Better Concurrency in JavaScript with Asyncify

Managing Concurrent Tasks in NodeJS API Requests

When handling API requests in a shared NodeJS environment, or when processing a large number of “Ajax” requests in a browser, it’s crucial to implement proper concurrency control to prevent resource exhaustion and maintain optimal performance.

Without proper concurrency limits, it’s possible to spawn numerous Promise-based tasks, leading to:

• Memory overflow
• CPU saturation
• Degraded response times for other users
• Potential server crashes under heavy load

Solution: Using Asyncify

Asyncify provides a clean approach to managing concurrent tasks through:

import { Asyncify } from 'asyncify-wasm';

const concurrencyLimit = 5; // Adjust based on server capacity
const asyncify = new Asyncify({
  maxConcurrent: concurrencyLimit
});
async function handleAPIRequest(req, res) {
  try {
    const tasks = generateTasks(); // Your task generation logic
    
    // Process tasks with concurrency limit
    const results = await asyncify.all(tasks);
    
    res.json({ success: true, results });
  } catch (error) {
    res.status(500).json({ error: error.message });
  }
}

Here’s another example using mapLimit with asyncify:

import { mapLimit } from 'async';
import { asyncify } from 'async-utility';

async function processPatients(patientIds: string[]) {
  return await mapLimit(
    patientIds,
    5, // Concurrency limit of 5 parallel operations
    asyncify(async (patientId: string) => {
      // Process each patient
      const result = await performPatientOperation(patientId);
      return result;
    })
  );
}

This example demonstrates using mapLimit to process patient records with controlled concurrency, preventing server overload while handling multiple patient operations simultaneously.

Key Implementation Points

• Set appropriate concurrency limits based on server resources
• Handle task queue overflow scenarios
• Implement proper error handling and timeout mechanisms
• Monitor task execution metrics

Best Practices

When implementing concurrency control:

• Start with conservative limits and adjust based on monitoring
• Include timeout mechanisms for long-running tasks
• Implement proper error handling and recovery
• Add monitoring to track concurrent task metrics

By implementing these controls, you can ensure your NodeJS server remains stable and responsive even under heavy load conditions.