Learn a practical observer design you can use in code today. This guide defines the observation pattern technique (also called the Observer pattern) and shows how it helps you react to meaningful events instead of constantly polling for state.

You’ll see the core roles: a publisher (subject) that maintains a list and one or more subscribers (observers). You get a clear view of how notifications flow through a system and why an interface keeps classes loosely coupled.

This solves a common problem in apps: wasting time polling or flooding components with irrelevant updates. By the end, you’ll be ready to sketch a high-level UML, explain when to use observer design, and build a working example with add/remove and notify methods.

For a psychology-oriented take on direct recording and event-driven data, see this short reference at direct observation methods.

What the Observer Design Pattern Solves in Real Systems

Real systems face two common costs: repeated polling and noisy broadcast updates. The observer design is a simple method that helps you avoid both. It defines a subscription flow where a subject pushes updates only when an object changes state.

The core tradeoff is clear: polling wastes time and CPU, while spamming every listener wastes bandwidth and annoys users.

The triggers you see in apps today

• Events: clicks, keystrokes, or messages that start a notification.
• State updates: a stock price or weather reading that changes value.
• Change signals: configuration or user status changes that matter to other components.

Everyday examples

You already use this in social feeds, stock alerts, GUI listeners, and weather displays. In each case, observers subscribe to a subject so relevant information flows without tight coupling.

Practical result: fewer wasted operations, cleaner business logic, and easier scaling as the number of observers grows.

How the observation pattern technique Works Under the Hood

Imagine a central object that owns the data and a set of listeners that respond when that data shifts. This is the simplest mental model you can use when you draw UML or debug your design. It keeps business logic distinct from the parts that react to changes.

Publisher versus subscriber

The publisher (often called the subject) holds the interesting state. It provides methods to change that state and to add or remove subscribers.

Subscription mechanism

The subject maintains a list (or a map keyed by event type) of references to observers. You implement add/remove methods to manage that list safely at runtime.

Notification flow

When an event occurs, the subject iterates the list and calls a notification method, commonly update, on each observer. That method is the single, predictable entry point for reactions.

Why an interface matters

Define a shared interface for observers so the subject only depends on that type. This prevents tight coupling to concrete classes and lets you swap in loggers, email senders, or UI widgets without changing the subject.

“Keep the subject focused on state and the observers focused on response.”

Finally, choose a payload style: push to send data directly, or pull to pass the subject and let observers query the state. Either way, the under-the-hood model is the same: list management, method calls, and clear boundaries between system components.

When You Should Use the Observer Pattern (and When You Shouldn’t)

Choose this approach when a change in one object may need to update many other components in your system. It shines if the number of observers is unknown at design time or if subscribers appear and disappear while the app runs.

Good fit cases: dynamic GUIs, plugin systems, real-time feeds, and integration points where you add/remove listeners at runtime to avoid wasted work.

When to avoid it

Don’t use it for rigid, fixed relationships between two classes. If only two objects interact, simple direct calls are clearer and faster.

Also avoid it when notification overhead hurts performance. A subject that updates too frequently with a long list of observers can create latency and memory pressure.

Order caveat and practical guidance

Notifications may arrive in an unpredictable sequence. Do not encode correctness around update order. If order matters, add sequence controls or a coordinator object instead of relying on observer notification order.

Use case	Why it fits	What to watch for
Dynamic subscribers (UI, plugins)	Scales without changing the subject	Manage add/remove and avoid leaks
Temporary listeners (dialogs, short tasks)	Enable limited-time observation	Ensure unregistering on teardown
Fixed relationships (one-to-one)	Not necessary	Prefer direct method calls
High-frequency updates	Can flood observers	Throttle updates or batch notifications

Quick rule: pick the observer design when the number of observers is unknown, changes over time, or must scale without rewriting the subject. Otherwise, choose simpler coordination.

Key Components You’ll Implement in Code

Begin with the exact interfaces and methods you must code to keep responsibilities clear. A small, consistent API makes your implementation easier to test and reason about.

Subject / publisher interface

Define three required methods: addObserver, removeObserver, and notifyObservers.

These methods let the subject maintain a list of observers and trigger notifications when relevant state changes.

Observer interface

Create a simple update() signature. Decide whether update receives a data payload or a reference to the subject.

Keep the interface small so different classes can implement reactions like UI refreshes, logging, or alerts without heavy coupling.

ConcreteSubject and ConcreteObserver classes

Your ConcreteSubject owns business logic and calls notifyObservers when the object changes state.

ConcreteObservers implement update() and focus on reactions only. This prevents the subject from becoming a “god class.”

Data payload design

Compare two choices: push the context (event type and data) to make observers independent, or pull by passing the subject so observers query needed information.

Push reduces observer queries and improves testability. Pull can reduce duplicate data but raises coupling.

“Keep subscription code separate from core business logic so components stay focused and testable.”

UML-oriented breakdown

Communicate interfaces and implementations with a simple diagram: ISubject / IObserver -> ConcreteSubject / ConcreteObserver. This makes roles explicit for teammates.

For a hands-on walkthrough and a compact example you can follow, see the Unity course on creating modular code with the observer approach: create modular and maintainable code with the observer.

Step-by-Step Implementation Method for Your App

Begin with a clear split: business objects own state and lightweight listeners handle reactions. This keeps your system testable and reduces coupling.

Separate core logic and reactions

Move state and business logic into a subject and put UI, logging, or side effects into small observer classes. That makes each class easier to maintain.

Design events and decide what’s “interesting”

List the events that truly matter. If every change is an event, you’ll spam observers. Choose clear event types and payloads up front.

Inheritance or composition for subscriptions

Prefer composition when your publisher already extends another class. Use an abstract base publisher only when many subjects share the same list-management behavior.

Build and manage the observer container

Store observers in a safe container (List or HashSet). Handle add/remove while iterating by copying or marking removals to avoid missed notifications.

Wire it up and test in the client

In the client: create a subject, register observers, trigger state changes, and verify notifications arrive. Include tests that confirm unsubscribe works and payloads are correct.

• Quick checklist: observers can unsubscribe, notification payloads match, system scales when the number of observers changes.

Walkthrough Example: Event Manager + Editor Notifications

See how a small EventManager keeps your Editor focused while listeners handle logging and alerts.

The EventManager maintains a hash map of event names to listener lists. It exposes three clear methods: subscribe, unsubscribe, and notify. Each listener implements an EventListener interface with update(filename).

Event types and listeners: subscribe, unsubscribe, notify

Your Editor uses composition: it has an EventManager and calls notify(“open”, filename) or notify(“save”, filename) when files change. The manager looks up the list for that event and calls update(filename) on each listener.

Adding observers without changing the publisher

Implement a LoggingListener that writes a short message to a log file. You register it for the “open” event and never touch the Editor’s logic. That makes the system open for extension and closed for modification.

Multiple observers for the same subject

Add an EmailAlertsListener for the “save” event. Now the same subject emits one notification and multiple observers react differently. This shows how the design keeps your core class small while features like notifications and logging live in their own classes.

“Keep the publisher simple: let observers own side effects and cross-cutting concerns.”

Advanced Variations and Platform Notes for Present-Day Development

Large projects often need many subjects and many observers working together. You’ll design shared interfaces so publishers and listeners interoperate across modules. This scales the system without tight coupling.

Many-to-many relationships

Allow multiple publishers to emit events and multiple observers to subscribe across features. Use a small, predictable interface for each event type so code stays modular.

.NET: IObservable<T> and IObserver<T>

In .NET you implement System.IObservable<T> and System.IObserver<T&gt. Providers call OnNext, OnError, and OnCompleted to deliver notifications in a consistent way.

Unsubscribe and memory management

Return an IDisposable from Subscribe so observers call Dispose to unregister. This prevents lingering references and memory leaks in long-running services.

Documentation and UML

Document which interface each class implements and list responsibilities for publishers versus observers. A compact UML diagram makes roles and dependencies clear to teammates.

Mediator vs Observer

Use a Mediator when you need a central coordinator. Use observer-style subscriptions for lightweight, dynamic notifications. Both are valid design choices depending on component coupling and control needs.

Conclusion

Conclude by turning the theory into a tiny, runnable demo that shows notifications flowing.

Now you can model a one-to-many dependency where observers automatically react when the subject changes. You get less wasted checking, fewer noisy updates, and a cleaner split between business logic and reaction code.

Keep three core building blocks: a small interface for updates, a subscription container to manage listeners, and a consistent update contract that each class implements. Reuse that trio across features so new subscribers plug in without changing the subject.

Use this approach when the number of observers is unknown or changes at runtime. For your next step, wire up the EventManager + listeners demo or the .NET IObservable<T> flow and validate it with a short, testable feature.