Skip to main content

Observer Pattern in Java Explained with Story & Real Example (2025 Guide)

 Observer Pattern Explained: From School Bell to Order Events


🎯 Why This Pattern Matters

In interviews, design patterns often pop up, and the Observer Pattern is one of the most asked. Instead of memorizing theory, let’s connect it to a story you’ll never forget — and then translate it into practical Java code you can actually show in an interview


📖 Story Analogy — The School Bell


Think back to school days:

At 12:30 PM, the bell rings.

Students run to lunch.

Teachers close books.

The peon opens gates.


👉 The bell (Subject) doesn’t know or care who reacts. Each Observer does its own thing when notified.


That’s the Observer Pattern: one subject, many independent observers reacting differently.

🧑‍💻 Practical Java Example — Order Placed Event


Let’s switch from school to a real project example: e-commerce order placement.

When an order is placed:

Send confirmation email

Write an audit log

Update metrics


Instead of hard-coding all in the service, we publish an event. Observers (listeners) handle their part.


Minimal Code

// Event class

class OrderPlacedEvent {

    String orderId;

    OrderPlacedEvent(String orderId) { this.orderId = orderId; }

}


// Subject (Publisher)

class OrderService {

    private List<Observer> observers = new ArrayList<>();

    void addObserver(Observer o) { observers.add(o); }


    void placeOrder(String orderId) {

        System.out.println("Order placed: " + orderId);

        notifyObservers(new OrderPlacedEvent(orderId));

    }


    private void notifyObservers(OrderPlacedEvent event) {

        for (Observer o : observers) o.update(event);

    }

}


// Observer interface

interface Observer {

    void update(OrderPlacedEvent event);

}


// Observers

class EmailService implements Observer {

    public void update(OrderPlacedEvent e) {

        System.out.println("📧 Email sent for order " + e.orderId);

    }

}


class AuditLog implements Observer {

    public void update(OrderPlacedEvent e) {

        System.out.println("🧾 Audit log created for order " + e.orderId);

    }

}


// Demo

public class ObserverDemo {

    public static void main(String[] args) {

        OrderService service = new OrderService();

        service.addObserver(new EmailService());

        service.addObserver(new AuditLog());


        service.placeOrder("ORD-101");

    }

}


Output:


Order placed: ORD-101

📧 Email sent for order ORD-101

🧾 Audit log created for order ORD-101


🧠 How to Explain in an Interview

“Observer Pattern allows one subject to notify multiple observers independently.”

“In real systems, we use it for event-driven flows — e.g., when an order is placed, many services react without tight coupling.”


“In Spring Boot, this is implemented with @EventListener and ApplicationEventPublisher.”


✅ Conclusion

Story: Remember the school bell → one event, many reactions.


Practice: Show a minimal “order placed” code sample.


Interview-ready: Map it to Spring events or message queues in real projects.

Comments

Popular posts from this blog

Using Java 8 Streams to Find the Second-Highest Salary in an Employee List

To find the second-highest salary from a list of employees using Java 8 streams, you can follow these steps: Create a list of employees with their salaries. Use Java 8 streams to sort the employees by salary in descending order. Skip the first element (which is the employee with the highest salary). Get the first element of the remaining stream (which is the employee with the second-highest salary). Example code: java import java.util.ArrayList; import java.util.List; class Employee { private String name; private double salary; public Employee (String name, double salary) { this .name = name; this .salary = salary; } public double getSalary () { return salary; } } public class SecondHighestSalary { public static void main (String[] args) { List<Employee> employees = new ArrayList <>(); employees.add( new Employee ( "John" , 60000.0 )); employees.add( new Employe...

Java Data Structures and Algorithms: A Practical Guide with Examples and Top Interview Questions"

Data Structures and Algorithms in Java Understanding Data Structures ArrayList When to Use: Use ArrayList when you need a dynamic array that can grow or shrink in size. It's efficient for random access but less efficient for frequent insertions and deletions. Example Code: java List<String> arrayList = new ArrayList <>(); arrayList.add( "Java" ); arrayList.add( "Data Structures" ); arrayList.add( "Algorithms" ); LinkedList When to Use: LinkedList is suitable for frequent insertions and deletions. It provides better performance than ArrayList in scenarios where elements are frequently added or removed from the middle of the list. Example Code: java LinkedList<String> linkedList = new LinkedList <>(); linkedList.add( "Java" ); linkedList.add( "Data Structures" ); linkedList.add( "Algorithms" ); HashMap When to Use: Use HashMap for fast retrieval of data based on a key. It is efficient for loo...

Mastering Java Streams: A Complete Guide with Examples and Interview Questions

Java Streams have revolutionized the way data processing tasks are handled in Java programming. Introduced in Java 8, Streams offer a fluent and functional approach to processing collections of objects. In this guide, we'll delve into what Streams are, how they work, and provide practical examples along the way. Understanding Java Streams: Java Streams represent a sequence of elements that can be processed sequentially or in parallel. They provide a pipeline through which data can be manipulated using various operations such as filtering, mapping, sorting, and aggregating. Benefits of Java Streams: Concise and Readable Code : Streams promote a functional programming style, leading to more concise and readable code compared to traditional imperative approaches. Lazy Evaluation : Stream operations are lazily evaluated, meaning elements are processed only when necessary, improving efficiency. Parallelism : Streams can leverage parallel processing for improved performance on multicore ...

Subscribe to get new posts

Name

Email *

Message *