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Performance Standards

This document outlines the performance standards and optimization guidelines that all Bayat projects must adhere to.

Performance Targets

Web Applications

Metric Target Value Measurement Tool
First Contentful Paint < 1.8s Lighthouse, WebPageTest
Time to Interactive < 3.8s Lighthouse
Speed Index < 3.4s Lighthouse, WebPageTest
Total Blocking Time < 300ms Lighthouse
Largest Contentful Paint < 2.5s Lighthouse, Chrome UX
Cumulative Layout Shift < 0.1 Lighthouse, Chrome UX
First Input Delay < 100ms Chrome UX Report
Page Weight < 1.5MB total, < 500KB critical WebPageTest
HTTP Requests < 50 initial page load WebPageTest
Server Response Time < 200ms Lighthouse, AppDynamics

Mobile Applications

Metric Target Value Measurement Tool
App Start Time (Cold) < 2s Custom instrumentation
App Start Time (Warm) < 1s Custom instrumentation
App Size < 50MB for Android, < 100MB for iOS App stores
Frame Rate 60 FPS for animations Device profiler
UI Response Time < 100ms Custom instrumentation
Network Request Time < 1s for critical requests Network monitoring
Memory Usage < 200MB Device profiler
Battery Impact < 5% drain per hour of active use Battery monitoring

Backend Systems

Metric Target Value Measurement Tool
API Response Time (p95) < 300ms API Gateway, AppDynamics
API Response Time (p99) < 1s API Gateway, AppDynamics
Database Query Time (p95) < 100ms Database monitoring
Concurrent Users Specific to each application Load testing tools
Request Throughput Specific to each application Load testing tools
Error Rate < 0.1% Application monitoring
CPU Utilization < 70% average Infrastructure monitoring
Memory Utilization < 80% average Infrastructure monitoring

Frontend Performance Practices

JavaScript/TypeScript

  • Use code splitting and lazy loading for routes
  • Minimize third-party JavaScript
  • Implement tree shaking for unused code elimination
  • Avoid render-blocking JavaScript
  • Optimize event listeners and debounce where appropriate
  • Use Web Workers for CPU-intensive tasks
  • Implement virtual scrolling for long lists
  • Use requestAnimationFrame for animations
  • Minimize DOM updates and batch when possible

CSS

  • Use CSS containment where appropriate
  • Minimize unused CSS
  • Avoid expensive CSS selectors
  • Optimize CSS animations using transform and opacity
  • Use media queries to load appropriate assets
  • Implement critical CSS inline
  • Minimize render-blocking CSS

Assets

  • Implement responsive images with srcset and sizes
  • Use WebP/AVIF formats with appropriate fallbacks
  • Compress all images appropriately
  • Implement lazy loading for images and iframes
  • Preload critical assets
  • Use SVG for icons and simple graphics
  • Implement font-display: swap for web fonts
  • Use font subsetting

Backend Performance Practices

API Design

  • Implement caching headers (ETags, Cache-Control)
  • Support pagination for large data sets
  • Implement GraphQL for flexible data fetching
  • Use field selection to minimize response size
  • Implement data compression (gzip, Brotli)
  • Design batched endpoints for multiple operations

Database

  • Optimize database queries with proper indexing
  • Implement database query caching
  • Use connection pooling
  • Implement database sharding for large datasets
  • Use NoSQL databases for appropriate use cases
  • Implement database denormalization where appropriate
  • Use ORM optimization techniques

Caching

  • Implement multi-level caching strategy
  • Use Redis/Memcached for shared caching
  • Implement CDN caching for static assets
  • Use service worker caching for web applications
  • Implement cache invalidation strategies

Mobile-specific Practices

  • Implement app size optimization techniques
  • Use binary data formats (Protocol Buffers, FlatBuffers)
  • Optimize startup time with lazy initialization
  • Implement efficient image loading and caching
  • Use appropriate view recycling patterns
  • Optimize battery usage with background processing limits
  • Implement offline capabilities

Testing and Monitoring

Performance Testing Types

  • Load testing (steady load)
  • Stress testing (beyond normal capacity)
  • Spike testing (sudden increases)
  • Endurance testing (sustained period)
  • Scalability testing (increasing resources)
  • Component testing (isolated components)

Monitoring Requirements

  • Implement real user monitoring (RUM)
  • Set up synthetic monitoring for critical paths
  • Monitor backend performance metrics
  • Implement alerting for performance degradation
  • Use distributed tracing for request flow analysis
  • Perform regular performance audits

Implementation Process

  1. Requirements Phase: Define specific performance requirements
  2. Design Phase: Review design decisions for performance impact
  3. Development Phase: Implement performance best practices
  4. Testing Phase: Conduct performance testing
  5. Deployment Phase: Set up performance monitoring
  6. Operations Phase: Continuously monitor and optimize

Tools and Libraries

Web Performance Tools

  • Lighthouse
  • WebPageTest
  • Chrome DevTools Performance panel
  • Webpack Bundle Analyzer
  • Google PageSpeed Insights

Mobile Performance Tools

  • Android Profiler
  • Xcode Instruments
  • Firebase Performance Monitoring
  • Android Vitals
  • iOS App Analytics

Backend Performance Tools

  • JMeter/k6/Locust for load testing
  • AppDynamics/New Relic for APM
  • Prometheus/Grafana for monitoring
  • ELK Stack for log analysis
  • Datadog for comprehensive monitoring

Documentation Requirements

Every project must include:

  • Performance budgets and targets
  • Performance testing results
  • Known performance limitations
  • Performance optimization roadmap