Optimization in high-concurrency scenarios

Challenges in High-Concurrency Scenarios

Koa2, as a lightweight Node.js framework, faces several core issues when handling high-concurrency requests: event loop blocking, memory leak risks, database connection pool exhaustion, and middleware execution efficiency. When QPS exceeds 5000, typical performance bottlenecks appear in the following areas:

1. Synchronous I/O operations blocking the event loop
2. Unoptimized asynchronous operations causing memory buildup
3. Context-passing overhead from middleware chaining
4. Failure to leverage multi-core CPU capabilities in cluster mode

// Example of problematic middleware
app.use(async (ctx, next) => {
  const start = Date.now()
  await next() // Potential performance bottleneck
  const ms = Date.now() - start
  console.log(`${ctx.method} ${ctx.url} - ${ms}ms`)
})

Event Loop Optimization Strategies

Avoid Synchronous Operations

All blocking operations must be asynchronous, especially file I/O and cryptographic computations. Use fs.promises instead of callback-style APIs, and offload crypto operations to worker threads:

const { promisify } = require('util')
const crypto = require('crypto')
const pbkdf2Async = promisify(crypto.pbkdf2)

app.use(async ctx => {
  // Bad practice: synchronous hash calculation
  // const hash = crypto.createHash('sha256').update('data').digest('hex')
  
  // Correct approach
  const hash = await pbkdf2Async('data', 'salt', 100000, 64, 'sha512')
  ctx.body = hash.toString('hex')
})

Event Loop Monitoring

Use the loopbench module to monitor event loop latency in real-time:

const loopBench = require('loopbench')
const loop = loopBench()

app.use(async (ctx, next) => {
  if (loop.delay > 100) {
    ctx.status = 503
    ctx.body = { error: 'Server Overload' }
    return
  }
  await next()
})

Memory Management Practices

Streamline Context

Avoid attaching large data to the ctx object. Use Symbol as private property keys:

const USER_DATA = Symbol('userData')

app.use(async (ctx, next) => {
  // Bad practice: attaching full user object
  // ctx.user = await User.find({ id: ctx.params.id })
  
  // Optimized approach
  ctx[USER_DATA] = { id: ctx.params.id }
  await next()
})

Stream Response Handling

Use streaming APIs for large file transfers to avoid Buffer memory buildup:

const fs = require('fs')
const { pipeline } = require('stream/promises')

app.use(async ctx => {
  ctx.set('Content-Type', 'application/octet-stream')
  const fileStream = fs.createReadStream('./large-file.zip')
  await pipeline(fileStream, ctx.res)
})

Database Connection Optimization

Connection Pool Configuration

Recommended configurations for different database types:

// Sequelize connection pool example
const sequelize = new Sequelize({
  dialect: 'mysql',
  pool: {
    max: 50,
    min: 5,
    acquire: 30000,
    idle: 10000
  }
})

Batch Operation Optimization

Use bulk inserts instead of looping single inserts:

// Inefficient approach
for (const item of dataList) {
  await Model.create(item)
}

// Optimized solution
await Model.bulkCreate(dataList, {
  updateOnDuplicate: ['updatedAt'],
  returning: true
})

Middleware Performance Tuning

Flatten Execution Chains

Merge similar middlewares and use bitwise operations for permission checks:

const PERMISSIONS = {
  READ: 1 << 0,
  WRITE: 1 << 1,
  ADMIN: 1 << 2
}

app.use(async (ctx, next) => {
  const userPerm = await getUserPermissions(ctx)
  if (!(userPerm & PERMISSIONS.READ)) {
    ctx.throw(403)
  }
  await next()
})

Cache Middleware Results

Add an in-memory cache layer for static content:

const LRU = require('lru-cache')
const cache = new LRU({ max: 500, ttl: 1000 * 60 })

app.use(async (ctx, next) => {
  const key = ctx.url
  if (cache.has(key)) {
    ctx.body = cache.get(key)
    return
  }
  await next()
  if (ctx.status === 200) {
    cache.set(key, ctx.body)
  }
})

Cluster Mode Best Practices

Optimize Inter-Process Communication

Use shared memory instead of IPC:

const { SharedArrayBuffer } = require('worker_threads')
const sab = new SharedArrayBuffer(1024)
const counter = new Int32Array(sab)

cluster.on('message', (worker, msg) => {
  Atomics.add(counter, 0, 1)
  if (Atomics.load(counter, 0) > 1000) {
    // Implement throttling
  }
})

Graceful Shutdown Mechanism

Process pending requests before terminating:

let connections = new Set()

server.on('connection', conn => {
  connections.add(conn)
  conn.on('close', () => connections.delete(conn))
})

process.on('SIGTERM', () => {
  server.close(() => process.exit(0))
  setTimeout(() => {
    connections.forEach(conn => conn.destroy())
  }, 5000)
})

Stress Testing and Monitoring

Distributed Tracing Integration

Use OpenTelemetry to collect cross-service performance data:

const { NodeTracerProvider } = require('@opentelemetry/sdk-trace-node')
const { Resource } = require('@opentelemetry/resources')
const provider = new NodeTracerProvider({
  resource: new Resource({
    'service.name': 'koa-api'
  })
})

app.use(async (ctx, next) => {
  const tracer = trace.getTracer('koa-tracer')
  const span = tracer.startSpan('request-handler')
  await next()
  span.end()
})

Circuit Breaker Strategy

Implement a Hystrix-style circuit breaker:

class CircuitBreaker {
  constructor(timeout = 3000, threshold = 0.5) {
    this.state = 'CLOSED'
    this.failureCount = 0
    this.timeout = timeout
  }

  async exec(fn) {
    if (this.state === 'OPEN') throw new Error('Service Unavailable')
    try {
      const result = await Promise.race([
        fn(),
        new Promise((_, reject) => 
          setTimeout(reject, this.timeout, 'Timeout')
        )
      ])
      this.reset()
      return result
    } catch (err) {
      this.failureCount++
      if (this.failureCount >= 5) this.state = 'OPEN'
      throw err
    }
  }
}