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Accelerating Web Applications: Optimizing API Design and Angular Frontend Performance with Node.js and LoopBack 4

Saurav Bhargava
14 min read1 day ago

--

Introduction

Welcome to the third installment of our series on mastering performance optimization in web applications. Building on the foundational strategies discussed in our previous posts — diagnosing performance issues and database/backend optimization — today we shift our focus to enhancing API efficiency and optimizing the Angular frontend. Leveraging Node.js, LoopBack 4, and Angular, we’ll explore how to design responsive APIs capable of handling large datasets and implement frontend performance tactics that ensure a smooth and engaging user experience.

Efficient APIs and a performant frontend are critical for delivering fast, reliable, and user-friendly applications. In this blog, we’ll delve into designing scalable APIs with pagination and filtering, managing large data operations asynchronously, and optimizing the Angular frontend using asynchronous operations and modern JavaScript techniques. Through technical insights and practical code examples, you’ll gain the knowledge to elevate your web application’s performance to new heights.

Designing Responsive APIs and Managing Large Datasets Efficiently

APIs serve as the backbone of modern web applications, facilitating communication between the frontend and backend. Designing responsive APIs that can handle large datasets efficiently is paramount for maintaining swift application performance and ensuring a seamless user experience.

Principles of Responsive API Design

Creating responsive APIs involves several key principles:

  • Statelessness: Each API request should contain all the information necessary to process it, without relying on stored context. This ensures scalability and simplifies server-side logic.
  • Efficient Data Retrieval: APIs should fetch only the data required by the client, minimizing payload sizes and reducing processing overhead.
  • Pagination and Filtering: Implementing pagination and filtering mechanisms prevents the server from overloading with large data requests and allows clients to retrieve data in manageable chunks.
  • Asynchronous Processing: For operations that involve large datasets or time-consuming processes, asynchronous endpoints prevent the server from becoming unresponsive.

Implementing Pagination and Filtering in LoopBack 4

LoopBack 4 provides robust support for implementing pagination and filtering, essential for managing large datasets efficiently.

Example: Implementing Pagination and Filtering

// src/controllers/keyword.controller.ts
import { get, param, Response, RestBindings } from '@loopback/rest';
import { repository } from '@loopback/repository';
import { KeywordRepository } from '../repositories';
import { inject } from '@loopback/core';

export class KeywordController {
  constructor(
    @repository(KeywordRepository)
    public keywordRepository: KeywordRepository,
  ) {}
  @get('/keywords')
  async getKeywords(
    @param.query.string('search') search: string,
    @param.query.number('limit') limit: number = 100,
    @param.query.number('offset') offset: number = 0,
    @inject(RestBindings.Http.RESPONSE) response: Response,
  ): Promise<void> {
    response.setHeader('Content-Type', 'application/json');
    const keywords = await this.keywordRepository.find({
      where: { name: { like: `%${search}%` } },
      limit: limit,
      skip: offset,
      order: ['name ASC'],
    });
    response.status(200).json(keywords);
  }
}

In this example, the getKeywords endpoint allows clients to search for keywords with pagination support. By specifying limit and offset query parameters, clients can retrieve data in chunks, reducing the load on both the server and the client.

Asynchronous API Endpoints for Large Data Operations

For operations involving extensive data processing, asynchronous APIs ensure that the server remains responsive by handling tasks in the background.

Example: Asynchronous Data Processing Endpoint

// src/controllers/keyword.controller.ts
import { post, requestBody, Response, RestBindings } from '@loopback/rest';

export class KeywordController {
  // ...constructor and other methods...
  @post('/keywords/process')
  async processKeywords(
    @requestBody() payload: { search: string },
    @inject(RestBindings.Http.RESPONSE) response: Response,
  ): Promise<void> {
    response.setHeader('Content-Type', 'application/json');
    response.status(202).json({ message: 'Keyword processing started.' });
    // Asynchronously process keywords
    this.handleKeywordProcessing(payload.search);
  }
  private async handleKeywordProcessing(search: string): Promise<void> {
    try {
      const keywords = await this.keywordRepository.find({
        where: { name: { like: `%${search}%` } },
      });
      for (const keyword of keywords) {
        await this.processKeyword(keyword);
      }
      console.log('Keyword processing completed.');
    } catch (error) {
      console.error('Error processing keywords:', error);
    }
  }
  private async processKeyword(keyword: any): Promise<void> {
    // Simulate an asynchronous operation
    return new Promise((resolve) => setTimeout(resolve, 10));
  }
}

This approach ensures that intensive processing does not block the main thread, maintaining API responsiveness. Clients receive an immediate acknowledgment (202 Accepted) while the server handles the processing in the background.

Frontend Performance Tactics: Asynchronous Operations and Modern JavaScript Techniques in Angular

Optimizing the frontend is just as crucial as backend optimizations. Efficient frontend performance ensures that users experience smooth interactions and swift data rendering, which can significantly enhance user satisfaction and engagement.

Asynchronous Operations in the Frontend

Asynchronous operations allow the frontend to perform tasks without blocking the main thread, ensuring that the user interface remains responsive even during heavy processing tasks.

Example: Fetching Data Asynchronously with Angular’s HttpClient and RxJS

// src/app/keyword.service.ts
import { Injectable } from '@angular/core';
import { HttpClient, HttpParams } from '@angular/common/http';
import { Observable } from 'rxjs';

export interface Keyword {
  id: number;
  name: string;
  path: string;
}
@Injectable({
  providedIn: 'root',
})
export class KeywordService {
  constructor(private http: HttpClient) {}
  getKeywords(search: string, limit: number = 100, offset: number = 0): Observable<Keyword[]> {
    const params = new HttpParams()
      .set('search', search)
      .set('limit', limit.toString())
      .set('offset', offset.toString());
    return this.http.get<Keyword[]>('/api/keywords', { params });
  }
}
// src/app/keyword-list/keyword-list.component.ts
import { Component } from '@angular/core';
import { KeywordService, Keyword } from '../keyword.service';
import { Observable } from 'rxjs';

@Component({
  selector: 'app-keyword-list',
  template: `
    <div>
      <input [(ngModel)]="searchQuery" (input)="fetchKeywords()" placeholder="Search keywords..." />
      <ul>
        <li *ngFor="let keyword of keywords$ | async">{{ keyword.name }}</li>
      </ul>
    </div>
  `,
})
export class KeywordListComponent {
  searchQuery: string = '';
  keywords$!: Observable<Keyword[]>;
  constructor(private keywordService: KeywordService) {}
  fetchKeywords(): void {
    this.keywords$ = this.keywordService.getKeywords(this.searchQuery);
  }
}

In this Angular component, the fetchKeywords method asynchronously fetches keywords based on user input using Angular's HttpClient and RxJS observables. This ensures that the UI remains responsive while the data is being retrieved.

Leveraging Web Workers for Heavy Computations

Web Workers allow you to run scripts in background threads, enabling the main thread to remain free for user interactions. This is particularly useful for performing computationally intensive tasks without causing UI freezes.

Example: Using Web Workers in Angular

Create a Web Worker

Generate a web worker using Angular CLI:

ng generate web-worker keywordProcessor

This command creates a keyword-processor.worker.ts file.

// src/app/keyword-processor.worker.ts
/// <reference lib="webworker" />

addEventListener('message', ({ data }) => {
  const keywords = data as Keyword[];
  const processedKeywords = keywords.map((keyword) => ({
    ...keyword,
    processedName: keyword.name.toUpperCase(),
  }));
  postMessage(processedKeywords);
});

Integrate the Web Worker in the Component

// src/app/keyword-list/keyword-list.component.ts
import { Component, OnDestroy } from '@angular/core';
import { KeywordService, Keyword } from '../keyword.service';

@Component({
  selector: 'app-keyword-list',
  template: `
    <div>
      <input [(ngModel)]="searchQuery" (input)="fetchAndProcessKeywords()" placeholder="Search keywords..." />
      <ul>
        <li *ngFor="let keyword of processedKeywords">{{ keyword.processedName }}</li>
      </ul>
    </div>
  `,
})
export class KeywordListComponent implements OnDestroy {
  searchQuery: string = '';
  keywords: Keyword[] = [];
  processedKeywords: Keyword[] = [];
  worker: Worker | undefined;
  constructor(private keywordService: KeywordService) {
    if (typeof Worker !== 'undefined') {
      this.worker = new Worker(new URL('./keyword-processor.worker', import.meta.url));
      this.worker.onmessage = ({ data }) => {
        this.processedKeywords = data as Keyword[];
      };
    } else {
      console.error('Web Workers are not supported in this environment.');
    }
  }
  fetchAndProcessKeywords(): void {
    this.keywordService.getKeywords(this.searchQuery).subscribe(
      (data) => {
        this.keywords = data;
        if (this.worker) {
          this.worker.postMessage(this.keywords);
        }
      },
      (error) => {
        console.error('Error fetching keywords:', error);
      }
    );
  }
  ngOnDestroy(): void {
    if (this.worker) {
      this.worker.terminate();
    }
  }
}

In this example, the KeywordListComponent sends the fetched keywords to a Web Worker for processing. The worker converts each keyword's name to uppercase, and the processed keywords are then displayed in the UI. This offloads the processing to a background thread, ensuring that the main thread remains responsive.

Using Modern JavaScript Techniques in Angular for Faster Rendering and Data Processing

Modern JavaScript frameworks like Angular provide features that enhance frontend performance through efficient rendering and state management. Leveraging these features can lead to significant improvements in application responsiveness and user experience.

Change Detection Optimization

Angular’s change detection mechanism can be optimized to reduce unnecessary checks and re-renders, enhancing performance.

Example: Using OnPush Change Detection Strategy

// src/app/keyword-list/keyword-list.component.ts
import { Component, ChangeDetectionStrategy } from '@angular/core';
import { KeywordService, Keyword } from '../keyword.service';
import { Observable } from 'rxjs';

@Component({
  selector: 'app-keyword-list',
  template: `
    <div>
      <input [(ngModel)]="searchQuery" (input)="fetchKeywords()" placeholder="Search keywords..." />
      <ul>
        <li *ngFor="let keyword of keywords$ | async">{{ keyword.name }}</li>
      </ul>
    </div>
  `,
  changeDetection: ChangeDetectionStrategy.OnPush,
})
export class KeywordListComponent {
  searchQuery: string = '';
  keywords$!: Observable<Keyword[]>;
  constructor(private keywordService: KeywordService) {}
  fetchKeywords(): void {
    this.keywords$ = this.keywordService.getKeywords(this.searchQuery);
  }
}

By setting the ChangeDetectionStrategy to OnPush, Angular only checks for changes when the component's inputs change, reducing the number of change detection cycles and improving rendering performance.

Virtual Scrolling for Large Lists

Displaying large lists can lead to performance issues due to the rendering of numerous DOM elements. Angular’s cdk-virtual-scroll-viewport provides an efficient way to handle large datasets by rendering only the visible items.

Example: Implementing Virtual Scrolling in Angular

Install Angular CDK

npm install @angular/cdk

Update the Component Template

<!-- src/app/keyword-list/keyword-list.component.html -->
<div>
  <input [(ngModel)]="searchQuery" (input)="fetchAndProcessKeywords()" placeholder="Search keywords..." />
  <cdk-virtual-scroll-viewport itemSize="50" class="viewport">
    <ul>
      <li *cdkVirtualFor="let keyword of processedKeywords">{{ keyword.processedName }}</li>
    </ul>
  </cdk-virtual-scroll-viewport>
</div>

Add Styles for the Viewport

/* src/app/keyword-list/keyword-list.component.css */
.viewport {
  height: 400px;
  width: 100%;
  border: 1px solid #ccc;
}

Ensure Module Imports

// src/app/app.module.ts
import { NgModule } from '@angular/core';
import { BrowserModule } from '@angular/platform-browser';
import { ScrollingModule } from '@angular/cdk/scrolling';
import { FormsModule } from '@angular/forms';
import { HttpClientModule } from '@angular/common/http';

import { AppComponent } from './app.component';
import { KeywordListComponent } from './keyword-list/keyword-list.component';
@NgModule({
  declarations: [AppComponent, KeywordListComponent],
  imports: [BrowserModule, FormsModule, HttpClientModule, ScrollingModule],
  providers: [],
  bootstrap: [AppComponent],
})
export class AppModule {}

By implementing virtual scrolling, only the items visible within the viewport are rendered, significantly improving performance when dealing with large lists.

Lazy Loading Modules

Lazy loading Angular modules ensures that feature modules are loaded only when needed, reducing the initial load time of the application.

Example: Implementing Lazy Loading in Angular

Define a Feature Module

// src/app/keywords/keywords.module.ts
import { NgModule } from '@angular/core';
import { CommonModule } from '@angular/common';
import { KeywordListComponent } from './keyword-list/keyword-list.component';
import { RouterModule, Routes } from '@angular/router';
import { ScrollingModule } from '@angular/cdk/scrolling';
import { FormsModule } from '@angular/forms';

const routes: Routes = [
  {
    path: '',
    component: KeywordListComponent,
  },
];
@NgModule({
  declarations: [KeywordListComponent],
  imports: [CommonModule, FormsModule, ScrollingModule, RouterModule.forChild(routes)],
})
export class KeywordsModule {}

Configure Lazy Loading in the App Routing Module

// src/app/app-routing.module.ts
import { NgModule } from '@angular/core';
import { RouterModule, Routes } from '@angular/router';

const routes: Routes = [
  {
    path: 'keywords',
    loadChildren: () => import('./keywords/keywords.module').then((m) => m.KeywordsModule),
  },
  { path: '', redirectTo: '/keywords', pathMatch: 'full' },
  { path: '**', redirectTo: '/keywords' },
];
@NgModule({
  imports: [RouterModule.forRoot(routes, { preloadingStrategy: NoPreloading })],
  exports: [RouterModule],
})
export class AppRoutingModule {}

By lazy loading the KeywordsModule, the application loads the module only when the user navigates to the /keywords route, reducing the initial bundle size and improving load times.

Case Study: Optimizing API Efficiency and Angular Frontend Performance in a Real-World Application

To illustrate the practical application of these optimization techniques, let’s examine a case study involving a web application that provides budget estimates for advertising campaigns through a stepper form. The application faced performance challenges related to API responsiveness and frontend rendering when handling large datasets of keywords.

Scenario:

The application allowed users to input various parameters to generate budget estimates. One critical feature was the keyword fetching API, which retrieved up to 100,000 keywords based on user input. Users reported slow load times and unresponsive interfaces when interacting with the keyword selection field, especially during peak usage periods.

Step 1: Enhancing API Design for Efficiency

  • Implementing Pagination and Filtering: The development team redesigned the keyword fetching API to include pagination and filtering, enabling clients to retrieve data in smaller, manageable chunks.
// src/controllers/keyword.controller.ts
@get('/keywords')
async getKeywords(
  @param.query.string('search') search: string,
  @param.query.number('limit') limit: number = 100,
  @param.query.number('offset') offset: number = 0,
  @inject(RestBindings.Http.RESPONSE) response: Response,): Promise < void> {
    response.setHeader('Content-Type', 'application/json');
    const keywords = await this.keywordRepository.find({
      where: { name: { like: `%${search}%` } },
      limit: limit, skip: offset, order: ['name ASC'],
    });
    response.status(200).json(keywords);
  }
  • By implementing limit and offset parameters, the API now supports paginated requests, reducing the load on the server and decreasing response times.
  • Asynchronous Processing for Large Data Operations: For operations requiring extensive data processing, the team implemented asynchronous endpoints to handle tasks in the background, preventing the server from becoming unresponsive.
@post('/keywords/process') async processKeywords(@requestBody() payload: { search: string }, @inject(RestBindings.Http.RESPONSE) response: Response,): Promise < void> {
  response.setHeader('Content-Type', 'application/json');
  response.status(202).json({ message: 'Keyword processing started.' });    // Asynchronously process keywords
  this.handleKeywordProcessing(payload.search);
}
private async handleKeywordProcessing(search: string): Promise < void> {
  try {
    const keywords = await this.keywordRepository.find({
      where: { name: { like: `%${search}%` } },
    });
    for(const keyword of keywords) {
      await this.processKeyword(keyword);
      }
     console.log('Keyword processing completed.');
  }
  catch(error) { 
      console.error('Error processing keywords:', error); 
  }
}
private async processKeyword(keyword: any): Promise < void> {
  // Simulate an asynchronous operation
  return new Promise((resolve) => setTimeout(resolve, 10));
}
  • This approach ensures that intensive processing does not block the main thread, maintaining API responsiveness. Clients receive an immediate acknowledgment (202 Accepted) while the server handles the processing in the background.

Step 2: Frontend Optimizations for Enhanced Performance

  • Asynchronous Data Fetching with Angular’s HttpClient: The frontend was updated to fetch keywords asynchronously, allowing users to continue interacting with the interface while data is being retrieved.
// src/app/keyword.service.ts
import {HttpClient, HttpParams} from '@angular/common/http';
import {Injectable} from '@angular/core';
import {Observable} from 'rxjs';
export interface Keyword {
  id: number;
  name: string;
  path: string;
}
@Injectable({providedIn: 'root'})
export class KeywordService {
  constructor(private http: HttpClient) {}
  getKeywords(
    search: string,
    limit: number = 100,
    offset: number = 0,
  ): Observable<Keyword[]> {
    const params = new HttpParams()
      .set('search', search)
      .set('limit', limit.toString())
      .set('offset', offset.toString());
    return this.http.get<Keyword[]>('/api/keywords', {params});
  }
}
// src/app/keyword-list/keyword-list.component.ts
import {Component} from '@angular/core';
import {Observable} from 'rxjs';
import {Keyword, KeywordService} from '../keyword.service';
@Component({
  selector: 'app-keyword-list',
  template: `
    <div>
      <input
        [(ngModel)]="searchQuery"
        (input)="fetchKeywords()"
        placeholder="Search keywords..."
      />
      <ul>
        <li *ngFor="let keyword of keywords$ | async">{{ keyword.name }}</li>
      </ul>
    </div>
  `,
})
export class KeywordListComponent {
  searchQuery: string = '';
  keywords$!: Observable<Keyword[]>;
  constructor(private keywordService: KeywordService) {}
  fetchKeywords(): void {
    this.keywords$ = this.keywordService.getKeywords(this.searchQuery);
  }
}
  • By using Angular’s HttpClient and RxJS observables, the KeywordListComponent asynchronously fetches and displays keywords based on user input, ensuring a responsive user interface.
  • Utilizing Web Workers for Data Processing: To handle the processing of large keyword datasets without blocking the main thread, the team implemented Web Workers.

Create a Web Worker

  • Generate a web worker using Angular CLI:
ng generate web-worker keywordProcessor
  • This command creates a keyword-processor.worker.ts file.
// src/app/keyword-processor.worker.ts
/// <reference lib="webworker" />
addEventListener('message', ({data}) => {
  const keywords = data as Keyword[];
  const processedKeywords = keywords.map(keyword => ({
    ...keyword,
    processedName: keyword.name.toUpperCase(),
  }));
  postMessage(processedKeywords);
});

Integrate the Web Worker in the Component

// src/app/keyword-list/keyword-list.component.ts
import {Component, OnDestroy} from '@angular/core';
import {Keyword, KeywordService} from '../keyword.service';
@Component({
  selector: 'app-keyword-list',
  template: `
    <div>
      <input
        [(ngModel)]="searchQuery"
        (input)="fetchAndProcessKeywords()"
        placeholder="Search keywords..."
      />
      <ul>
        <li *ngFor="let keyword of processedKeywords">
          {{ keyword.processedName }}
        </li>
      </ul>
    </div>
  `,
})
export class KeywordListComponent implements OnDestroy {
  searchQuery: string = '';
  keywords: Keyword[] = [];
  processedKeywords: Keyword[] = [];
  worker: Worker | undefined;
  constructor(private keywordService: KeywordService) {
    if (typeof Worker !== 'undefined') {
      this.worker = new Worker(
        new URL('./keyword-processor.worker', import.meta.url),
      );
      this.worker.onmessage = ({data}) => {
        this.processedKeywords = data as Keyword[];
      };
    } else {
      console.error('Web Workers are not supported in this environment.');
    }
  }
  fetchAndProcessKeywords(): void {
    this.keywordService.getKeywords(this.searchQuery).subscribe(
      data => {
        this.keywords = data;
        if (this.worker) {
          this.worker.postMessage(this.keywords);
        }
      },
      error => {
        console.error('Error fetching keywords:', error);
      },
    );
  }
  ngOnDestroy(): void {
    if (this.worker) {
      this.worker.terminate();
    }
  }
}
  • In this example, the KeywordListComponent sends the fetched keywords to a Web Worker for processing. The worker converts each keyword's name to uppercase, and the processed keywords are then displayed in the UI. This offloads the processing to a background thread, ensuring that the main thread remains responsive.

Using Modern JavaScript Techniques in Angular for Faster Rendering and Data Processing

Modern JavaScript frameworks like Angular provide features that enhance frontend performance through efficient rendering and state management. Leveraging these features can lead to significant improvements in application responsiveness and user experience.

Change Detection Optimization

Angular’s change detection mechanism can be optimized to reduce unnecessary checks and re-renders, enhancing performance.

Example: Using OnPush Change Detection Strategy

// src/app/keyword-list/keyword-list.component.ts
import { Component, ChangeDetectionStrategy } from '@angular/core';
import { KeywordService, Keyword } from '../keyword.service';
import { Observable } from 'rxjs';

@Component({
  selector: 'app-keyword-list',
  template: `
    <div>
      <input [(ngModel)]="searchQuery" (input)="fetchKeywords()" placeholder="Search keywords..." />
      <ul>
        <li *ngFor="let keyword of keywords$ | async">{{ keyword.name }}</li>
      </ul>
    </div>
  `,
  changeDetection: ChangeDetectionStrategy.OnPush,
})
export class KeywordListComponent {
  searchQuery: string = '';
  keywords$!: Observable<Keyword[]>;
  constructor(private keywordService: KeywordService) {}
  fetchKeywords(): void {
    this.keywords$ = this.keywordService.getKeywords(this.searchQuery);
  }
}

By setting the ChangeDetectionStrategy to OnPush, Angular only checks for changes when the component's inputs change, reducing the number of change detection cycles and improving rendering performance.

Virtual Scrolling for Large Lists

Displaying large lists can lead to performance issues due to the rendering of numerous DOM elements. Angular’s cdk-virtual-scroll-viewport provides an efficient way to handle large datasets by rendering only the visible items.

Example: Implementing Virtual Scrolling in Angular

Install Angular CDK

npm install @angular/cdk

Update the Component Template

<!-- src/app/keyword-list/keyword-list.component.html -->
<div>
  <input [(ngModel)]="searchQuery" (input)="fetchAndProcessKeywords()" placeholder="Search keywords..." />
  <cdk-virtual-scroll-viewport itemSize="50" class="viewport">
    <ul>
      <li *cdkVirtualFor="let keyword of processedKeywords">{{ keyword.processedName }}</li>
    </ul>
  </cdk-virtual-scroll-viewport>
</div>

Add Styles for the Viewport

/* src/app/keyword-list/keyword-list.component.css */
.viewport {
  height: 400px;
  width: 100%;
  border: 1px solid #ccc;
}

Ensure Module Imports

// src/app/app.module.ts
import { NgModule } from '@angular/core';
import { BrowserModule } from '@angular/platform-browser';
import { ScrollingModule } from '@angular/cdk/scrolling';
import { FormsModule } from '@angular/forms';
import { HttpClientModule } from '@angular/common/http';

import { AppComponent } from './app.component';
import { KeywordListComponent } from './keyword-list/keyword-list.component';
@NgModule({
  declarations: [AppComponent, KeywordListComponent],
  imports: [BrowserModule, FormsModule, HttpClientModule, ScrollingModule],
  providers: [],
  bootstrap: [AppComponent],
})
export class AppModule {}

By implementing virtual scrolling, only the items visible within the viewport are rendered, significantly improving performance when dealing with large lists.

Lazy Loading Modules

Lazy loading Angular modules ensures that feature modules are loaded only when needed, reducing the initial load time of the application.

Example: Implementing Lazy Loading in Angular

Define a Feature Module

// src/app/keywords/keywords.module.ts
import { NgModule } from '@angular/core';
import { CommonModule } from '@angular/common';
import { KeywordListComponent } from './keyword-list/keyword-list.component';
import { RouterModule, Routes } from '@angular/router';
import { ScrollingModule } from '@angular/cdk/scrolling';
import { FormsModule } from '@angular/forms';

const routes: Routes = [
  {
    path: '',
    component: KeywordListComponent,
  },
];
@NgModule({
  declarations: [KeywordListComponent],
  imports: [CommonModule, FormsModule, ScrollingModule, RouterModule.forChild(routes)],
})
export class KeywordsModule {}

Configure Lazy Loading in the App Routing Module

// src/app/app-routing.module.ts
import { NgModule } from '@angular/core';
import { RouterModule, Routes } from '@angular/router';

const routes: Routes = [
  {
    path: 'keywords',
    loadChildren: () => import('./keywords/keywords.module').then((m) => m.KeywordsModule),
  },
  { path: '', redirectTo: '/keywords', pathMatch: 'full' },
  { path: '**', redirectTo: '/keywords' },
];
@NgModule({
  imports: [RouterModule.forRoot(routes, { preloadingStrategy: NoPreloading })],
  exports: [RouterModule],
})
export class AppRoutingModule {}

By lazy loading the KeywordsModule, the application loads the module only when the user navigates to the /keywords route, reducing the initial bundle size and improving load times.

Conclusion

Enhancing API efficiency and optimizing the Angular frontend are pivotal for delivering high-performance web applications that meet the demands of modern users. By designing responsive APIs with effective pagination and asynchronous processing, developers can handle large datasets efficiently, ensuring swift and reliable data retrieval. On the frontend, implementing asynchronous operations and leveraging Web Workers maintain a responsive user interface, even during intensive data processing tasks. Additionally, utilizing modern Angular features like change detection optimization, virtual scrolling, and lazy loading further accelerates rendering and data handling, providing a seamless and engaging user experience.

Through detailed strategies and practical code examples using Node.js, LoopBack 4, and Angular, this blog has equipped you with the tools and knowledge necessary to optimize both your backend APIs and frontend operations. As demonstrated in our case study, these optimizations lead to significant improvements in response times, resource utilization, and overall user satisfaction.

Stay tuned for our next blog in this series, “Caching and Scalability Solutions,” where we will discuss implementing Redis caching and scaling applications using a microservices architecture. These advanced strategies will further enhance your application’s performance and scalability, ensuring it can grow and adapt to increasing demands without compromising on efficiency.

By following this series, you will gain a comprehensive understanding of performance optimization, empowering you to build robust, scalable, and high-performing web applications that excel in today’s competitive digital landscape.

Web Perf
Angular
Loopback4
Programming

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Saurav Bhargava
Saurav Bhargava

Written by Saurav Bhargava

14 Followers
11 Following

Tech Architect with 15+ years in Web Architecture. 🚀 Passionate about tech innovations. Sharing insights & tales from the tech world.

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