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Performance Optimization Guide

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Performance Optimization

Comprehensive guide to system performance optimization techniques

11
Optimization Techniques
Database
high impactmedium complexity

Database Indexing

Create indexes to speed up query performance

Techniques:

  • B-tree indexes for range queries
  • Hash indexes for equality lookups
  • Composite indexes for multi-column queries

Benefits:

  • +Faster query execution
  • +Reduced I/O operations
  • +Better concurrent performance

Tradeoffs:

  • -Increased storage space
  • -Slower write operations
  • -Index maintenance overhead

Key Metrics:

Query execution timeIndex hit ratioDisk I/O reduction

Tools:

EXPLAIN PLANDatabase profilersQuery analyzers
Database
high impactmedium complexity

Query Optimization

Optimize SQL queries for better performance

Techniques:

  • Use appropriate WHERE clauses
  • Avoid SELECT * statements
  • Use JOINs instead of subqueries when possible

Benefits:

  • +Reduced query execution time
  • +Lower resource consumption
  • +Better scalability

Tradeoffs:

  • -More complex query writing
  • -Increased development time
  • -Need for query analysis expertise

Key Metrics:

Query response timeRows examined vs returnedCPU usage

Tools:

EXPLAINQuery profilersDatabase monitoring tools
Caching
high impactmedium complexity

Application-Level Caching

Cache frequently accessed data in application memory

Techniques:

  • In-memory caching (Redis, Memcached)
  • Application-level cache (local cache)
  • Cache-aside pattern

Benefits:

  • +Dramatically reduced latency
  • +Decreased database load
  • +Better user experience

Tradeoffs:

  • -Cache invalidation complexity
  • -Memory usage overhead
  • -Data consistency challenges

Key Metrics:

Cache hit ratioResponse time improvementMemory usage

Tools:

RedisMemcachedHazelcastCaffeine
Caching
high impactlow complexity

CDN Optimization

Use Content Delivery Networks for static content

Techniques:

  • Static asset caching
  • Geographic distribution
  • Edge caching

Benefits:

  • +Reduced latency globally
  • +Decreased origin server load
  • +Better availability

Tradeoffs:

  • -Additional service cost
  • -Cache invalidation delays
  • -Complexity in cache management

Key Metrics:

Global response timeCache hit ratioBandwidth savings

Tools:

CloudFlareAWS CloudFrontAzure CDNGoogle Cloud CDN
Code
high impacthigh complexity

Algorithm Optimization

Improve algorithmic efficiency and data structures

Techniques:

  • Choose optimal data structures
  • Reduce time complexity (Big O)
  • Minimize memory allocations

Benefits:

  • +Faster execution times
  • +Lower memory usage
  • +Better scalability

Tradeoffs:

  • -Increased development complexity
  • -Code readability challenges
  • -Longer development time

Key Metrics:

Execution timeMemory usageCPU utilization

Tools:

ProfilersBenchmarking toolsCode analyzers
Code
medium impactlow complexity

Lazy Loading

Load resources only when needed

Techniques:

  • Lazy initialization of objects
  • On-demand resource loading
  • Pagination for large datasets

Benefits:

  • +Faster initial load times
  • +Reduced memory usage
  • +Better user experience

Tradeoffs:

  • -Potential delays on first access
  • -Increased complexity
  • -Need for loading states

Key Metrics:

Initial load timeMemory usageUser engagement

Tools:

Intersection Observer APIReact.lazyDynamic imports
Network
medium impactlow complexity

Data Compression

Compress data to reduce transfer times

Techniques:

  • Gzip compression for text
  • Brotli compression for modern browsers
  • Image optimization and compression

Benefits:

  • +Reduced bandwidth usage
  • +Faster page load times
  • +Lower data transfer costs

Tradeoffs:

  • -CPU overhead for compression
  • -Increased server processing
  • -Complexity in setup

Key Metrics:

Transfer size reductionPage load timeBandwidth usage

Tools:

WebpackGzipImageOptimBrotli
Network
high impactmedium complexity

Connection Pooling

Reuse database and network connections

Techniques:

  • Database connection pooling
  • HTTP connection keep-alive
  • Connection pool sizing

Benefits:

  • +Reduced connection overhead
  • +Better resource utilization
  • +Improved throughput

Tradeoffs:

  • -Memory usage for idle connections
  • -Configuration complexity
  • -Connection leakage risks

Key Metrics:

Connection establishment timePool utilizationThroughput

Tools:

HikariCPpgbouncerConnection pool monitors
Infrastructure
high impactmedium complexity

Load Balancing

Distribute load across multiple servers

Techniques:

  • Round-robin load balancing
  • Weighted load balancing
  • Health check implementation

Benefits:

  • +Better resource utilization
  • +Improved availability
  • +Higher throughput

Tradeoffs:

  • -Additional infrastructure complexity
  • -Session management challenges
  • -Increased operational overhead

Key Metrics:

Request distributionResponse timeServer utilization

Tools:

NGINXHAProxyAWS ALBGoogle Cloud Load Balancer
Infrastructure
high impacthigh complexity

Horizontal Scaling

Add more servers to handle increased load

Techniques:

  • Auto-scaling groups
  • Microservices architecture
  • Stateless application design

Benefits:

  • +Better scalability
  • +Improved fault tolerance
  • +Cost-effective scaling

Tradeoffs:

  • -Increased complexity
  • -Data consistency challenges
  • -Network overhead

Key Metrics:

Throughput per instanceScaling response timeCost per request

Tools:

KubernetesDocker SwarmAWS Auto ScalingTerraform
Frontend
medium impactlow complexity

Asset Optimization

Optimize static assets for faster loading

Techniques:

  • Image optimization and modern formats
  • CSS and JavaScript minification
  • Bundle splitting and tree shaking

Benefits:

  • +Faster page load times
  • +Better user experience
  • +Improved SEO rankings

Tradeoffs:

  • -Build process complexity
  • -Development workflow changes
  • -Debugging challenges

Key Metrics:

First Contentful PaintLargest Contentful PaintBundle size

Tools:

WebpackParcelViteImageOptim

Optimization Impact Matrix

8
high Impact Techniques
3
medium Impact Techniques
0
low Impact Techniques

Optimization Strategy: Start with High Impact, Low Complexity techniques for quick wins. Then tackle High Impact, High Complexity optimizations for maximum benefit. Always measure before and after to validate improvements.