Performance Optimization

Optimize your API for maximum performance and scalability.

Learn advanced techniques to improve your API's response times, throughput, and resource efficiency.

🎯 What You'll Learn

• ✅ Performance monitoring and analysis
• ✅ Database optimization techniques
• ✅ Caching strategies
• ✅ Load balancing and scaling
• ✅ Code optimization
• ✅ Infrastructure optimization

📹 Performance Overview

🎥 API Performance Fundamentals

Replace this placeholder with your performance overview video

Understand the key factors that affect API performance and how to measure and optimize them.

📊 Performance Metrics

Key Performance Indicators (KPIs)

Response Time Metrics

• Average Response Time: Mean time for API responses
• 95th Percentile: 95% of requests complete within this time
• 99th Percentile: 99% of requests complete within this time
• Maximum Response Time: Slowest request in the measurement period

Throughput Metrics

• Requests Per Second (RPS): Number of requests handled per second
• Concurrent Users: Number of simultaneous active users
• Peak Load: Maximum traffic during high-usage periods
• Sustained Load: Consistent traffic over extended periods

Resource Utilization

• CPU Usage: Processor utilization percentage
• Memory Usage: RAM consumption and garbage collection
• Database Connections: Active database connections
• Network I/O: Network bandwidth utilization

📹 Performance Monitoring

🎥 Setting Up Performance Monitoring

Replace this placeholder with your performance monitoring demonstration

Learn how to set up comprehensive performance monitoring for your API.

🚀 Database Optimization

Query Optimization

Index Strategy

-- Primary indexes (automatically created)
CREATE INDEX idx_users_id ON users(id);

-- Foreign key indexes
CREATE INDEX idx_posts_user_id ON posts(user_id);
CREATE INDEX idx_comments_post_id ON comments(post_id);

-- Search indexes
CREATE INDEX idx_users_email ON users(email);
CREATE INDEX idx_posts_title ON posts(title);

-- Composite indexes for complex queries
CREATE INDEX idx_posts_user_status ON posts(user_id, status);
CREATE INDEX idx_orders_date_status ON orders(created_at, status);

Query Analysis

-- Analyze query performance
EXPLAIN ANALYZE SELECT * FROM users WHERE email = 'user@example.com';

-- Identify slow queries
SELECT query, mean_time, calls
FROM pg_stat_statements
ORDER BY mean_time DESC
LIMIT 10;

Database Connection Optimization

Connection Pooling

// PostgreSQL connection pooling
const { Pool } = require("pg");

const pool = new Pool({
  user: "your_user",
  host: "localhost",
  database: "your_database",
  password: "your_password",
  port: 5432,
  max: 20, // Maximum number of connections
  idleTimeoutMillis: 30000,
  connectionTimeoutMillis: 2000,
});

Query Optimization

// Use prepared statements
const getUserById = async (id) => {
  const query = "SELECT * FROM users WHERE id = $1";
  const result = await pool.query(query, [id]);
  return result.rows[0];
};

// Batch operations
const createMultipleUsers = async (users) => {
  const query = "INSERT INTO users (name, email) VALUES ($1, $2)";
  const values = users.map((user) => [user.name, user.email]);
  await pool.query(query, values);
};

📹 Database Optimization

🎥 Optimizing Database Performance

Replace this placeholder with your database optimization demonstration

Learn advanced techniques for optimizing database queries and connections.

🚀 Caching Strategies

Application-Level Caching

In-Memory Caching

// Simple in-memory cache
const cache = new Map();

const getCachedUser = async (userId) => {
  const cacheKey = `user:${userId}`;

  if (cache.has(cacheKey)) {
    return cache.get(cacheKey);
  }

  const user = await db.users.findById(userId);
  cache.set(cacheKey, user);

  // Set expiration (5 minutes)
  setTimeout(() => cache.delete(cacheKey), 5 * 60 * 1000);

  return user;
};

Redis Caching

const redis = require("redis");
const client = redis.createClient();

const getCachedData = async (key) => {
  const cached = await client.get(key);
  if (cached) return JSON.parse(cached);

  const data = await fetchDataFromDatabase();
  await client.setex(key, 3600, JSON.stringify(data)); // 1 hour
  return data;
};

HTTP Caching

Response Headers

// Set cache headers
app.get("/api/users", (req, res) => {
  res.set({
    "Cache-Control": "public, max-age=300", // 5 minutes
    ETag: generateETag(data),
    "Last-Modified": new Date().toUTCString(),
  });

  res.json(users);
});

CDN Integration

// CDN-friendly caching
app.get("/api/static/:id", (req, res) => {
  res.set({
    "Cache-Control": "public, max-age=31536000", // 1 year
    ETag: generateETag(staticData),
  });

  res.json(staticData);
});

📹 Caching Implementation

🎥 Implementing Caching Strategies

Replace this placeholder with your caching implementation demonstration

Learn how to implement various caching strategies to improve API performance.

🚀 Code Optimization

JavaScript/Node.js Optimization

Async/Await Best Practices

// Good: Parallel execution
const [users, posts, comments] = await Promise.all([
  db.users.findAll(),
  db.posts.findAll(),
  db.comments.findAll(),
]);

// Bad: Sequential execution
const users = await db.users.findAll();
const posts = await db.posts.findAll();
const comments = await db.comments.findAll();

Memory Management

// Efficient data processing
const processLargeDataset = (data) => {
  // Use streams for large datasets
  const stream = require("stream");
  const transform = new stream.Transform({
    objectMode: true,
    transform(chunk, encoding, callback) {
      // Process chunk
      const processed = processChunk(chunk);
      callback(null, processed);
    },
  });

  return data.pipe(transform);
};

API Response Optimization

Response Compression

const compression = require("compression");
app.use(compression());

// Custom compression for specific routes
app.get("/api/large-data", compression(), (req, res) => {
  res.json(largeDataset);
});

Pagination Optimization

// Efficient pagination
const getPaginatedUsers = async (page = 1, limit = 10) => {
  const offset = (page - 1) * limit;

  const [users, total] = await Promise.all([
    db.users.findAll({
      limit,
      offset,
      order: [["created_at", "DESC"]],
    }),
    db.users.count(),
  ]);

  return {
    data: users,
    pagination: {
      page,
      limit,
      total,
      pages: Math.ceil(total / limit),
    },
  };
};

📹 Code Optimization

🎥 Optimizing API Code

Replace this placeholder with your code optimization demonstration

Learn how to optimize your API code for better performance and efficiency.

🚀 Infrastructure Optimization

Load Balancing

Application Load Balancing

# Nginx load balancer configuration
upstream api_backend {
    server api1.example.com:3000;
    server api2.example.com:3000;
    server api3.example.com:3000;
}

server {
    listen 80;
    location /api/ {
        proxy_pass http://api_backend;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
    }
}

Database Load Balancing

// Read/write splitting
const readDB = new Pool({
  host: "read-replica.example.com",
  // ... other config
});

const writeDB = new Pool({
  host: "master.example.com",
  // ... other config
});

// Route reads to replica, writes to master
const getUsers = () => readDB.query("SELECT * FROM users");
const createUser = (user) => writeDB.query("INSERT INTO users ...", [user]);

Auto-scaling Configuration

Horizontal Pod Autoscaler (Kubernetes)

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: api-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: api-deployment
  minReplicas: 2
  maxReplicas: 10
  metrics:
    - type: Resource
      resource:
        name: cpu
        target:
          type: Utilization
          averageUtilization: 70

📹 Infrastructure Scaling

🎥 Scaling API Infrastructure

Replace this placeholder with your infrastructure scaling demonstration

Learn how to scale your API infrastructure to handle increased load and traffic.

🚀 Performance Testing

Load Testing

Load Testing Tools

# Using Apache Bench
ab -n 1000 -c 10 http://localhost:3000/api/users

# Using Artillery
artillery quick --count 100 --num 10 http://localhost:3000/api/users

# Using k6
k6 run --vus 10 --duration 30s load-test.js

Load Testing Script (k6)

import http from "k6/http";
import { check } from "k6";

export let options = {
  stages: [
    { duration: "2m", target: 100 }, // Ramp up
    { duration: "5m", target: 100 }, // Stay at 100 users
    { duration: "2m", target: 200 }, // Ramp up to 200 users
    { duration: "5m", target: 200 }, // Stay at 200 users
    { duration: "2m", target: 0 }, // Ramp down
  ],
};

export default function () {
  let response = http.get("http://localhost:3000/api/users");
  check(response, {
    "status is 200": (r) => r.status === 200,
    "response time < 500ms": (r) => r.timings.duration < 500,
  });
}

Performance Profiling

Node.js Profiling

// CPU profiling
const profiler = require("v8-profiler-node8");

// Start profiling
profiler.startProfiling("api-profile");

// Stop profiling after some time
setTimeout(() => {
  const profile = profiler.stopProfiling("api-profile");
  profile
    .export()
    .pipe(fs.createWriteStream("profile.cpuprofile"))
    .on("finish", () => profile.delete());
}, 30000);

📹 Performance Testing

🎥 Testing API Performance

Replace this placeholder with your performance testing demonstration

Learn how to conduct comprehensive performance testing to identify bottlenecks and optimize your API.

🎯 Performance Best Practices

General Optimization

Measure Before Optimizing

Always measure performance before and after optimizations

Optimize the Critical Path

Focus on the most frequently used code paths

Use Appropriate Data Structures

Choose the right data structure for your use case

Implement Caching Strategically

Cache at the right level for maximum benefit

Database Optimization

Index Frequently Queried Columns

Add indexes to columns used in WHERE clauses

Use Connection Pooling

Optimize database connections for better performance

Optimize Queries

Use EXPLAIN ANALYZE to identify slow queries

Consider Read Replicas

Use read replicas for read-heavy workloads

Infrastructure Optimization

Use Load Balancers

Distribute traffic across multiple instances

Implement Auto-scaling

Automatically scale based on demand

Use CDNs

Cache static content closer to users

Monitor Everything

Set up comprehensive monitoring and alerting

🚀 Next Steps

Your API is Optimized!

After implementing performance optimizations:

1. Monitor Performance: Track improvements and identify new bottlenecks
2. Regular Testing: Conduct periodic performance tests
3. Continuous Optimization: Keep optimizing based on usage patterns
4. Scale as Needed: Plan for future growth and scaling

Learn More

• Deployment Guide →
• Monitoring Guide →
• Security Best Practices →

Advanced Topics

• Microservices Performance →
• Database Sharding →
• Advanced Caching →

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Ready to monitor your optimized API? Learn about monitoring → 🚀