What is message broker used for?

In this article, you will gain information about Message Brokers. You will also gain a holistic understanding of basic concepts of Message Brokers, models of Message Brokers, comparison between Message Brokers vs APIs, best use cases of Message Brokers, top Message Broker tools, advantages and disadvantages of Message Brokers. Read along to find out in-depth information about Message Brokers.

A Message Broker is a software that allows applications, systems, and services to communicate and exchange data. This is accomplished by the message broker by translating messages between formal messaging protocols. This enables interdependent services to “talk” directly to one another, even if they are written in different languages or run on different platforms.

Message brokers are software modules that are included in Messaging Middleware or Message-Oriented Middleware (MOM) solutions. This type of middleware provides developers with a standardized method of handling data flow between an application’s components, allowing them to focus on the application’s core logic. It can function as a distributed communications layer, allowing applications on different platforms to communicate with one another.

Message Brokers are capable of validating, storing, routing, and delivering messages to their intended destinations. They act as go-betweens for other applications, allowing senders to send messages without knowing where the receivers are, whether they are active, or how many there are. This makes it easier to decouple processes and services within systems.

Some of the basic terms used in Message Brokers are as follows:

Message Brokers offer two basic message distribution patterns or messaging styles:

This is the distribution pattern used in message queues where the sender and receiver have a one-to-one relationship. Each message in the queue is sent to and consumed by a single recipient. When a message must be acted on only once, point-to-point messaging is used.

Payroll and financial transaction processing are two examples of applications for this distribution pattern. Both senders and receivers in these systems require assurance that each payment will be sent only once.

In this message distribution pattern, also known as “pub/sub,” the message producer publishes each message to a topic, and multiple message consumers subscribe to topics from which they want to receive messages. All messages posted to a topic are distributed to all applications that have subscribed to it. This is a broadcast-style distribution method in which the message’s publisher and consumers have a one-to-many relationship.

If an airline, for example, circulated updates about the landing times or delay status of its flights, multiple parties could benefit from the information, including ground crews performing aircraft maintenance and refuelling, baggage handlers, flight attendants, and pilots preparing for the plane’s next trip, and operators of visual displays informing the public. In this case, a pub/sub messaging style would be appropriate.

Hybrid models do exist in practice. For example, when multiple systems require a copy of a message while also requiring permanence and persistence from message loss. Messages must be distributed similarly to topics in these cases. Every message is routed to the system that is most interested in it. These recipients have the ability to specify which other consumers will receive the message.

Representational State Transfer (REST) refers to a set of principles and constraints that developers can use when creating web services. REST APIs are commonly used for inter-microservice communication. Any services that follow them will be able to communicate using a standard set of uniform shared stateless operators and requests.

REST APIs use Hypertext Transfer Protocol (HTTP) to communicate. HTTP is a request/response protocol, however, so it is best used in situations that call for a synchronous request/reply. This means that services making requests via REST APIs must be designed to expect an immediate response. If the client receiving the response is down, the sending service will be blocked while it awaits the reply. Failover and error handling logic should be built into both services.

Whereas, Message brokers enable asynchronous communications between services so that the sending service need not wait for the receiving service’s reply. This improves fault tolerance and resiliency in the systems in which they’re employed. In addition, the use of message brokers makes it easier to scale systems since a pub/sub messaging pattern can readily support changing numbers of services. Message brokers also keep track of consumers’ states.

Message brokers can be used to address a wide range of business needs across industries and in a variety of enterprise computing environments.

Message brokers are often employed in the following ways:

Some of the best Message Broker Tools are as follows:

Amazon Simple Notification Service (SNS) is a Cloud service that coordinates the delivery of push notifications from software applications to subscribed endpoints and clients. It allows you to send notifications to your customers directly. It can be used to send individual messages as well as in a publish-subscribe pattern. It’s a component of Amazon Web Services. One of its primary benefits is its low-cost infrastructure. It also scales the workload within your application automatically.

Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables the decoupling and scaling of microservices, distributed systems, and serverless applications. It can also be automatically scaled to the size of the workload. Amazon SQS uses a pull mechanism, which means that receivers must pull messages from SQS queues on their own.

SQS removes the complexity and overhead associated with managing and operating message-oriented middleware, allowing developers to concentrate on differentiating their work. SQS allows you to send, store, and receive messages between software components at any volume without losing messages or requiring the availability of other services.

Redis is an in-memory data store that can function as a high-performance key-value store or a message broker. It is a data structure store that is kept in memory. As a result, messages are not guaranteed to be durable there. Strings, lists, maps, sets, sorted sets, hyper logs, bitmaps, and spatial indexes are among the abstract data structures supported by Redis. Redis is fast and lightweight, which makes it a favorite among many developers around the world.

RabbitMQ is the most widely used and popular open-source best message broker software — a messaging intermediary. It is written in Erlang and is supported by the Pivotal Software Foundation. It provides a common platform and a secure location for your applications to send and receive messages.

It can handle advanced and complex routing scenarios. It offers four types of exchanges – it is a component of the broker that routes messages to appropriate queues. Messages are thus sent to exchanges first, rather than queues, in the case of RabbitMQ. Its characteristics include performance, reliability, high availability, clustering, and federation, among others. RabbitMQ comes with a simple management interface that allows you to monitor and control your message broker.

Kafka is a robust Queue Broker and an Open Source Messaging system. It is a distributed event streaming platform that can handle a high volume of messages. Message broker Kafka messages are stored on disc and allow you to seamlessly send messages from one point to another. Apache message queue messages are replicated across the entire Kafka cluster to prevent unwanted operations such as data loss from occurring. The Kafka messaging platform was designed to handle real-time event streaming, pipelining, and data replaying for fast, scalable operations.

Some of the advantages of using Message Brokers are as follows:

The use of the message broker involves asynchronous processing. Therefore, the disadvantages of using it are related to the challenges we face by using asynchronous calls.

In this article, you have learned about Message Brokers. This article also provided information on basic concepts of Message Brokers, models of Message Brokers, comparison between Message Brokers vs APIs, best use cases of Message Brokers, top Message Broker tools, advantages and disadvantages of Message Brokers.

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In the code above, I passed the credentials to the AWS account as arguments in the constructor. Remember that it’s only for example purposes! Hard-coding your credentials within your application can be dangerous. You can read more about this here.

Now you can create your SNS topic. Think of some name for your topic and trigger the createTopic function of the SnsClient. As a result of the operation, you’ll get an Aws\Result object with information about your newly created topic. You can retrieve single data using the get function on the result object. Save a TopicArn property – you‘ll need that later.

Creating a queue is very similar to creating the topic. Instead of SnsClient and createTopic function use SqsClient and createQueue function. For the next steps, you’ll need the URL and ARN property of the newly created queue. You can create as many queues as you want – we’ll connect them to the topic later.

Now you have to allow our topic to send messages to your newly created queues. AWS uses policies to manage permissions. These are represented in JSON format. For creating your policy you’ll need the topic and queue ARN’s. They uniquely identify your AWS resources. You should pass the policy to the SQS queue (not SNS topic) using sqsClient and setQueueAttributesFunction. For pointing up to which queue the policy needs to be added, you must set QueueUrl parameter.

Setting up the policy cannot be skipped. If you subscribe queues to the topic and the topic won’t have permission for sending messages – your queues will remain empty after publishing messages.

After setting up the policy you can subscribe your queues to the topic. You need to use snsClient here and its subscribe function Setting up subscription requires choosing protocol – it’s a type of endpoint on which you want to receive messages. Amazon SNS supports sms, email, or even AWS lambda function, among other things. In our case, it will be sqs protocol, as we are subscribing queues. As an Endpoint, you need to pass your queue ARN. For TopicArn – as the name of an argument says – pass your topic ARN so the client will know to which topic you want to subscribe to a new endpoint. If you want to see subscription ARN in the result – set up the ReturnSubscriptionArn parameter to true.

Your architecture setup is complete and you can move on to publishing a message. It’s very simple. All you have to do is to prepare a message and send it using snsClient and its publish function. You need to pass topic ARN, on which you are publishing, and message content. There are much more options you can set up before publishing a message such as subject, attributes, etc, but they are not required.

After running the script, access your AWS panel to see your queues. You can notice that one message has been replicated among all your queues subscribed to your topic.

Now, when you have your messages in queues, you can start receiving them. For that, use sqsClient again and call receiveMessage function. The only required parameter is QueueUrl. You can also set up how many messages you want to pull out (MaxNumberOfMessages parameter) and which attributes you want to receive. For each message returned, the reply contains several parameters, of which you are the most interested in message content and the receipt handle.

After calling the receiveMessage function you’ll get the Aws\Result object. Your messages are stored behind the Messages key as an array. Remember that it can be an empty array in case of no messages in the queue. Every message is an associative array and should look more or less like in the image presented below. You can see the message content under the Message attribute, as also your receive confirmation under the ReceiptHandle attribute.

Message brokers are often used to manage communications between on-premises systems and cloud components in hybrid cloud environments. Using a message broker gives increased control over interservice communications, ensuring that data is sent securely, reliably, and efficiently between the components of an application.

Didn't understand much about message brokers from the definition ?🤔 . That's totally fine😊. Read this article to the end, and come back to the definition, and read again.

Anyway, now you know what the term means let’s look into what message broker is.

A message broker is an intermediary program that applications and services use to communicate with each other to exchange information. Message brokers can be used to validate, store, route and deliver messages to the required destinations. Not only applications can communicate information, even if they are implemented in different programming languages. Since message brokers act as an intermediary program, the sender has no idea how many recipients there are if they are online.

Most importantly brokers ensure that recipients receive the message even if they are not online or active. (It’s kinda like email. You don’t have to be online but you still receive the message).

So how do message brokers ensure the delivery of the messages?

Message brokers use a message queue for this and it’s saved in memory or a hard disk. They are used to store messages and deliver them. (I hope you are familiar with the data structure “Queue”. This is the same as this, First In First Out).