Angular Interview Preparation Guide for Experienced Developers

Angular has evolved into one of the most powerful front-end frameworks for building modern, scalable, and enterprise-level applications. For developers of experienced, interviews not only test your **theoretical knowledge** but also your **hands-on expertise** in building, deploying, and maintaining real-world Angular applications.

In this article, we’ll walk through the **key areas in Angular** you should master — starting from fundamentals to advanced production-ready concepts.

## 1. Angular Lifecycle Hooks

Lifecycle hooks are crucial for managing component creation, rendering, and destruction. Be prepared to explain **when and why** to use them.

* **ngOnInit**: Initialize component data.

* **ngOnChanges**: Detect changes in input-bound properties.

* **ngDoCheck**: Custom change detection.

* **ngAfterViewInit & ngAfterContentInit**: DOM and content initialization.

* **ngOnDestroy**: Cleanup, unsubscribe from Observables, release resources.

👉 **Interview Tip**: Be ready with real-time scenarios like unsubscribing in `ngOnDestroy` to prevent memory leaks.

## 2. Routing & Navigation

Routing is the backbone of any Angular application. Understand:

* **RouterModule** setup with `forRoot()` and `forChild()`.

* **Lazy Loading** modules for performance optimization.

* **Child Routes & Wildcards** (`**` for 404 pages).

* **Route Guards** (AuthGuard, CanActivate, CanDeactivate, Resolve).

* **Preloading strategies** for balancing lazy loading with speed.

👉 Example: Use `AuthGuard` with JWT tokens to restrict access to secure routes.

## 3. Forms in Angular

Forms are everywhere in enterprise apps. You must be comfortable with both approaches:

* **Template-driven forms** (simple, quick setup, two-way binding).

* **Reactive forms** (more control, validation, and scalability).

Key concepts:

* FormControl, FormGroup, FormBuilder.

* Built-in and custom validators.

* Async validators (e.g., checking if a username already exists).

* Dynamic form generation.

## 4. Angular Material & UI Components

Angular Material provides ready-to-use UI components. Focus on:

* Data tables with sorting, pagination, filtering.

* Dialogs, snackbars, and modals.

* Responsive layouts using Flex Layout/Grid.

* Theming and customization.

👉 **Interview Tip**: Be able to explain how Angular Material improves productivity and consistency.

## 5. Dependency Injection (DI)

Angular’s DI system is core to writing maintainable code. Know:

* Provider scopes: root, feature module, component.

* Hierarchical injectors.

* `@Injectable({ providedIn: 'root' })` usage.

* Tree-shakable providers.

* Use cases of `InjectionToken`.

## 6. HTTP Interceptors & API Handling

Interceptors allow you to **modify requests/responses globally**. Key scenarios:

* Attaching **JWT tokens** to headers.

* Global error handling (e.g., redirect to login on `401 Unauthorized`).

* Request/response logging.

* Caching responses for performance.

## 7. Authentication & Authorization (JWT Implementation)

Almost every production app requires authentication. Learn how to:

* Store and manage JWT tokens securely (localStorage vs cookies).

* Refresh tokens.

* Use interceptors to attach tokens.

* Protect routes with AuthGuards.

* Role-based access control.

👉 **Hands-on Task**: Implement login/logout with JWT, refresh tokens, and secure route navigation.

## 8. Caching & Performance Optimization

Production-grade apps demand speed. Interviewers expect knowledge of:

* Browser caching strategies (LocalStorage, IndexedDB).

* API response caching via interceptors.

* `OnPush` change detection strategy.

* Lazy loading and preloading strategies.

* TrackBy with `*ngFor` to prevent re-rendering.

## 9. Server-Side Rendering (SSR) with Angular Universal

For SEO and performance, Angular Universal is important. Be ready to answer:

* How SSR improves **SEO** for Angular apps.

* Setting up Angular Universal.

* Handling API calls on the server vs client.

* Differences between CSR (Client-Side Rendering) and SSR.

## 10. Error Handling & Logging

Enterprise apps need solid error handling. Know how to:

* Use **ErrorHandler** class for global error handling.

* Implement custom error services.

* Log errors to monitoring tools (e.g., Sentry, Azure App Insights).

* Show user-friendly error messages.

## 11. State Management (NgRx / Services)

Large apps often use state management. You should:

* Understand RxJS and Observables deeply.

* Be able to explain state management with Services and BehaviorSubject.

* Know NgRx basics: Actions, Reducers, Effects, Store.

* When to choose NgRx vs simple service-based state management.

## 12. Production-Level Deployment

Finally, demonstrate deployment expertise:

* `ng build --prod` optimizations (AOT compilation, minification, tree-shaking).

* Hosting on **Azure, AWS, Firebase, or Nginx**.

* Environment configuration (`environment.ts`).

* CI/CD pipeline setup for Angular apps.

* Handling SSL, security headers, and API proxy configuration.

## Conclusion

For a experienced Angular developer, interviews focus less on syntax and more on **architecture, scalability, performance, and deployment**.

If you cover these areas thoroughly — from lifecycle hooks, routing, forms, interceptors, JWT, Angular Universal, to production deployment — you’ll not only crack interviews but also be confident in building enterprise-grade Angular applications.

✅ **Pro Tip**: Build a small end-to-end Angular project that includes authentication, lazy loading, caching, Angular Material UI, and SSR. This will help you confidently explain your real-world experience.

Task vs Thread in C#: What’s the Difference?

When we start working with **multithreading and asynchronous programming in C#**, one of the most common confusions is between **Task** and **Thread**. Both let you execute code concurrently, but they are not the same thing. In this article, let’s break down the differences in a clear and practical way.

## What is a Thread?

A **Thread** is the smallest unit of execution managed by the operating system. When you create a thread, the system allocates resources for it, and you control its lifecycle manually.

### Key points about Threads:

* Created explicitly using `new Thread()`.

* Heavyweight – consumes more system resources.

* Full control over start, sleep, abort, and join operations.

* Suitable for long-running or dedicated background operations.

**Example:**

```csharp

using System;

using System.Threading;

class Program

{

    static void Main()

    {

        Thread thread = new Thread(() =>

        {

            Console.WriteLine("Running inside a thread.");

        });

        thread.Start();

    }

}

## What is a Task?

A **Task** is a higher-level abstraction introduced with the **Task Parallel Library (TPL)**. Instead of manually managing threads, a task represents a unit of work that runs on a thread (usually from the .NET Thread Pool).

### Key points about Tasks:

* Created using `Task.Run()` or `Task.Factory.StartNew()`.

* Lightweight – reuses thread pool threads.

* Handles return values and exceptions more easily.

* Integrates seamlessly with **async/await**.

* Best for short-lived, parallel, or asynchronous operations.

**Example:**

```csharp

using System;

using System.Threading.Tasks;

class Program

{

    static async Task Main()

    {

        await Task.Run(() =>

        {

            Console.WriteLine("Running inside a task.");

        });

    }

}

## Task vs Thread: A Comparison

| Feature             | **Thread**                           | **Task**                                  |

| ------------------- | ------------------------------------ | ----------------------------------------- |

| Abstraction Level   | Low-level (OS concept)               | High-level (TPL abstraction)              |

| Creation            | `new Thread()`                       | `Task.Run()` or `Task.Factory.StartNew()` |

| Cost                | Expensive (dedicated OS thread)      | Cheaper (uses thread pool)                |

| Return Values       | Complex (callbacks/delegates needed) | Easy (`Task<T>` returns a value)          |

| Exception Handling  | Manual try/catch                     | Built-in aggregation (`Task.Exception`)   |

| Async/Await Support | ❌ Not supported                      | ✅ Supported                               |

| Best For            | Long-running, dedicated operations   | Short-lived, async or parallel tasks      |

## When Should You Use What?

* ✅ Use **Thread** when you need **fine-grained control** over execution (e.g., setting priority, long-running background workers).

* ✅ Use **Task** when you want **concurrent or asynchronous operations** with less boilerplate code.

In modern .NET development, **Task is recommended in most cases** because it’s easier to work with, more efficient, and integrates directly with `async/await`.

## Final Thoughts

Both **Thread** and **Task** allow you to run code concurrently, but they operate at different abstraction levels. Think of **Thread** as the “engine” and **Task** as the “driver” that tells the engine what to do.

If you’re building modern applications in .NET, start with **Tasks** — and only fall back to **Threads** when you really need low-level control.

👉 This explanation should help you decide which to use next time you want to run code in parallel or asynchronously in C#.

Message Brokers Explained: The Backbone of Modern Applications

 In today’s world of **microservices, cloud computing, and distributed applications**, seamless communication between services is more important than ever. This is where **Message Brokers** come into play. They act as middlemen, ensuring that messages flow smoothly between producers (senders) and consumers (receivers).

## 🔹 What is a Message Broker?

A **message broker** is a software system that enables different applications, services, or systems to communicate by **sending, receiving, and routing messages**. Instead of services directly talking to each other (tight coupling), a broker **decouples** them, making communication more **reliable, scalable, and fault-tolerant**.

## 🔹 Why Do We Need Message Brokers?

* **Decoupling** → Services don’t need to know about each other.

* **Reliability** → Ensures no data loss with persistence and acknowledgments.

* **Scalability** → Multiple consumers can process workload in parallel.

* **Asynchronous Processing** → Producers don’t need to wait for consumers.

* **Cross-Platform Integration** → Works across different languages and systems.

## 🔹 Core Features of Message Brokers

1. **Queueing** – Stores messages until consumed.

2. **Publish/Subscribe (Pub/Sub)** – One message can be delivered to multiple subscribers.

3. **Routing** – Directs messages based on rules, topics, or headers.

4. **Persistence** – Stores messages on disk for durability.

5. **Acknowledgments** – Guarantees delivery even if a consumer crashes.

6. **Dead Letter Queues (DLQ)** – Stores undelivered messages for troubleshooting.

## 🔹 Popular Message Brokers in the Industry

| Broker                | Best Use Case                         | Key Features                                      |

| --------------------- | ------------------------------------- | ------------------------------------------------- |

| RabbitMQ| Complex routing & enterprise apps     | AMQP protocol, durable queues, flexible routing   |

| Apache Kafka| Event streaming & real-time analyticsHigh throughput, distributed log-based system     |

| ActiveMQ         | Java ecosystem | Supports JMS, good for legacy integration         |

| Amazon SQS| Cloud-native queueing                 | Fully managed, integrates with AWS ecosystem      |

| Azure Service Bus | Enterprise cloud apps                 | FIFO, sessions, dead-lettering, security features |

| Google Pub/Sub    | Event-driven GCP apps           | Global scalability, real-time streaming           |

## 🔹 Real-Life Example: E-Commerce Application

Imagine an **e-commerce platform**:

* A customer **places an order**.

* The app sends this order message to the **message broker**.

* Multiple services consume the message:

  * **Inventory Service** → Updates stock.

  * **Billing Service** → Processes payment.

  * **Notification Service** → Sends confirmation email/SMS.

Without a broker, each service would directly call the others, leading to **tight coupling, higher failures, and poor scalability**.

## 🔹 Advantages and Disadvantages

✅ **Advantages:**

* Decouples services for flexible architecture.

* Handles failures gracefully.

* Improves scalability and reliability.

* Supports asynchronous and real-time communication.

⚠️ **Disadvantages:**

* Adds complexity in deployment and monitoring.

* May introduce slight latency compared to direct calls.

* Requires proper schema and version management.

## 🔹 Final Thoughts

Message brokers are the **backbone of modern distributed systems**. Whether you’re building **microservices, IoT solutions, or cloud-based applications**, choosing the right broker (Kafka, RabbitMQ, SQS, etc.) is crucial for reliability and scalability.

By using message brokers, you can ensure **smooth, reliable, and efficient communication** across your application ecosystem.

Docker: A Complete Guide for Beginners

 In the world of modern software development, **Docker** has become one of the most powerful tools for building, packaging, and deploying applications. Whether you’re working on microservices, cloud-native applications, or DevOps pipelines, Docker simplifies the way developers manage and run their applications across environments.

In this article, we’ll cover what Docker is, why it is important, its key concepts, and real-world use cases.

 What is Docker?

Docker is an **open-source platform** designed to automate the deployment of applications inside **lightweight, portable containers**.

Unlike traditional virtual machines (VMs), which emulate entire operating systems, Docker containers share the same OS kernel but run in isolated environments. This makes them **faster, smaller, and more efficient**.

Why Use Docker?

Here are some of the main benefits:

* 🚀 **Portability**: Run your application anywhere — local machine, on-premise servers, or cloud platforms.

* ⚡ **Performance**: Containers are lightweight compared to VMs, leading to faster startup times.

* 🔄 **Consistency**: “Works on my machine” problem is solved — the same container runs the same way across all environments.

* 🛠 **Scalability**: Docker integrates well with orchestration tools like **Kubernetes** for scaling applications.

* 🔐 **Isolation**: Each container is isolated, ensuring security and minimal conflicts between dependencies.

 Key Concepts in Docker

### 1. Docker Image

An **image** is a read-only blueprint for creating containers. It includes your application code, dependencies, and runtime environment.

Example: A Python app image may include Python runtime, pip packages, and your code.

### 2. Docker Container

A **container** is a running instance of an image. It’s lightweight, fast, and can be started, stopped, or destroyed without affecting the host system.

### 3. Dockerfile

A **Dockerfile** is a script containing instructions to build an image.

Example:

dockerfile

# Use Python as the base image

FROM python:3.10

# Set working directory

WORKDIR /app

# Copy files into container

COPY . /app

# Install dependencies

RUN pip install -r requirements.txt

# Run the application

CMD ["python", "app.py"]

### 4. Docker Hub

Docker Hub is a public repository where you can **find and share images**. Example: `docker pull nginx` downloads the latest Nginx image.

## Basic Docker Commands

Here are some commonly used commands:

```bash

# Check Docker version

docker --version  

# Pull an image from Docker Hub

docker pull nginx  

# Run a container from an image

docker run -d -p 8080:80 nginx  

# List running containers

docker ps  

# Stop a container

docker stop <container_id>  

# Build an image from Dockerfile

docker build -t myapp .  

## Real-World Use Cases of Docker

1. **Microservices Development** – Running each service in its own container.

2. **CI/CD Pipelines** – Automating testing and deployment.

3. **Cloud Deployments** – Docker containers can run seamlessly on AWS, Azure, or GCP.

4. **Legacy Application Modernization** – Packaging old applications into containers to run in modern environments.

5. **Learning & Experimentation** – Developers can quickly test new technologies in isolated environments.

## Docker vs Virtual Machines

| Feature        | Docker Containers | Virtual Machines |

| -------------- | ----------------- | ---------------- |

| Startup Time   | Seconds           | Minutes          |

| Resource Usage | Lightweight       | Heavy            |

| Portability    | High              | Limited          |

| Performance    | Near Native       | Slower           |

| Isolation      | Process-level     | Hardware-level   |

## Conclusion

Docker has transformed how applications are built, shipped, and run. By providing **speed, consistency, and scalability**, it has become a must-have tool in every developer’s toolkit. Whether you’re working on a personal project or an enterprise-level system, Docker can simplify your workflow and ensure smoother deployments.

👉 If you’re just starting out, try creating your first Dockerfile and running a simple container. From there, you’ll discover the endless possibilities Docker brings to modern development.

Load Balancing in Web API Traffic: A Complete Guide

In today’s digital world, applications are expected to deliver **high availability, scalability, and reliability**. As user traffic grows, a single Web API server may struggle to handle all incoming requests, leading to slow responses or even downtime. This is where **load balancing** comes into play.

What is Load Balancing in Web APIs?

Load balancing is the process of distributing **incoming API traffic** across multiple servers (or instances) so that no single server becomes a bottleneck. It ensures:

* **High Availability** – If one server goes down, others continue serving requests.

* **Scalability** – As traffic increases, new servers can be added behind the load balancer.

* **Performance Optimization** – Requests are routed intelligently, reducing response time.

In short, load balancing acts as a **traffic manager** for your Web APIs.

Why is Load Balancing Important for Web APIs?

1. **Handles High Traffic Loads** – During peak hours, APIs often receive thousands or millions of requests.

2. **Reduces Server Failures** – If one server crashes, requests are automatically redirected.

3. **Improves Response Times** – Traffic is routed to the nearest or least busy server.

4. **Enhances Security** – Load balancers can filter malicious requests before reaching backend servers.

Load Balancing Strategies

Different algorithms decide **how traffic is distributed** across API servers. Common strategies include:

1. **Round Robin**

   * Requests are sent to servers in sequence.

   * Simple and effective for equal-capacity servers.

2. **Least Connections**

   * Routes traffic to the server with the fewest active connections.

   * Useful for APIs with long-running requests.

3. **IP Hash**

   * Assigns clients to servers based on their IP address.

   * Good for maintaining **session persistence**.

4. **Weighted Distribution**

   * Servers are assigned weights based on capacity (CPU, RAM).

   * High-capacity servers handle more requests.

Types of Load Balancers

1. **Hardware Load Balancers**

   * Physical devices (expensive but powerful).

   * Used in enterprise data centers.

2. **Software Load Balancers**

   * Run on standard servers (e.g., Nginx, HAProxy).

   * Flexible and cost-effective.

3. **Cloud Load Balancers**

   * Provided by cloud vendors like **Azure Application Gateway, AWS Elastic Load Balancer, GCP Load Balancing**.

   * Auto-scaling, global reach, and integrated monitoring.

 Load Balancing in Web API Architecture

Here’s a simplified flow:

1. **Client** sends an API request.

2. **Load Balancer** receives the request.

3. Load balancer applies algorithm (Round Robin, Least Connections, etc.).

4. Request is forwarded to one of the available **API servers**.

5. **Response** is returned to the client.

This ensures **even workload distribution** and **zero downtime** in case of server failure.

Best Practices for Load Balancing Web APIs

* Use **health checks** to detect and remove unhealthy servers.

* Implement **SSL termination** at the load balancer for security.

* Enable **caching** for repeated requests to reduce load.

* Monitor traffic patterns and **auto-scale servers** when demand increases.

* Use **global load balancing** if your users are worldwide.

 Conclusion

Load balancing is not just a performance booster—it is a **survival mechanism** for modern APIs. By distributing traffic efficiently, it ensures your Web APIs remain **fast, reliable, and always available** to users. Whether you use hardware, software, or cloud-based solutions, implementing the right load balancing strategy is a critical step toward building scalable API-driven applications.

Throttling in Web API – A Complete Guide

APIs are the backbone of modern applications, but if not protected, they can be overwhelmed by excessive requests from clients. To ensure **fair usage, reliability, and performance**, we use **Throttling** in Web API.

🔹 What is Throttling?

Throttling is a mechanism that **limits the number of API requests a client can make within a given time frame**. It prevents abuse, protects server resources, and ensures all clients get a fair share of the system’s capacity.

For example:

* A client is allowed only **100 requests per minute**.

* If they exceed the limit, the API returns **HTTP 429 (Too Many Requests)**.

 🔹 Why Do We Need Throttling?

* ✅ **Prevents server overload** – Protects from heavy traffic or denial-of-service (DoS) attacks.

* ✅ **Fair usage policy** – Ensures no single user hogs all the resources.

* ✅ **Cost efficiency** – Reduces unnecessary server and bandwidth usage.

* ✅ **Improved reliability** – Keeps the API stable and consistent.

 🔹 Throttling Strategies

There are multiple approaches to implement throttling:

1. **Fixed Window**

   * Restricts requests in fixed time slots.

   * Example: 100 requests allowed between 12:00–12:01.

2. **Sliding Window**

   * Uses a rolling time frame for more accuracy.

   * Example: If a request is made at 12:00:30, the limit resets at 12:01:30.

3. **Token Bucket**

   * A bucket holds tokens, each request consumes one. Tokens refill at a fixed rate.

   * Allows short bursts of traffic until the bucket is empty.

4. **Leaky Bucket**

   * Similar to Token Bucket but processes requests at a fixed outflow rate.

   * Ensures smooth traffic flow without sudden spikes.

 🔹 Implementing Throttling in .NET Web API

 ✅ Option 1: Custom Middleware

You can create your own middleware to limit requests per client:

`csharp

public class ThrottlingMiddleware

{

    private static Dictionary<string, (DateTime timestamp, int count)> _requests = new();

    private readonly RequestDelegate _next;

    private const int LIMIT = 5; // max 5 requests

    private static readonly TimeSpan TIME_WINDOW = TimeSpan.FromMinutes(1);

    public ThrottlingMiddleware(RequestDelegate next) => _next = next;

    public async Task Invoke(HttpContext context)

    {

        var clientIp = context.Connection.RemoteIpAddress?.ToString();

        if (_requests.ContainsKey(clientIp))

        {

            var (timestamp, count) = _requests[clientIp];

            if ((DateTime.Now - timestamp) < TIME_WINDOW)

            {

                if (count >= LIMIT)

                {

                    context.Response.StatusCode = StatusCodes.Status429TooManyRequests;

                    await context.Response.WriteAsync("Too many requests. Try again later.");

                    return;

                }

                _requests[clientIp] = (timestamp, count + 1);

            }

            else

            {

                _requests[clientIp] = (DateTime.Now, 1);

            }

        }

        else

        {

            _requests[clientIp] = (DateTime.Now, 1);

        }

        await _next(context);

    }

}

Register in **Program.cs**:

csharp

app.UseMiddleware<ThrottlingMiddleware>();

 ✅ Option 2: Built-in Rate Limiting in .NET 7+

ASP.NET Core 7 introduced built-in **Rate Limiting Middleware**:

```csharp

builder.Services.AddRateLimiter(options =>

{

    options.AddFixedWindowLimiter("Fixed", opt =>

    {

        opt.Window = TimeSpan.FromSeconds(10);

        opt.PermitLimit = 5;  // 5 requests per 10 seconds

        opt.QueueLimit = 2;

        opt.QueueProcessingOrder = QueueProcessingOrder.OldestFirst;

    });

});

app.UseRateLimiter();

Apply to a specific endpoint:

```csharp

app.MapGet("/data", () => "Hello")

   .RequireRateLimiting("Fixed");

🔹 Best Practices for API Throttling

* Always return **HTTP 429 Too Many Requests** when limits are hit.

* Provide a **Retry-After header** to guide clients on when to retry.

* Implement **per-user or per-IP throttling** for fairness.

* Use **distributed caching (Redis, SQL, etc.)** when running multiple servers.

* Log throttling events to monitor abuse patterns.

🔹 Final Thoughts

Throttling is essential for any production-ready API. It helps maintain **performance, security, and fair usage**. Whether you use a **custom middleware** or the **built-in .NET rate limiter**, implementing throttling ensures your API remains **reliable and scalable**.

API Versioning in ASP.NET Core Web API – A Complete Guide

 When building Web APIs, one inevitable challenge is **change**. As your application grows, you’ll add new features, change contracts, or even remove old functionality. But what happens to existing clients who still depend on the old API?

That’s where **API versioning** comes in. It allows you to evolve your API safely without breaking existing consumers.

 🔑 Why Do We Need API Versioning?

* **Backward compatibility** – Old clients continue to work.

* **Gradual migration** – Clients can upgrade at their own pace.

* **Flexibility** – You can experiment with new versions.

* **Safe deprecation** – Retire old versions without sudden breaks.

 📌 API Versioning Strategies

 1. **URI Path Versioning (Most Common)**

https://api.example.com/v1/customers

https://api.example.com/v2/customers

✅ Easy to use and document

❌ URL changes for every version

 2. **Query String Versioning**

https://api.example.com/customers?api-version=1.0

✅ Very simple to implement

❌ Not as RESTful (query strings are usually for filters)

3. **Header Versioning**

GET /customers

Header: api-version: 1.0

✅ Keeps URLs clean

❌ Requires client to manage headers

 4. **Content Negotiation (Media Type)**

Accept: application/json; version=1.0

✅ Standards-friendly

❌ More complex to manage

 ⚙️ Implementing Versioning in ASP.NET Core

Microsoft provides a handy NuGet package for API versioning:

powershell

Install-Package Microsoft.AspNetCore.Mvc.Versioning

 Step 1: Configure Services

csharp

public void ConfigureServices(IServiceCollection services)

{

    services.AddControllers();

    services.AddApiVersioning(options =>

    {

        options.DefaultApiVersion = new ApiVersion(1, 0); 

        options.AssumeDefaultVersionWhenUnspecified = true;

        options.ReportApiVersions = true; // Adds headers like api-supported-versions

        options.ApiVersionReader = new UrlSegmentApiVersionReader(); 

        // Options: QueryStringApiVersionReader("api-version") 

        //          HeaderApiVersionReader("x-api-version")

    });

}

Step 2: Create Versioned Controllers

`csharp

[ApiVersion("1.0")]

[Route("api/v{version:apiVersion}/customers")]

[ApiController]

public class CustomersV1Controller : ControllerBase

{

    [HttpGet]

    public IActionResult Get() => Ok("Customer list from V1");

}

[ApiVersion("2.0")]

[Route("api/v{version:apiVersion}/customers")]

[ApiController]

public class CustomersV2Controller : ControllerBase

{

    [HttpGet]

    public IActionResult Get() => Ok("Customer list from V2 with new fields");

}

 Step 3: Testing Requests

* `GET /api/v1/customers` → handled by **V1 controller**

* `GET /api/v2/customers` → handled by **V2 controller**

## 🔧 Best Practices for API Versioning

1. Use **URI path versioning** for public APIs (clear & user-friendly).

2. Use **Header or Media Type versioning** for internal APIs (cleaner approach).

3. Always **document versions** using Swagger (OpenAPI).

4. Define a **deprecation strategy** – mark old versions and set timelines for removal.

 ✅ Conclusion

API versioning is essential for **scalable, maintainable, and client-friendly** Web APIs. In ASP.NET Core, you can easily implement versioning using the official `Microsoft.AspNetCore.Mvc.Versioning` package.

By planning your versioning strategy early, you ensure smooth upgrades for clients and keep your API future-proof.