Writing Production-Ready Code in Node.js

Without beating around the bush, let’s jump in.

First, let's discuss the common industry standards yet efficient ways for writing production-ready code.

Building Code that Sings with Common Industry Standards: Crafting Efficiency in Every Line.

Logging :

Where Bugs Get a ‘Nametag’ and We Play Sherlock with Code.

Remembering the ABCs of writing code. Logging is the most used industry-wide technique, always uncovering what sent your server south! Not only NodeJS, but indeed any server-side language has full support of logging libraries.

• Utilize a logging library (e.g., Winston, Bunyan) to log application events and errors.
• Log meaningful information at different levels (info, debug, error) to assist in troubleshooting.

Example —

const winston = require('winston');

// Create a logger instance
const logger = winston.createLogger({
  level: 'info', // Log level
  format: winston.format.simple(), // Log format
  transports: [
    new winston.transports.Console(), // Log to the console
    new winston.transports.File({ filename: 'app.log' }) // Log to a file
  ]
});

// Log some messages
logger.log('info', 'This is an info message.');
logger.log('error', 'This is an error message.');

Caching :

Because Who Wants to Make the Same Trip Twice in the World of Code!

Once again, remember the ABCs of writing code. Whenever there is common data that is queried from a database, prefer it to be cached and the overhead time of querying our database is saved.
In simple words, Cache Common Data to Save Valuable Database Query Time.

• Caching enhances performance by storing frequently used data in memory.
• One can use Redis, currently the most used caching solution by industry as per today’s trends.

Example of caching in NodeJS —

const NodeCache = require('node-cache');
const cache = new NodeCache({ stdTTL: 3600 }); // Cache with a 1-hour TTL

function fetchDataFromAPI(key) {
  const cachedData = cache.get(key);
  if (cachedData) {
    console.log('Data retrieved from cache');
    return cachedData;
  } else {
    // Fetch data from the API
    const data = /* ... fetch data from API ... */;
    cache.set(key, data);
    console.log('Data fetched from API and cached');
    return data;
  }
}

// Usage
const result1 = fetchDataFromAPI('cache-key-1');
const result2 = fetchDataFromAPI('cache-key-2');

Indexing :

The Savior for Navigating Vast Databases and Finding Needle-in-the-Haystack User Data

Caching may not suffice for retrieving user-specific data from a massive database. That’s where indexing emerges as the savior.

Example for MongoDB indexing in NodeJS —

// Create an index on the 'email' field for faster queries
const collection = db.collection('users');
collection.createIndex({ email: 1 });

Moving Beyond Basics: Node.js Tips for Pro Developers.

Let’s discuss the NodeJS-specific tips for production-ready code.

When Should You Opt for Node.js?

Don’t Surf the Trendy Wave, Ride the Right Technology Wave!

Node.js is often used for building APIs and handling data-intensive operations and it works a charm for the same.

When to use:

• Real-Time Applications
• APIs and Microservices

When not to use:

• CPU-Intensive Tasks
• Large Rendering Engines

Async/Await :

Syncing Up the Async Dance: Bringing Order to JavaScript with the Elegance of async/await.

Although javascript is asynchronous, at times we need to write code synchronously. For example to perform a series of actions after API response.

async function fetchData() {
  try {
    const response = await fetch('https://example.com/api/data');
    const data = await response.json();
    return data;
  } catch (error) {
    console.error('Error fetching data:', error);
    throw error;
  }
}

// Usage
fetchData()
  .then(data => {
    console.log('Data fetched successfully:', data);
  })
  .catch(error => {
    console.error('Error in data fetch:', error);
  });

Using TypeScript :

TypeScript: The Savvy Way to Keep Your Data Dancing to the Right Tune.

TypeScript is a statically typed superset of JavaScript that brings the power of strong typing and modern language features to JavaScript development, enhancing code quality and maintainability while enabling advanced tooling and error checking.

• Static Typing: TypeScript enforces static typing, catching errors early.
• Type Inference: Reduce the need for explicit type annotations.

Example —

function greet(name: string): string {
  return `Hello, ${name}!`;
}

const personName: string = "John";
console.log(greet(personName));

Using Streams :

“Node.js streams: Where data flows like a river, saving RAM’s precious shorelines.”

• They allow you to read or write data piece by piece, rather than loading the entire dataset into memory.
• Streams are particularly useful for handling large files, network communication, and real-time data processing.

const fs = require('fs');

const sourceStream = fs.createReadStream('source.txt');
const destinationStream = fs.createWriteStream('destination.txt');

sourceStream.pipe(destinationStream);

console.log('File copied successfully.');

Miscellaneous :

• Implement robust error handling to gracefully manage failures in your code
• Using Gzip compression can reduce the amount of data sent over the network, resulting in faster response times and reduced bandwidth usage.
• Choose the correct API type REST vs. GraphQL.