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In this article by Mario Casciaro, the author of the book, “Node.js Design Patterns“, has described the importance of using a middleware pattern.

One of the most distinctive patterns in Node.js is definitely middleware. Unfortunately it’s also one of the most confusing for the inexperienced, especially for developers coming from the enterprise programming world. The reason for the disorientation is probably connected with the meaning of the term middleware, which in the enterprise architecture’s jargon represents the various software suites that help to abstract lower level mechanisms such as OS APIs, network communications, memory management, and so on, allowing the developer to focus only on the business case of the application. In this context, the term middleware recalls topics such as CORBA, Enterprise Service Bus, Spring, JBoss, but in its more generic meaning it can also define any kind of software layer that acts like a glue between lower level services and the application (literally the software in the middle).

(For more resources related to this topic, see here.)

Middleware in Express

Express (http://expressjs.com) popularized the term middleware in theNode.js world, binding it to a very specific design pattern. In express, in fact, a middleware represents a set of services, typically functions, that are organized in a pipeline and are responsible for processing incoming HTTP requests and relative responses. An express middleware has the following signature:

function(req, res, next) { … }

Where req is the incoming HTTP request, res is the response, and next is the callback to be invoked when the current middleware has completed its tasks and that in turn triggers the next middleware in the pipeline.

Examples of the tasks carried out by an express middleware are as the following:

  • Parsing the body of the request
  • Compressing/decompressing requests and responses
  • Producing access logs
  • Managing sessions
  • Providing Cross-site Request Forgery (CSRF) protection

If we think about it, these are all tasks that are not strictly related to the main functionality of an application, rather, they are accessories, components providing support to the rest of the application and allowing the actual request handlers to focus only on their main business logic. Essentially, those tasks are software in the middle.

Middleware as a pattern

The technique used to implement middleware in express is not new; in fact, it can be considered the Node.js incarnation of the Intercepting Filter pattern and the Chain of Responsibility pattern. In more generic terms, it also represents a processing pipeline,which reminds us about streams. Today, in Node.js, the word middleware is used well beyond the boundaries of the express framework, and indicates a particular pattern whereby a set of processing units, filters, and handlers, under the form of functions are connected to form an asynchronous sequence in order to perform preprocessing and postprocessing of any kind of data. The main advantage of this pattern is flexibility; in fact, this pattern allows us to obtain a plugin infrastructure with incredibly little effort, providing an unobtrusive way for extending a system with new filters and handlers.

If you want to know more about the Intercepting Filter pattern, the following article is a good starting point: http://www. oracle.com/technetwork/ java/interceptingfilter-142169.html. A nice overview of the Chain of Responsibility pattern is available at this URL: http:// java.dzone.com/articles/design-patterns-uncovered-chain-of-responsibility.

The following diagram shows the components of the middleware pattern:

The essential component of the pattern is the Middleware Manager, which is responsible for organizing and executing the middleware functions. The most important implementation details of the pattern are as follows:

  • New middleware can be registered by invoking the use() function (the name of this function is a common convention in many implementations of this pattern, but we can choose any name). Usually, new middleware can only be appended at the end of the pipeline, but this is not a strict rule.
  • When new data to process is received, the registered middleware is invoked in an asynchronous sequential execution flow. Each unit in the pipeline receives in input the result of the execution of the previous unit.
  • Each middleware can decide to stop further processing of the data by simply not invoking its callback or by passing an error to the callback. An error situation usually triggers the execution of another sequence of middleware that is specifically dedicated to handling errors.

There is no strict rule on how the data is processed and propagated in the pipeline. The strategies include:

  • Augmenting the data with additional properties or functions
  • Replacing the data with the result of some kind of processing
  • Maintaining the immutability of the data and always returning fresh copies as result of the processing

The right approach that we need to take depends on the way the Middleware Manager is implemented and on the type of processing carried out by the middleware itself.

Creating a middleware framework for ØMQ

Let’s now demonstrate the pattern by building a middleware framework around the ØMQ (http://zeromq.org) messaging library. ØMQ (also known as ZMQ, or ZeroMQ) provides a simple interface for exchanging atomic messages across the network using a variety of protocols; it shines for its performances, and its basic set of abstractions are specifically built to facilitate the implementation of custom messaging architectures. For this reason, ØMQ is often chosen to build complex distributed systems.

The interface of ØMQ is pretty low-level, it only allows us to use strings and binary buffers for messages, so any encoding or custom formatting of data has to be implemented by the users of the library.

In the next example, we are going to build a middleware infrastructure to abstract the preprocessing and postprocessing of the data passing through a ØMQ socket, so that we can transparently work with JSON objects but also seamlessly compress the messages traveling over the wire.

Before continuing with the example, please make sure to install the ØMQ native libraries following the instructions at this URL: http://zeromq.org/intro:get-the-software. Any version in the 4.0 branch should be enough for working on this example.

The Middleware Manager

The first step to build a middleware infrastructure around ØMQ is to create a component that is responsible for executing the middleware pipeline when a new message is received or sent. For the purpose, let’s create a new module called zmqMiddlewareManager.js and let’s start defining it:

function ZmqMiddlewareManager(socket) {
this.socket = socket;
this.inboundMiddleware = []; //[1]
this.outboundMiddleware = [];
var self = this;
socket.on('message', function(message) { //[2]
self.executeMiddleware(self.inboundMiddleware, {
data: message
module.exports = ZmqMiddlewareManager;

This first code fragment defines a new constructor for our new component. It accepts a ØMQ socket as an argument and:

  1. Creates two empty lists that will contain our middleware functions, one for the inbound messages and another one for the outbound messages.
  2. Immediately, it starts listening for the new messages coming from the socket by attaching a new listener to the message event. In the listener, we process the inbound message by executing the inboundMiddleware pipeline.

The next method of the ZmqMiddlewareManager prototype is responsible for executing the middleware when a new message is sent through the socket:

ZmqMiddlewareManager.prototype.send = function(data) {
var self = this;
var message = { data: data};
self.executeMiddleware(self.outboundMiddleware, message, 
   function() {

This time the message is processed using the filters in the outboundMiddleware list and then passed to socket.send() for the actual network transmission.

Now, we need a small method to append new middleware functions to our pipelines; we already mentioned that such a method is conventionally called use():

ZmqMiddlewareManager.prototype.use = function(middleware) {
if(middleware.inbound) {
}if(middleware.outbound) {

Each middleware comes in pairs; in our implementation it’s an object that contains two properties, inbound and outbound, that contain the middleware functions to be added to the respective list.

It’s important to observe here that the inbound middleware is pushed to the end of the inboundMiddleware list, while the outbound middleware is inserted at the beginning of the outboundMiddleware list. This is because complementary

inbound/outbound middleware functions usually need to be executed in an inverted order. For example, if we want to decompress and then deserialize an inbound message using JSON, it means that for the outbound, we should instead first serialize and then compress.

It’s important to understand that this convention for organizing the middleware in pairs is not strictly part of the general pattern, but only an implementation detail of our specific example.

Now, it’s time to define the core of our component, the function that is responsible for executing the middleware:

ZmqMiddlewareManager.prototype.executeMiddleware = 
function(middleware, arg, finish) {var self = this;(
   function iterator(index) {
     if(index === middleware.length) {
       return finish && finish();
     middleware[index].call(self, arg, function(err) { if(err) {
       console.log('There was an error: ' + err.message);

The preceding code should look very familiar; in fact, it is a simple implementation of the asynchronous sequential iteration pattern. Each function in the middleware array received in input is executed one after the other, and the same

arg object is provided as an argument to each middleware function; this is the trickthat makes it possible to propagate the data from one middleware to the next. At the end of the iteration, the finish() callback is invoked.

Please note that for brevity we are not supporting an error middleware pipeline. Normally, when a middleware function propagates an error, another set of middleware specifically dedicated to handling errors is executed. This can be easily implemented using the same technique that we are demonstrating here.

A middleware to support JSON messages

Now that we have implemented our Middleware Manager, we can create a pair of middleware functions to demonstrate how to process inbound and outbound messages. As we said, one of the goals of our middleware infrastructure is having a filter that serializes and deserializes JSON messages, so let’s create a new middleware to take care of this. In a new module called middleware.js; let’s include the following code:

module.exports.json = function() {
return {
   inbound: function(message, next) {
     message.data = JSON.parse(message.data.toString());
   outbound: function(message, next) {
     message.data = new Buffer(JSON.stringify(message.data));

The json middleware that we just created is very simple:

The inbound middleware deserializes the message received as an input and assigns the result back to the data property of message, so that it can be further processed along the pipeline

The outbound middleware serializes any data found into message.data

Design Patterns

Please note how the middleware supported by our framework is quite different from the one used in express; this is totally normal and a perfect demonstration of how we can adapt this pattern to fit our specific need.

Using the ØMQ middleware framework

We are now ready to use the middleware infrastructure that we just created. To do that, we are going to build a very simple application, with a client sending a ping to a server at regular intervals and the server echoing back the message received.

From an implementation perspective, we are going to rely on a request/reply messaging pattern using the req/rep socket pair provided by ØMQ (http://zguide. zeromq.org/page:all#Ask-and-Ye-Shall-Receive). We will then wrap the socketswith our zmqMiddlewareManager to get all the advantages from the middleware infrastructure that we built, including the middleware for serializing/deserializing JSON messages.

The server

Let’s start by creating the server side (server.js). In the first part of the module we initialize our components:

var zmq = require('zmq');
var ZmqMiddlewareManager = require('./zmqMiddlewareManager');
var middleware = require('./middleware');
var reply = zmq.socket('rep');

In the preceding code, we loaded the required dependencies and bind a ØMQ ‘rep’ (reply) socket to a local port. Next, we initialize our middleware:

var zmqm = new ZmqMiddlewareManager(reply);

We created a new ZmqMiddlewareManager object and then added two middlewares, one for compressing/decompressing the messages and another one for parsing/ serializing JSON messages. For brevity, we did not show the implementation of the zlib middleware.

Now we are ready to handle a request coming from the client, we will do this by simply adding another middleware, this time using it as a request handler:

inbound: function(message, next) { console.log('Received: ', 
if(message.data.action === 'ping') {
    this.send({action: 'pong', echo: message.data.echo});

Since this last middleware is defined after the zlib and json middlewares, we can transparently use the decompressed and deserialized message that is available in the message.data variable. On the other hand, any data passed to send() will be processed by the outbound middleware, which in our case will serialize then compress the data.

The client

On the client side of our little application, client.js, we will first have to initiate a new ØMQ req (request) socket connected to the port 5000, the one used by our server:

var zmq = require('zmq');
var ZmqMiddlewareManager = require('./zmqMiddlewareManager'); var middleware = require('./middleware');
var request = zmq.socket('req'); request.connect('tcp://');

Then, we need to set up our middleware framework in the same way that we did for the server:

var zmqm = new ZmqMiddlewareManager(request);

Next, we create an inbound middleware to handle the responses coming from the server:

inbound: function(message, next) {
   console.log('Echoed back: ', message.data);

In the preceding code, we simply intercept any inbound response and print it to the console.

Finally, we set up a timer to send some ping requests at regular intervals, always using the zmqMiddlewareManager to get all the advantages of our middleware:

setInterval(function() {
zmqm.send({action: 'ping', echo: Date.now()});
}, 1000);

We can now try our application by first starting the server:

node server

We can then start the client with the following command:

node client

At this point, we should see the client sending messages and the server echoing them back.

Our middleware framework did its job; it allowed us to decompress/compress and deserialize/serialize our messages transparently, leaving the handlers free to focus on their business logic!


In this article, we learned about the middleware pattern and the various facets of the pattern, and we also saw how to create a middleware framework and how to use.

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