Concurrent programming powered by lightweight goroutines and channels is a standout feature of Go that simplifies writing scalable, parallel systems.
Go has strong ecosystem support with growing third-party libraries and frameworks like Gin, Echo, and Buffalo. It supports generics, improving code reuse significantly. Implicit interfaces can be challenging to manage. Organizations like Google, Uber, Cloudflare, and Docker use Go in production for performance-critical applications.
.NET is a software development framework developed by Microsoft for building desktop, web, mobile, cloud, and applications. Released in 2001, .NET was initially Windows-centric but now runs on macOS, Linux, Android, and iOS, with frameworks like ASP.NET Core and .NET MAUI
The .NET ecosystem, powered by .NET 9, is a unified, open-source, cross-platform framework for building modern, scalable applications.
.NET uses a modular structure that enables developers to break down code into smaller pieces and seamlessly build and manage software products using CI/CD pipelines via GitHub Actions, Azure DevOps, and Visual Studio. It offers features like dependency injection, async programming, built-in security, and automatic monitoring that help in quickly building enterprise-grade applications.
ASP.NET Core provides robust caching (in-memory, distributed with Redis) that enhances performance while the integration with tools like Application Insights offers real-time monitoring.
.NET is free and open-source and best suits enterprise applications, where performance, interoperability, and cloud integration are essential. Companies like Stack Overflow, Accenture, and Dell rely on .NET for building mission-critical software systems.
Ruby
Ruby is a dynamic, object-oriented programming language known for its simplicity, productivity, and elegant syntax. It gained widespread popularity with the Ruby on Rails server-side framework that enables rapid development of web applications. . Ruby on Rails comes with built-in security to mitigate risks related to SQL injections, cross-site scripting software (XSS), and cross-site request forged (CSRF). Ruby has a mature library ecosystem powered by RubyGems, excellent documentation, and strong community support.
While developers can quickly build applications, the speed of the applications is a concern. That said, this problem mainly affects large-scale apps. Improvements in Ruby 3.x, JRuby, and advanced caching techniques have mitigated many of those issues. For small and medium-sized organizations, Ruby remains a productive and reliable choice.
Companies like Shopify, GitHub, and Basecamp use Ruby and Rails in production at scale.
Read our blog about the best programming languages.
Application Programming Interface (API) is not a technology- it’s a conceptual interface that enables communication between different software systems. Simply put, it is a mediator that allows apps to request and exchange data or functionality without knowing the internal implementation details.. It comprises protocols, tools, and subroutine definitions required to build apps.
For instance, when you sign in to an application, the app calls the API to retrieve your account details and credentials. The application will contact the corresponding servers to receive this information and return this data to the user app. Web APIs are typically exposed over HTTP/HTTPS, and built using frameworks like .NET, Node.js, Java, Python Flask/FastAPI, or Go.
With APIs, developers don’t have to create everything from scratch but use existing functions exposed as an API to increase productivity and gain faster time to market. By reducing development efforts, APIs significantly reduce development costs. As components are decoupled, we can scale each one independently. It also improves collaboration and connectivity across the ecosystem while enhancing customer experience.
Cloud instances are important to a modern web application architecture diagram for hosting and running applications at scale. A cloud instance is a virtual server instance built, delivered, and hosted using a public or a private cloud and is accessible over the Internet. It works as a physical server that seamlessly moves across multiple devices or deploys numerous instances on a single server
Unlike fixed on-premise servers, cloud instances can be spun up or terminated dynamically based on demand. They support horizontal and vertical scaling with minimal configuration, accessible globally, and can be replicated across regions for better performance and cost effectiveness. Cloud instances leverage containerization, serverless computing, and edge infrastructure to deliver low-latency, high-availability applications globally.
Read our blog on How to Build an App Like Instagram.
A database is a key component of a web application that stores and manages information for a web app. Using a function, you can search, filter, and sort information based on user request and present the required info to the end user. They allow role-based access to maintain data integrity.
When choosing a database for your web app architecture, the size, speed, scalability, and structure are the four aspects that require your consideration. For structured data, SQL-based databases are a good choice. It suits financial apps wherein data integrity is a key requirement.
NoSQL is a good option for handling unstructured data. It suits apps wherein the nature of incoming data is not predictable. Key Value databases associate each value with a key and suit databases that store user profiles, reviews, blog comments, etc. For analytics, Wide Column databases are a good choice.
Read our blog on the best programming languages to develop your application.
| Database Type | Use Cases | Examples | Description |
| Relational (SQL) | Structured data, transactional systems | PostgreSQL, MySQL, SQL Server | Follows ACID principles, ideal for apps needing data integrity like finance, healthcare. |
| NoSQL (Document) | Flexible schema, content-heavy apps | MongoDB, Couchbase | Handles unstructured/semi-structured data; great for content management, real-time analytics. |
| Key-Value Stores | High-speed lookups, session data | Redis, DynamoDB | Simple but fast, Best for user profiles, preferences, shopping carts. |
| Wide-Column Stores | Analytical workloads | Apache Cassandra, Google Bigtable | Optimized for write-heavy, large-scale apps (IoT, logs) |
| Graph Databases | Relationship mapping | Neo4j, Amazon Neptune | Ideal for recommendation engines, fraud detection, and social networks. |
| Time-Series Databases | Chronological data | InfluxDB, TimescaleDB | Ideal for IoT, sensor data, financial markets, and log monitoring. |
The web app architecture is evolving. As such, organizations should proactively monitor these changes and realign the architecture accordingly. Here are a few trends to check out:
Artificial Intelligence (AI) and machine learning (ML) are deeply integrated into web app development, enabling smarter, adaptive systems.
Caching system is a local data store that facilitates quick access to data for an application server instead of contacting the database every time. In a traditional setup, data is stored in a database. When a user makes a request, the app server requests that data from the database and presents it to the user. When the same data is requested again, the server should repeat the same process, which is repetitive and time-consuming. By storing this information in a temporary cache memory, apps can quickly present data to users.
The caching system can be designed in 4 models:
In a web application architecture, cloud storage is an obvious requirement. Cloud storage is about storing the data in the cloud and accessing it over the Internet. A cloud service provider provides the storage infrastructure on a pay-per-use subscription model.
AWS is the most popular cloud service provider, Amazon S3 is the most popular cloud storage solution in web application architecture and environments across the globe. Amazon Simple Storage Service (S3) is a flexible, cost-effective, durable, secure cloud storage service that offers high availability and scalability.
In AWS, a cloud storage unit is called a “bucket” in which objects are stored. When a bucket is created, it is deployed in the region specified by the user. Once the deployment is done and objects are added to the bucket, the user can choose the storage class type along with features such as versioning control, lifecycle policies, bucket policy, etc. AWS manages the lifecycle management for objects, including IAM policy and data protection.
A Content Delivery Network (CDN) is a globally distributed network of edge servers that cache and deliver content faster and better to users based on their geographic location. Instead of contacting the central server, the users’ request is routed to a CDN server that stores a cached version of the content. As such, site speed and performance increases while packet loss decreases.
The original server load is reduced. It also enables the segmentation of the audience and provides advanced web security.
The server load is reduced. It also enables the segmentation of the audience and advanced web security.
As the name says, the load balancer is a service that balances traffic loads by distributing them across different servers based on the availability of predefined policies. When a user request is received in the load balancer, it retrieves the server’s health regarding availability and scalability and routes the request to the best server. A load balancer can be a hardware component or a software program.
Load balancing can be done in two ways
1) TCP/UDP level Layer 4 Load Balancing: It routes traffic based on IP address and port without inspecting the content. It’s fast and lightweight.
2) App-level Layer 7 Load Balancing: Load balancing based on application load
Popular load balancer tools:
In a traditional web architecture, you’ll see a web server and a database. The web server listens to client requests and contacts the database to provide the required information or process the business logic. When concurrent users increase, the web server will run out of resources. Even though upgrading the server configuration helps for a while, it provides limited capabilities and causes a single point of failure. Deploying multiple servers is a good choice to create a highly scalable web architecture.
While designing the multi-server architecture, organizations can connect multiple OS deployment servers to a single database or multiple databases. However, it is important to keep them replicated with appropriate content. Replication can be scheduled at specified times.
A message queue is a buffer that stores messages asynchronously and facilitates communication between different services in a web application. In today’s microservices environment, software is developed in smaller, modular, and independent building blocks. While RESTful APIs are commonly used for synchronous communication, message queues support asynchronous communication between these services.. Message queues provide granular scalability, simplify decoupling processes, and increase reliability and performance.
Amazon Simple Queue Service (SQS) is a fully managed publish/subscribe (pub/sub) messaging queue service offered by Amazon. Users can access the messages via any programming language using the web services API provided by AWS SQS. Messaging is processed asynchronously, meaning messages wait in a queue, and apps can access them later. It seamlessly integrates with other AWS services.
Amazon SQS uses two types of Queues:
Standard Queues: The message string remains the same, but the order might change. It is helpful for tasks wherein messages are distributed to various nodes.
Apache Kafka: is a distributed event streaming platform that is popular for high-throughput, real-time data pipelines and analytics. It handles massive volumes of events with low latency and high durability. Kafka best suits scenarios requiring reliable event logging, stream processing, and scalable pub/sub messaging across microservices or big data environments.
RabbitMQ: is a robust, open-source message broker that supports multiple messaging protocols like AMQP. The tool is flexible and easy to integrate with existing systems. It efficiently handles tasks like complex routing, message queuing, and workload distribution in microservices. RabbitMQ is ideal for reliable, decoupled communication between distributed application components with built-in delivery guarantees.
Over here, you can analyze the process from start to end with the help of a Web Application Architecture Diagram. It is essential to consider the elements and resources that would take action on the flow, such as the API, cloud storage, technologies, and databases.
A monolithic architecture is a traditional software development model —also known as web development architecture— wherein the entire software is developed as a single piece of code going through the traditional waterfall model. This means that all the components are interdependent and interconnected; every component is required to run the application. To change or update a specific feature, you need to change the entire code to be rewritten and compiled.
As monolithic architecture treats the entire code as a single program, building a new project, applying frameworks, scripts, and templates, and testing it becomes simple and easy.
However, as the code grows, it becomes difficult to manage or make updates; for even a small change, you must go through the entire process of your web development architecture. As each element is interdependent, scaling the application is complex. Moreover, it is unreliable, as a single point of failure can bring down the application.
The monolithic architecture will serve the purpose when you want to build a lightweight application and are on a tight budget.
Microservices architecture solves several challenges that are encountered in a monolithic environment. In a microservice architecture, the code is developed as loosely coupled, independent services that communicate via RESTful APIs. Each microservice contains its database and operates a specific business logic, so you can easily develop and deploy independent services.
Since it’s loosely coupled, microservice architecture provides the flexibility to update/modify and scale independent services. Development becomes easy and efficient, and continuous delivery is enabled. Developers can quickly adapt to innovation. For highly scalable and complex applications, microservices is a good choice.
However, deploying multiple services with runtime instances is a challenge. When the number of services grows, the complexity of managing them grows, too. Moreover, microservices apps share partition databases. It means you should ensure consistency across multiple databases affected by the transaction.
Learn more about microservices vs monolith on our blog.
Container technology is the best option when it comes to deploying microservices. A container encapsulates a lightweight runtime environment for an application that can run on a physical or a virtual machine. As such, applications run consistently from the developer’s device to the production environment. By abstracting execution at the OS level, containerization allows you to run multiple containers inside a single OS instance. While it reduces overhead and processing power, it also increases efficiency.
Containerization enables developers to add multiple app components in a single VM environment instead of segregating code into different VMs, thereby gaining more application processing power. With its lightweight nature, containers run quickly. They are flexible, reliable, and best suited to policy-based microservices environments.
Docker is the most popular containerization technology that offers a comprehensive ecosystem for containerization technologies. It offers greater performance, easy-to-use technology and large community support.
Serverless architecture is a model for developing software applications. In this structure, an infrastructure service provider manages the underlying infrastructure’s provisioning. It means you only pay for the infrastructure when it’s in use.
Serverless computing lowers costs as resources are only used when the application is in execution. The cloud provider handles the scaling tasks. Moreover, the backend code gets simplified. It reduces development efforts and costs and brings faster time to market.
Multimedia processing, live streaming, chatbots, CI Pipelines, IoT sensor messages, etc. are some of the use cases for serverless computing.
In a microservices architecture, you can perform serverless computing using AWS Lambda, API Gateway, and API Step Functions.
AWS Lambda is a serverless computing service offered by Amazon. Launched in 2014, Lambda offers an execution environment for functions written in languages such as Python, C#, Java, Node.js, etc. It automatically provisions and removes servers as per the traffic requirements. You don’t have to upload the entire app, only the required functions, then trigger it to run the service. Lambda offers ease of execution, improved app resilience, and a cost-effective solution. On the downside, there is no control over the environment.
An API Gateway is an API management tool that enables you to create, publish, secure, and manage HTTP, WebSocket, and REST APIs. Acting as a reverse proxy, an API Gateway receives various API calls, performs service aggregation to fulfill those calls, and delivers the result. API Gateways help you protect your APIs, run analytics tools on APIs, connect a billing service, manage older and deleted APIs, etc. In a serverless environment, resources are provisioned based on the API calls. API Gateway helps you to deploy and manage serverless functions.
Azure and Google offer similar services for serverless computing:
AWS Step Functions is an AWS visual workflow tool that enables developers to break a process into several steps. Automation of IT processes, building distributed apps, and machine learning pipelines becomes easy with this low-code service. You can quickly build and deploy reliable and highly scalable apps and manage stateful and fault-tolerant workflows with less integration code.
Read our slideshow for an overview of the types of architecture.
Here are some best practices for designing a grand web application architecture diagram.
A scalable web server is critical to delivering consistent app performance regardless of the number of concurrent users, location, and time. There are three types of scaling options: horizontal, vertical, and diagonal. While vertical scaling is about upgrading/downgrading the device configuration, horizontal scaling is about increasing/decreasing the number of devices. Diagonal scaling is about combining both models.
Choosing a horizontal scaling model is recommended as you will not be limited by configuration or number of servers. Moreover, you can mix vertical scaling where applicable.
With hybrid and multi-cloud environments increasingly becoming popular, adapting to the cloud and proactively provisioning resources is key to delivering high-performing web apps. Elastic infrastructure comes with preconfigured network systems, VM servers, storage, and compute resources, allowing the environment to be easily managed with self-service portals.
It gives the flexibility to quickly adapt to changing market needs and customer expectations.
It enables administrators to provision resources using code automatically. When servers are to be updated or modified, they are automatically replaced by newer ones.
Configurational drift is a big challenge in mutable infrastructure. Scaling and debugging issues while replicating the production environment adds to this challenge. Immutable infrastructure uses a validated and version-controlled image to provision new servers for every deployment. So, the previous state of the server is not a concern. You can test servers before deploying them.
It eliminates configurational drifts and allows horizontal scaling while offering simple rollback and recovery with consistent staging environments.
Microservice and serverless computing are both critical to web application development. However, the difference is that microservice architecture offers a long-term solution with high scalability, while serverless computing offers code efficiency. Serverless functions run only when they are triggered.
By combining both models, you can gain the best of both worlds. You can use AWS Step Functions to assign triggers to combine several functions into a service and assign triggers to them. With event-triggered microservices, you can build a combined system to gain code efficiency, long-term stability, cost-effectiveness, and scalability.
Web applications are now being delivered as SaaS applications. There are two models to deploy SaaS apps: single tenant vs multi tenant architecture.
For web apps, using a multi-tenant architecture offers multiple benefits. Organizations can manage a single-user code base, reducing overhead and code conflict issues. It also reduces server infrastructure costs through economies of scale. Along with reduced development efforts, it also brings faster time to market.
Python/Node.js + React + AWS is the new trend in building SaaS web apps.
Visit our CEO’s LinkedIn for more insights about Development, AI, ML, DevOps, and more!
Building a secure architecture is a minimal requirement for any organization. Applying security protocols and policies not only secures your data and environment but it also helps you easily manage audit tasks and comply with government regulations.
Deployment automation is about easily automating the process of code movement between testing and production environments. It enables developers to quickly and frequently deploy code to production without human intervention. AWS offers a fully managed deployment service in the form of AWS CodeDeploy. It enables you to deploy code automatically to various environments such as AWS Lambda, AWS Fargate, Amazon EC2, or on-premise.
Deployment Automation is a part of the DevOps Continuous Integration / Continuous Deployment pipeline. It consists of three important phases: build, test, and deploy. When the code is written, it is automatically tested and added to the central repository. These changes are validated and added to the application. Automating testing runs various tests at different levels to ensure the code is error-free. Then, the code is automatically deployed to production.
Infrastructure as Code (IaC) is a method of automatically provisioning the infrastructure using code. It helps you treat servers, networks, databases, and other IT resources as software and manage them using config files.
As such, you can spin up resources instantly on-demand, manage configuration consistency, and eliminate configuration drifts while increasing software development efficiency. It reduces software development costs as well. Terraform and AWS CloudFormation are two most popular IaC tools.
This blog is available on our DZone profile
In today’s highly competitive software world, creating quality products and services is not enough to gain customers’ trust.
How you deliver the products and services to your customers matters the most. Web applications help you to do so. As such, organizations must create and deploy highly optimized web apps that cost-effectively deliver speed, performance, and superior customer UI/UX experience. Designing the right web app architecture is crucial here.
Contact ClickIT for web development services.
It would help if you chose the model of web applications based on the number of databases and servers used in the application. There are three popular models:
One database and one web server ( Simple architecture for small apps)
One Database and multiple web servers (Scales traffic while centralizing data)
Multiple databases and multiple web servers (Best for high-availability and distributed apps)
The web application architecture diagram talks about the high-level components of the application and how they interact with each other, while web application design talks about the code level design and how each service or function interacts with other components of the application.
MVC stands for Model-View-Controller. The MVC architecture splits the app logic into three components based on the functionality.
Model: Manages application data, logic, and business rules
View: Components that the user can view
Controller: Intermediate component between the model and view components
Caching system is a local data store that facilitates quick access to data for an application server instead of contacting the database every time. By storing this information in a temporary cache memory, apps can quickly present data to users.
Some of the best tools for managing web application architecture are:
Cloud Platforms: AWS, Azure, GCP
Infrastructure as Code: Terraform, AWS CloudFormation
Frontend Frameworks: React, Angular, Vue.js
Backend Frameworks: Node.js, Python (Django, Flask), .NET
DevOps: Docker, Kubernetes, GitHub Actions, Jenkins
Snowflake or Databricks, which one should you choose for your big data and AI projects?…
MCP architecture addresses one of the biggest limitations of generative AI. While generative AI excels…
I have been recruiting for tech for a while now, and to hire AI developers,…