Introduction

Every time you open a website, scroll through a social media feed, or purchase a product online, a complex system is working behind the scenes to handle your requests efficiently. Web applications have become an integral part of our daily lives, powering platforms like e-commerce sites, social networks, and online banking systems. But have you ever wondered how these applications manage to serve millions of users simultaneously, ensuring smooth interactions and quick responses?

At the heart of every web application lies an architecture designed to process user requests, interact with databases, and deliver responses efficiently. This process involves multiple components, including web servers, backend applications, databases, and network infrastructure. A simple request—like loading a webpage—triggers a series of operations, from routing traffic through a web server to executing database queries and rendering content in the browser.

In this article, we will explore the fundamental building blocks of web applications. We’ll begin by understanding how web servers handle requests and distribute them efficiently. Then, we’ll dive into the role of reverse proxies, which act as intermediaries to enhance security and performance. We’ll also compare multiprocessing and multithreading, two essential techniques for handling concurrent requests, and discuss scaling strategies that ensure applications remain fast and reliable under high traffic. Finally, we’ll introduce Content Delivery Networks (CDNs) and explain how they optimize performance by serving static content from geographically distributed locations.

By the end of this article, you will have a clear understanding of what happens behind the scenes when you interact with a web application, equipping you with the foundational knowledge needed to build and optimize scalable systems.

1. How Web Applications Work Behind the Scenes

Whenever you visit a website, a complex process unfolds behind the scenes to ensure that you receive the requested content efficiently. Whether you are browsing social media, reading an article, or making an online purchase, every interaction with a web application follows a structured request-response cycle. Understanding this cycle is essential for designing scalable and high-performance applications.

When a user enters a URL into their browser, the browser sends a request to the server hosting the web application. This request first reaches a web server, such as Nginx or Apache, which is responsible for processing and routing incoming traffic. If the requested resource is a static file—such as an HTML page, CSS stylesheet, JavaScript file, or image—the web server retrieves it and sends it directly to the browser.

However, if the request requires dynamic content—such as fetching user-specific data, executing database queries, or performing business logic—the web server forwards it to the backend application. The backend, typically built using frameworks like Django (Python) or Node.js (JavaScript), processes the request, interacts with the database, and generates a response. Instead of sending this response directly to the user, the backend returns it to the web server (e.g., Nginx), which then delivers the final content to the user’s browser.

This structured flow ensures that web applications remain scalable, secure, and efficient. Web servers act as a buffer between clients and backend services, improving performance, enabling load balancing, and securing backend systems from direct exposure to the internet. This functionality is known as acting as a reverse proxy, where the web server forwards requests to the backend and then returns the responses to the client.

Analogy: Sending an Image to a Friend

One day, Sarah asked her friend David to send her a picture. David quickly searched through his computer’s folders, found the image, and sent it to her immediately. Since Sarah only needed the file as it was, David didn’t have to modify or process anything.

A few days later, Sarah had a different request. This time, she said, Can you remove the background from this image and then send it to me? Unlike the first request, David couldn’t handle this himself. Instead of editing the image manually, he uploaded it to an AI-powered tool that specialized in background removal. The AI tool processed the image, removed the background, and returned the final result. Once the tool completed the task, David downloaded the modified image and sent it to Sarah.

In this scenario, David played the role of a web server (like Nginx or Apache):

✅ When Sarah needed a simple file, David retrieved it and sent it directly, just like a web server serving static content without backend processing.

✅ When Sarah’s request required additional processing, David did not modify the file himself. Instead, he forwarded the request to a specialized AI tool (acting as the backend), waited for the response, and then delivered the processed image. This is exactly how a web server, when acting as a reverse proxy, forwards dynamic requests to a backend application (like Django or Node.js) and waits for a response before returning it to the client.

✅ David was not involved in processing the image—only in forwarding the request and delivering the response. Similarly, a reverse proxy like Nginx does not execute business logic—it simply routes requests and responses between the client and backend.

Step-by-Step Request Flow

A user opens a browser and enters a URL (e.g., www.example.com).
The browser sends an HTTP request to the web server (e.g., Nginx, Apache).
The web server processes the request:
✅ If it is a static file (e.g., HTML, CSS, images), the web server delivers it directly.
✅ If it is a dynamic request, the web server forwards it to the backend application (e.g., Django, Node.js).
The backend processes the request, interacts with the database, and generates a response.
The backend sends the response back to the web server (e.g., Nginx).
The web server forwards the response to the browser.
The browser renders the content and displays it to the user.

Figure 1. represents how a web application processes a request and delivers a response:

Flowchart of a web application’s request-response cycle
Fig 1.: Representation of a web application’s request-response cycle, showing how a web server (acting as a reverse proxy) processes requests before forwarding them to the backend.

To enhance understanding, Figure 2. represents the same request-response process using icons to visualize key components:

Figure 2.: A request-response cycle represented using icons, illustrating the interactions between the browser, web server, backend, and database.

Key Takeaway

A web server (reverse proxy) behaves just like David in this analogy:

🔹 It serves static content directly when no processing is needed.
🔹 It forwards complex requests to a backend application and waits for the response before delivering it.
🔹 It does not process or modify the request itself—it simply relays information between the client and backend.

1.2 Role of Web Servers & Reverse Proxies

A web server is responsible for efficiently handling user requests and serving web content. When a user accesses a web application, their request is first processed by a web server such as Nginx or Apache, which then determines how to handle it.

Functions of a Web Server:

Handling HTTP requests from clients (browsers, mobile apps, or API clients).
Serving static content directly (e.g., HTML, CSS, JavaScript, images).
Forwarding dynamic requests (e.g., database queries, API calls) to backend services.

What is a Reverse Proxy?

A reverse proxy is an intermediary server that sits between clients and backend servers, enhancing performance, security, and load distribution. Instead of allowing users to communicate directly with backend services, requests first pass through a reverse proxy (like Nginx) before being routed to the appropriate service.

Key Benefits of a Reverse Proxy:

Distributes incoming traffic across multiple backend servers, preventing overload on a single system.
Caches responses to reduce latency and improve load times.
Enhances security by hiding backend services from direct exposure.
Acts as an internal load balancer, ensuring smooth traffic distribution among backend services.

Comparison: Nginx vs. Apache

Both Nginx and Apache are popular web servers, but they differ in their architecture and efficiency.

Feature	Nginx (Multiprocessing) 🚀	Apache (Multithreading) 🔄
Performance	Faster (event-driven, handles many connections efficiently)	Slower (thread-based, may struggle with high concurrency)
Scalability	Excellent for handling large traffic loads	Moderate scalability, better for dynamic applications
Static Content	High-speed delivery with caching	Good, but slower than Nginx for static files
Reverse Proxy	✅ Fully supported	✅ Fully supported
Best Use Case	High-traffic sites, API gateways, load balancing	Dynamic applications requiring `.htaccess` flexibility

How Data Flows Through a Web Server

Figure 3. shows the flow of data transfer over the web, where the computer on the right side represents the client’s computer and the left side illustrates the server hosting the web application, including all necessary files, folders, and backend services. The diagram visualizes how, when a user opens a browser and sends a request, the request flows through the web server, gets processed inside the backend, and the response is sent back to the client.

Once the web server receives the request, it determines whether the request is for static content (e.g., HTML, CSS, images) or dynamic content (requiring backend processing). For static content, the web server searches through pre-existing folders and delivers the appropriate file directly to the client. If the request requires dynamic processing, the web server communicates with the appropriate backend services, such as a database or an API, to generate the required response.

To ensure efficient data transfer, Nginx uses data streaming, where it reads content in chunks and progressively sends it to the client instead of waiting for the entire file to load. This enables faster delivery and improved performance. Additionally, for further optimization, Nginx can compress data before sending it—similar to how a file is compressed on a computer to be copied faster. This reduces bandwidth usage and speeds up data transmission, ensuring a smoother user experience. This compression and chunked delivery process is known as data streaming.

Figure 3.: The flow of data transfer over the web, illustrating how requests move from the client to the web server, then to backend services, and back to the client.

Key Takeaway

A web server (reverse proxy) behaves like a gateway between users and backend applications:

🔹 It serves static content directly when no processing is needed.
🔹 It forwards dynamic requests to backend applications for further processing.
🔹 It improves security, performance, and scalability by acting as a reverse proxy.

Understanding how web servers and reverse proxies function helps in designing scalable, high-performance web applications that efficiently handle user requests.

3. Understanding Multiprocessing vs. Multithreading

When multiple users access an application simultaneously, the server must efficiently handle many requests at once. To achieve this, two primary techniques are used: multiprocessing and multithreading. Both approaches enable parallel execution of tasks, but they differ in how they utilize system resources and manage concurrent operations.

Analogy: David Handling Multiple Requests

Initially, Sarah was the only one asking David to send her images from his computer. Since it was a single request at a time, he could manage it effortlessly. However, over time, as more people started asking David for images, the number of requests became overwhelming. He could no longer handle all the requests alone.

To deal with this, David had two options:

Hiring multiple employees and providing each with their own computer : In this approach, David shares his files with each employee, and they all work independently on separate systems. Since each employee has their own computer, they can process requests simultaneously without interfering with each other.
Hiring multiple employees but having them work on David’s computer: Instead of buying separate computers, David allows all employees to work on the same machine. However, instead of taking turns, each employee is given their own keyboard, mouse, and monitor, while they all share the same CPU, memory, and storage. This setup allows employees to work simultaneously, but since they all depend on the same processing unit, the system can slow down as more requests are made. If the number of requests becomes too high, the system may crash due to excessive resource consumption.

Comparison of the Two Approaches

Each approach comes with its own advantages and disadvantages:

Option 1: Hiring multiple employees with their own computers; similar to multiprocessing

✅ More efficient – Each employee works independently, leading to true parallel execution.
✅ More stable – If one employee (process) fails, it does not impact the others.
✅ Better performance for heavy tasks – Since each employee has their own machine, they are not limited by shared resources.
❌ Expensive – Requires purchasing multiple computers, leading to higher costs in hardware and energy.
❌ More resource-intensive – Running multiple computers simultaneously consumes more power and memory.

Option 2: Hiring multiple employees sharing one computer; similar to multithreading

✅ Less resource-intensive – All employees work on the same system, reducing the need for extra machines.
✅ More cost-effective – No need to buy additional hardware, leading to lower infrastructure costs.
✅ Good for handling many small tasks – Employees can work on different tasks without needing extra machines.
❌ Performance limitations – Since all employees share the same computer, they may experience slowdowns when handling multiple tasks simultaneously.
❌ More prone to crashes – If too many employees (threads) are working at the same time, the system can overload and fail.

Multiprocessing: Handling Tasks in Parallel

Multiprocessing involves running multiple processes simultaneously, each on a separate CPU core. This technique allows an application to execute multiple tasks in parallel, improving performance for CPU-intensive operations such as data processing, scientific computations, or video rendering. Since each process runs independently, they do not share memory space, making them isolated and less prone to crashes affecting other processes.

This is similar to the first scenario in the analogy, where David hired multiple employees and provided each with their own computer. In multiprocessing, each process runs in isolation, just as each employee had their own system to work on without interfering with others.

Multithreading: Efficiently Managing Waiting Tasks

Multithreading, on the other hand, allows multiple threads to run within a single process, sharing the same memory space. This technique is particularly useful for I/O-bound tasks, such as fetching data from a database, making API calls, or reading files from disk. Unlike multiprocessing, where each process requires a dedicated CPU core, multithreading enables multiple tasks to be handled concurrently without creating separate processes, reducing memory overhead.

This is similar to the second scenario in the analogy, where David hired multiple employees but had them work on the same machine. In multithreading, multiple threads share system resources, allowing tasks to run concurrently but relying on the same CPU, which can cause slowdowns when handling a high volume of intensive operations.

Comparison: Multiprocessing vs. Multithreading

Feature	Multiprocessing	Multithreading
CPU Utilization	High (uses multiple CPU cores)	Low (shares a single process)
Best for	CPU-bound tasks (e.g., data processing, computations)	I/O-bound tasks (e.g., database queries, API calls)
Scalability	High (parallel execution on multiple cores)	Moderate (efficient resource management within a single process)

Expanding the Request-Response Cycle in Web Applications

In web applications, multiprocessing and multithreading are crucial for handling multiple user requests efficiently.

Nginx is an event-driven, multiprocessing web server, meaning it creates multiple worker processes to handle requests in parallel. Each worker is independent and capable of handling multiple connections.
Apache, on the other hand, uses multithreading by default, where multiple threads share the same process, making it well-suited for handling many small, lightweight requests.

How Requests Flow Through Multiprocessing and Multithreading in Web Servers

A user sends a request, which first reaches the web server (Nginx or Apache).
If Nginx is used, it selects an available worker process (multiprocessing) to handle the request. If Apache is used, it selects an available thread (multithreading).
The selected worker or thread forwards the request to the backend application.
The backend’s internal load balancer assigns the request to an appropriate backend worker (e.g., a Django Gunicorn worker).
The backend worker processes the request, interacts with databases if needed, and generates a response.
The backend worker sends the response back to the backend load balancer.
The backend load balancer forwards the response back to the web server’s worker (Nginx) or thread (Apache).
The web server’s internal load balancer ensures the response is correctly handled.
Finally, the web server sends the response to the browser, and the user sees the requested content.

Figure 4. is an illustration of this process:

Expanded Request-Response Cycle
Figure 4.: A detailed representation of the request-response cycle, incorporating how Nginx (multiprocessing) handle requests and distribute them efficiently.

Key Takeaway

For CPU-intensive applications that require heavy computation, multiprocessing is the best choice since it can leverage multiple CPU cores to run processes in parallel. However, for applications that need to handle multiple users efficiently and manage I/O-bound tasks, multithreading is preferred, as it allows multiple threads to run within a single process while conserving system resources.

Nginx uses multiprocessing and acts as an event-driven, internal load balancer to distribute requests among workers efficiently.
Apache primarily uses multithreading, making it effective for handling high volumes of concurrent, lightweight tasks.
Backend services can combine both approaches, using multiprocessing for handling multiple requests and multithreading within each worker for efficient task execution.

By understanding how web servers and backend systems leverage multiprocessing and multithreading, developers can optimize application performance, scalability, and efficiency based on the nature of their workloads.

4. Load Balancing: Scaling Web Applications

As an application grows, a single server may struggle to handle all requests. Just like in any business, when demand increases, effective distribution of workload becomes necessary to maintain efficiency and prevent bottlenecks.

Analogy: Expanding David’s Business

At first, David ran a small office where he and a few employees managed all incoming requests. However, as more and more people started relying on his services, the workload became overwhelming. David had two possible solutions to handle the increasing demand:

Expanding the same office: David could enlarge his office space and add more desks and rooms to accommodate new employees. By increasing the physical capacity, he could hire more people and improve productivity. However, this approach had limitations—there was only so much space available, and if anything happened to this office (e.g., a power outage or an unexpected issue), the entire operation would be halted.
Opening multiple branches: Instead of overloading a single office, David decided to open new branches in different locations. This way, incoming customers could visit the nearest branch, reducing congestion in a single place. If one office became unavailable, the other branches could still continue working. However, managing multiple branches required an additional main office that would monitor all branches and ensure that workload distribution was balanced. This main office decided which branch should handle which task based on their availability and workload.

Scaling Web Applications

Similar to David’s business, web applications also face the challenge of handling increasing traffic. To ensure efficient request management, applications can scale using two primary methods:

1. Vertical Scaling (Scaling Up)

Vertical scaling means upgrading the existing server by increasing its CPU power, RAM, and storage capacity. This allows a single machine to handle more requests and perform better under heavy loads.

🚀 Advantages: Simple to implement, no need to distribute tasks across multiple servers.
⚠️ Disadvantages: Expensive, limited by hardware constraints, and introduces a single point of failure—if the server crashes, the entire system goes down.

Related to the analogy: This is like David expanding his current office, adding more desks and hiring more employees within the same space. However, if something happens to this office, all operations stop.

2. Horizontal Scaling (Scaling Out)

Horizontal scaling involves adding more servers to share the load. Instead of relying on a single machine, multiple servers work together to handle incoming requests, distributing the workload efficiently.

🚀 Advantages: Highly scalable, better fault tolerance (if one server fails, others continue working).
⚠️ Disadvantages: More complex setup, requires a system to manage how requests are distributed.

Related to the analogy: This is like David opening multiple branches instead of overloading a single location. If one branch has too much work, another can take over. Even if one branch shuts down, others remain functional.

Role of Load Balancer (Main Office Management)

When multiple branches (or servers) exist, there needs to be a system that determines how to distribute requests efficiently. This is where a load balancer comes into play.

Just like David’s main office monitors all branches and directs customers based on availability, a load balancer in web applications distributes requests across multiple servers. It ensures that no single server is overloaded while others remain underutilized, improving efficiency and response time.

By horizontal scaling, instead of sending a request directly to a server, the request is first sent to an external load balancer, just like how David’s main office decides which branch should handle a customer request. The load balancer evaluates which server is available and best suited to process the request, then forwards it to the appropriate server.

Once the request reaches the selected server, the web server (such as Nginx) takes over—this is similar to the manager of a branch handling the incoming request. The web server then decides:

If the request is for static content (such as an image or a basic HTML page), it is served immediately to the client, just like a manager handing a customer a ready-made product.
If the request is for dynamic content (such as fetching data from a database or processing an AI request), the web server forwards it to an available backend worker (similar to assigning a specialized employee in the branch to handle a request).

Thus, the web server plays the role of an internal load balancer, ensuring that within a given branch (server), tasks are efficiently assigned to the right backend services.

Request-Response Cycle in a Scaled System

The entire process follows these steps:

The client sends a request, which first reaches the external load balancer.
The external load balancer selects an appropriate server based on availability and workload.
The web server (like Nginx) inside the chosen server receives the request and determines the type of content requested.
If the request is static, the web server delivers it directly to the client.
If the request is dynamic, the web server forwards it to a backend worker.
The backend worker processes the request, interacts with the database if needed, and generates a response.
The response is sent back to the web server (internal load balancer).
The web server forwards the response to the external load balancer.
The external load balancer delivers the final response to the client.

Figure 5. is an illustration of this process:

Load Balancing Request-Response Cycle

Figure 5.: Representation of the request-response cycle in a horizontally scaled system, where multiple external load balancers distribute requests across multiple servers, and the web server (acting as an internal load balancer) manages tasks within the selected server.

Key Takeaway

Vertical Scaling (Scaling Up): Increases CPU, RAM, and storage on a single server, similar to expanding an office.
Horizontal Scaling (Scaling Out): Adds multiple servers to distribute the workload, similar to opening multiple branches.
Load Balancer: Ensures that requests are distributed efficiently across multiple servers, just like a main office managing workload distribution among branches.
Multiple Load Balancers: Prevent a single point of failure, similar to having multiple main offices managing different branches.

For handling large-scale applications, horizontal scaling with multiple load balancers is generally preferred, as it provides better fault tolerance, scalability, and flexibility compared to vertical scaling.

5. Content Delivery Networks (CDNs)

As web applications grow in popularity, users from different parts of the world may access them, leading to increased latency due to the geographical distance between users and the server hosting the application. A Content Delivery Network (CDN) helps solve this issue by caching static content across multiple geographically distributed nodes, ensuring that users receive data from the closest possible location rather than the original server.

Analogy: David Expanding with Global Partnerships

David, who originally started serving requests from his own office, now faces an increasing demand for his files. While his offices across North America efficiently serve users from nearby locations, requests from faraway places like Japan create a challenge. Since users in Japan cannot travel to North America just to receive a file quickly, David partners with a large global corporation that has offices worldwide. He shares his most frequently requested files with them, ensuring that users in different countries can access his content from the nearest office of that global company instead of reaching David’s original office in North America.

This global company functions just like a CDN, storing copies of static content closer to the users to improve response times. Moreover, CDNs have an optimized routing system, ensuring that if a file is not found in a nearby CDN location, the request is efficiently directed to the original source through the fastest, most secure path.

How CDNs Work

When a user requests content from a website using a CDN:

The request first goes to a CDN server closest to the user’s location.
If the CDN has a cached copy of the content, it serves the response immediately, reducing latency.
If the requested content is not available in the CDN cache, the request is forwarded to the external load balancer of the main infrastructure.
The external load balancer sends the request through the normal request-response cycle (as previously explained).
The response is first sent back to the CDN, where it gets stored (cached) for future requests.
Finally, the CDN delivers the response to the user, ensuring faster delivery the next time a similar request is made.

CDNs not only cache content but also optimize and secure traffic. They act as tunnelers, choosing the best possible routing path when forwarding requests to the main infrastructure. This reduces congestion, enhances security, and ensures data reaches its destination efficiently.

Request-Response Cycle with CDNs

The inclusion of a CDN in the request flow slightly modifies the request-response cycle:

A user sends a request to access a webpage.
The request is first sent to the nearest CDN node.
If the CDN has the requested content, it immediately responds to the user.
If the CDN does not have the requested content, it forwards the request to the external load balancer.
The external load balancer distributes the request to the appropriate web server (Nginx or Apache).
The web server processes the request and, if needed, forwards it to the backend application.
The backend retrieves necessary data, processes the request, and generates a response.
The response is sent back to the external load balancer.
Instead of going directly to the user, the response is first sent to the CDN, where it is cached for future requests.
Finally, the CDN delivers the response to the user, ensuring optimized performance.

Figure 6.: The request-response cycle with CDN integration, demonstrating how requests first go to a nearby CDN, and only if necessary, are forwarded to the main infrastructure. This figure represents the finalized request-response cycle for highly scalable web applications.

Key Takeaway

A Content Delivery Network (CDN) significantly improves web performance:

🔹 Caches content closer to users, reducing latency and improving load times.
🔹 Optimizes traffic routing, ensuring efficient communication between the client and the server.
🔹 Enhances security, acting as a protective layer that shields backend infrastructure.
🔹 Reduces server load, as many requests are handled at the CDN level instead of the original web server.

By leveraging CDNs, web applications can handle large-scale global traffic more efficiently, securely, and at lower latency.

The Science Behind Web Applications: Understanding Architecture and Performance