Horizontally Scaling an Express.js Application


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Express.js Application

It is critical that web applications can handle their expected load. As traffic to an application increase, horizontal scaling becomes even more essential to meet the load. In this journal, we will outline the steps involved in horizontally scaling an Express app. 

Step 1: Identify Bottlenecks

When horizontally scaling an Express application, the first step should be identifying any bottlenecks in its current architecture. This could involve database issues or server issues as well as any component which limits the traffic management capacity of the app.
Load testing tools can be an invaluable way to quickly identify bottlenecks. Through simulating multiple concurrent users, any performance issues may become evident quickly – and once identified steps can be taken to address any bottlenecks. 

Step 2: Load Balancing in networking

Implementing server load balancing is the second step in horizontally scaling an Express application. It ensures no single server becomes overburdened by spreading incoming traffic across several servers. 

Reverse proxy servers like Nginx provide an even distribution of traffic and ensure no one server becomes overburdened. Load balancing with Nginx can even distribute traffic across multiple express server instances. 

http {
    upstream express_servers {

    server {
        listen 80;
        server_name yoursite.com;

        location / {
            proxy_pass http://express_servers;
            proxy_set_header Host $host;
            proxy_set_header X-Real-IP $remote_addr;
            proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;

In this example, Nginx is configured to distribute traffic across three instances of an Express server running on ports 3000, 3001, and 3002. The proxy_pass directive is used to forward incoming requests to the Express servers, and the proxy_set_header directives are used to set headers that are required by the Express server.

Step 3: Database Scaling

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

app.get('/data', (req, res) => {
    client.get('data', (err, data) => {
        if (err) throw err;

        if (data) {
        } else {
            db.query('SELECT * FROM data', (err, results) => {
                if (err) throw err;

                const data = JSON.stringify(results);
                client.set('data', data);

In this example, Redis is used as a caching layer to reduce the load on the database.

It is crucial that the database can accommodate increased traffic. One way of dealing with increased user demand is implementing a sharded database architecture – each server is responsible for handling part of the data. 

Redis, a caching layer, provides another approach for database scaling. By caching frequently accessed data in memory, Redis can enhance application performance while decreasing database loads. 

Step 4: Track and Scale the Data

Subsequently, it is of paramount importance that your application operates as anticipated. Monitoring tools such as New Relic or AppDynamics may measure important metrics like response time, throughput rate, and error rates for accurate performance evaluation. 

If performance issues arise with an application, steps may be taken to scale it. This may involve optimizing its code or adding more servers; or increasing the capacity of existing ones. 

To Conclude

Horizontally scaling an Express application is a complex task that must be carefully planned and carried out. Addressing bottlenecks, applying load balancing techniques, expanding databases and tracking performance are essential steps towards building an application capable of handling high levels of traffic while remaining reliable and delivering top performance.

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