Angular Performance Optimization Techniques: Lazy Loading, Change Detection, and More

Performance is crucial in the realm of contemporary web development in order to deliver a smooth and responsive user experience. Developers may easily create scalable applications with Angular’s robust and feature-rich framework. However, if performance is not adequately maintained, it might become a bottleneck as applications get bigger and more complicated.

To greatly increase the speed and responsiveness of your Angular apps, we’ll go over several best practices for Angular performance optimization, such as effective change detection strategies, lazily loading modules, and other best practices. Working with a seasoned Angular Development Company or obtaining an Angular Development Consultation can offer the strategic guidance required to sustain the speed and effectiveness of your application, regardless of the project’s size.

1. Lazy Loading Modules

Lazy loading is one of the most effective ways to enhance Angular application performance. Instead of loading the entire application at once, lazy loading allows you to load feature modules only when they are required. As a result, perceived performance is enhanced and the initial load time is decreased. Angular Performance Optimization involves applying such strategic techniques to ensure your app remains fast, scalable, and responsive as it grows in complexity.

How to Implement Lazy Loading:

• Use Angular routing to define loadChildren for modules.
• Organize your application into feature modules.
• Ensure modules are isolated and have their routing configuration.

Example:

const routes: Routes = [
  {
    path: ‘admin’,
    loadChildren: () => import(‘./admin/admin.module’).then(m => m.AdminModule)
  }
];

2. Optimizing Change Detection

Angular’s change detection mechanism is powerful but can be performance-heavy if not optimized.

OnPush Change Detection Strategy

Use ChangeDetectionStrategy.OnPush to limit the component’s change detection to only when its inputs change.

Example:

@Component({
  selector: ‘app-sample’,
  templateUrl: ‘./sample.component.html’,
  changeDetection: ChangeDetectionStrategy.OnPush
})

Detach Change Detector When Needed

For rarely changing components, detach the change detector manually to reduce the overhead.

constructor(private cdRef: ChangeDetectorRef) {
  cdRef.detach();
}

3. TrackBy in *ngFor

When using *ngFor, Angular re-renders DOM elements when data changes. Implement trackBy to improve performance by tracking items by a unique identifier.

Example:

<li *ngFor=”let item of items; trackBy: trackByFn”>{{ item.name }}</li>
trackByFn(index: number, item: any): number {
  return item.id;
}

4. Avoid Memory Leaks

Unsubscribe from observables and DOM events to prevent memory leaks, especially in large applications.

• Use takeUntil with a Subject
• Use an async pipe when possible

5. Code Splitting and Preloading Strategy

Implement code splitting and use Angular’s PreloadAllModules strategy to balance lazy loading and faster navigation.

Example:

RouterModule.forRoot(routes, {

  preloadingStrategy: PreloadAllModules

})

6. Ahead-of-Time (AOT) Compilation

AOT compilation is the process of compiling Angular templates and components during the build phase, rather than in the browser at runtime.

How it helps:

• Faster Rendering: Since the templates are pre-compiled, Angular doesn’t need to compile them at runtime, resulting in faster rendering of the app.
• Smaller Bundles: AOT reduces the size of the final JavaScript bundles by eliminating unnecessary code and optimizing template generation.
• Improved Security: AOT prevents XSS (Cross-Site Scripting) attacks by sanitizing templates at compile time.

7. Avoiding Unnecessary Pipe Transformations

Pipes are used to transform data in templates, but Angular’s default change detection will trigger re-evaluation of pipes whenever any change occurs in the component.

How it helps:

• Performance Gains: By avoiding unnecessary pipe transformations (e.g., using pure pipes), you reduce the computational overhead caused by repeated transformations.
• Always use pure pipes (which are default) for computations that don’t need to be recalculated on every change detection cycle.

Example:

@Pipe({
  name: ‘purePipe’,
  pure: true  // This ensures that the pipe is only executed when its input changes
})
export class PurePipe implements PipeTransform {
  transform(value: any): any {
    return value * 2;
  }
}