What is Performance Optimisation?

Performance optimisation is the discipline of improving application speed and responsiveness. Effective optimisation identifies genuine performance bottlenecks and addresses them with changes delivering measurable improvement. Premature optimisation of non-critical code wastes effort and introduces unnecessary complexity.

Performance Metrics

Response Time

Time from user action to visible response. Slower response times create perception of sluggishness. Response times below 100 milliseconds feel instantaneous. Response times above one second feel unresponsive.

Throughput

How many requests a system can process per second. Higher throughput enables systems to handle more concurrent users.

CPU Utilisation

Percentage of available CPU time the application uses. Low utilisation on powerful hardware suggests inefficiency.

Memory Usage

Application memory consumption. Excessive memory usage causes slowdowns and crashes on memory-constrained devices.

Database Query Time

Time required to retrieve data. Database operations frequently dominate application performance.

Performance Profiling

Measurement Tools

Profiling tools measure application performance:

  • APM tools - Application performance monitoring provides end-to-end visibility
  • Browser dev tools - Chrome and Firefox provide performance analysis
  • Profilers - Programming language profilers measure CPU and memory usage
  • Load testing - Simulated traffic reveals performance under load

Identifying Bottlenecks

Profiling identifies where time is spent:

  • Database queries consuming excessive time
  • Algorithms with poor algorithmic complexity
  • Memory leaks causing garbage collection pauses
  • Network requests blocking user interaction

Data-Driven Optimisation

Optimisation should target genuine bottlenecks, not assumptions. Profiling reveals actual performance characteristics.

Common Performance Issues and Solutions

N+1 Queries

Loading a list of items with individual database queries for each item:

// Poor: N database queries
users.forEach(user => {
user.orders = fetchOrders(user.id);
});
// Good: Single query
const orders = fetchAllOrdersBatch(userIds);
users.forEach(user => {
user.orders = orders[user.id];
});

Unoptimised Algorithms

Algorithms with poor time complexity:

// O(n²) - slow for large datasets
function findDuplicates(items) {
const duplicates = [];
for (let i = 0; i < items.length; i++) {
for (let j = i + 1; j < items.length; j++) {
if (items[i] === items[j]) duplicates.push(items[i]);
}
}
return duplicates;
}
// O(n) - linear time
function findDuplicates(items) {
const seen = new Set();
const duplicates = [];
items.forEach(item => {
if (seen.has(item)) duplicates.push(item);
else seen.add(item);
});
return duplicates;
}

Uncompressed Assets

Large images, CSS, and JavaScript files slow page loads:

  • Image optimisation - Reduce file sizes through compression
  • CSS minification - Remove whitespace and comments
  • JavaScript minification - Reduce file size through compression
  • Gzip compression - Server-side compression reduces transmission size

Inefficient Rendering

DOM manipulation triggering unnecessary reflows:

// Triggers reflow for each element
elements.forEach(element => {
element.style.width = '100px';
});
// Batches style changes
elements.forEach(element => {
element.classList.add('new-width');
});

Blocking Requests

Synchronous requests blocking user interaction:

  • Use asynchronous requests preventing UI blocking
  • Implement request debouncing preventing excessive requests
  • Cache results reducing repeated requests

Performance Optimisation at PixelForce

PixelForce prioritises application performance. We profile applications to identify genuine bottlenecks and implement targeted optimisations. Our focus is on delivering responsive, fast applications.

Web Performance Optimisation

Frontend Performance

  • Lazy loading - Load images and content only when needed
  • Code splitting - Separate JavaScript into smaller chunks
  • Caching - Cache assets preventing repeated downloads
  • CDN distribution - Serve content from geographically close locations

Backend Performance

  • Database indexing - Improve query performance through indexing
  • Query optimisation - Rewrite slow queries for better performance
  • Caching - Cache frequently accessed data reducing database load
  • Asynchronous processing - Move slow operations to background jobs

Infrastructure Performance

  • Load balancing - Distribute traffic across multiple servers
  • Database replication - Distribute read load across replicas
  • Vertical scaling - More powerful servers
  • Horizontal scaling - More servers handling traffic together

Performance Regression Prevention

Performance degrades gradually through accumulated changes. Preventing regression:

  • Automated performance testing - Detect performance regressions
  • Performance budgets - Set limits on acceptable performance degradation
  • Continuous monitoring - Track performance over time
  • Review discipline - Code review focuses on performance impact

PixelForce Performance Standards

PixelForce maintains performance standards:

  • Page load times under 3 seconds
  • Response times under 200 milliseconds
  • Zero perceived lag in user interactions
  • Smooth 60 frames per second animations

Performance optimisation represents an ongoing commitment to user experience excellence. Fast applications delight users and drive adoption.