Performance Engineering with GenAI

AI-powered code optimization and performance analysis

Skills: Data Science & Site Reliability Engineering

⚡ AI Performance Analysis in Action

AI Analysis: Found performance bottleneck in OrderService.processPayment()
// Current implementation - 847ms average
for (Order order : orders) {
    PaymentResult result = paymentAPI.charge(order);
    database.save(result);
    emailService.sendConfirmation(order);
}
                
🤖 AI Recommendation: "This synchronous loop is your bottleneck. Let me optimize it..."
Optimized by AI:
// AI-optimized - 124ms average (85% improvement)
CompletableFuture[] futures = orders.stream()
    .map(order -> CompletableFuture
        .supplyAsync(() -> paymentAPI.charge(order))
        .thenCompose(result -> CompletableFuture.allOf(
            CompletableFuture.runAsync(() -> database.save(result)),
            CompletableFuture.runAsync(() -> emailService.sendConfirmation(order))
        )))
    .toArray(CompletableFuture[]::new);

CompletableFuture.allOf(futures).join();
                
85%
Faster
124ms
Response Time
10x
Throughput

🎯 GenAI Performance Features

Code Analysis

AI reviews every PR for performance issues before merge

Load Test Generation

Creates realistic traffic patterns from production data

Auto-Optimization

Suggests and implements performance improvements

Resource Tuning

Optimizes JVM, database, and container settings

"Reduced P99 latency by 73% across 200+ microservices using AI-driven optimization"