telegram-management-system/marketing-agent/frontend/PERFORMANCE_OPTIMIZATION.md

Frontend Performance Optimization Guide

This guide documents all performance optimizations implemented in the Telegram Marketing Agent frontend.

Overview

The frontend has been optimized for performance across multiple dimensions:

• Initial load time
• Runtime performance
• Memory usage
• Network efficiency
• User experience

Build Optimizations

1. Code Splitting

• Automatic vendor chunks for better caching
• Manual chunks for large libraries (Element Plus, Chart.js)
• Route-based code splitting with lazy loading

2. Compression

• Gzip compression for all assets > 10KB
• Brotli compression for better compression ratios
• Image optimization with quality settings

3. Asset Optimization

• Proper asset naming for cache busting
• Inline small assets (< 4KB)
• Organized asset directories

Runtime Optimizations

1. Lazy Loading

• Images: Intersection Observer-based lazy loading
• Components: Dynamic imports with loading/error states
• Routes: Lazy-loaded route components

<!-- Image lazy loading -->
<img v-lazy="imageSrc" :alt="imageAlt">

<!-- Background lazy loading -->
<div v-lazy-bg="backgroundUrl"></div>

<!-- Progressive image loading -->
<img v-progressive="{ lowQuality: thumbUrl, highQuality: fullUrl }">

2. Virtual Scrolling

For large lists, use the VirtualList component:

<VirtualList 
  :items="items" 
  :item-height="50"
  v-slot="{ item }"
>
  <div>{{ item.name }}</div>
</VirtualList>

3. Web Workers

Heavy computations are offloaded to web workers:

import { useComputationWorker } from '@/composables/useWebWorker'

const { sort, filter, aggregate, loading, result } = useComputationWorker()

// Sort large dataset
await sort(largeArray)

// Filter data
await filter(items, 'status', 'active')

4. Debouncing & Throttling

import { debounce, throttle } from '@/utils/performance'

// Debounce search input
const search = debounce((query) => {
  // Search logic
}, 300)

// Throttle scroll handler
const handleScroll = throttle(() => {
  // Scroll logic
}, 100)

State Management

1. Persisted State

Store state is automatically persisted with debouncing:

// In store configuration
export const useUserStore = defineStore('user', {
  persist: {
    paths: ['profile', 'preferences'],
    debounceTime: 1000
  }
})

2. Memory Management

• WeakMap for object references
• Automatic cleanup on component unmount
• Memory leak detection in development

Network Optimizations

1. Service Worker

• Offline support with cache strategies
• Background sync for failed requests
• Push notifications support

2. API Caching

• Cache-first for static data
• Network-first with cache fallback for dynamic data
• Stale-while-revalidate for frequently updated data

3. Request Optimization

• Request batching for multiple API calls
• Request deduplication
• Automatic retry with exponential backoff

Monitoring & Analytics

1. Performance Metrics

The app automatically tracks:

• First Contentful Paint (FCP)
• Largest Contentful Paint (LCP)
• First Input Delay (FID)
• Cumulative Layout Shift (CLS)
• Time to Interactive (TTI)

2. Error Tracking

• Global error handler
• Source maps for production debugging
• User context in error reports

3. User Analytics

• Page view tracking
• User interaction events
• Performance impact analysis

Best Practices

1. Component Development

• Use shallowRef for large objects
• Implement v-memo for expensive renders
• Use computed instead of methods for derived state

2. Event Handling

• Use passive event listeners
• Delegate events when possible
• Clean up listeners on unmount

3. Asset Loading

• Preload critical resources
• Use resource hints (prefetch, preconnect)
• Implement responsive images

4. Bundle Size

• Tree-shake unused code
• Use dynamic imports for optional features
• Monitor bundle size with visualizer

Development Tools

1. Performance Profiling

# Generate bundle analysis
npm run build -- --report

# Profile runtime performance
window.__PERFORMANCE__.getMetrics()

2. Lighthouse CI

Run Lighthouse in CI to track performance over time:

npm run lighthouse

3. Memory Profiling

Use Chrome DevTools Memory Profiler to identify leaks.

Configuration Files

vite.config.optimized.js

Contains all build optimizations including:

• Code splitting configuration
• Compression plugins
• Asset optimization
• Performance hints

Performance Budget

Target metrics:

• FCP: < 1.8s
• LCP: < 2.5s
• TTI: < 3.8s
• Bundle size: < 500KB (initial)

Checklist

Before deploying, ensure:

• Images are optimized and lazy-loaded
• Large lists use virtual scrolling
• Heavy computations use web workers
• API calls are cached appropriately
• Service worker is registered (production)
• Performance metrics are within budget
• No memory leaks detected
• Bundle size is optimized

Troubleshooting

High Memory Usage

1. Check for detached DOM nodes
2. Review event listener cleanup
3. Verify store subscription cleanup

Slow Initial Load

1. Review bundle splitting
2. Check for blocking resources
3. Verify compression is working

Poor Runtime Performance

1. Profile with Chrome DevTools
2. Check for unnecessary re-renders
3. Review computed property usage

Future Optimizations

1. HTTP/3 Support: When available
2. Module Federation: For micro-frontends
3. Edge Computing: For global performance
4. AI-Powered Prefetching: Predictive resource loading