Applications within modern cloud architecture are decoupled into smaller, independent, more easily developed, and easier to deploy building blocks. This type of architectural pattern relies on message queues so that distributed applications can communicate and share information. The implementation of queues simplifies the coding of decoupled applications and improves performance, reliability, and scalability. The message queue stores and orders messages until the consuming applications can process them. Messages are stored in strict order of transmission and remain in the queue until receipt is acknowledged.
A message broker is a type of message system that allows applications, systems, and services to communicate and exchange information. The broker provides message translation between formal messaging protocols, allowing interdependent services to communicate despite being in different languages or on different platforms. A message broker is a software module within messaging middleware that provides a standardized means of handling data flow between the application’s components. With this message system, the source application or producer deploys a message to a server that provides data marshaling, routing, message translation, persistence, and deployment to the appropriate destinations or message consumers.
A broker is a discrete service that allows communication using standard or proprietary protocols. The two basic forms of communication with a message broker are publish and subscribe messaging and point-to-point communication. Message brokers can validate, store, route, and deliver messages to the appropriate destinations. They are intermediaries between applications that give senders the ability to issue messages without knowing where, how many, and whether the receivers are active or not. This aids in the decoupling of services within systems.
Message queues allow for asynchronous communication, meaning the endpoints producing and consuming messages (the message producer and the message consumer) interact with the queue. Message producers can add requests to the queue without the need to wait for processing. Message consumers process messages when they become available. This means there’s no stalling of any system component, which optimizes data flow.
Queues increase reliability by improving data persistence and reducing errors that arise when different parts within a system are offline. Separating different system components via message queues creates more fault tolerance. In the event one component is unreachable, the other component can continue to interact with the queue.
Queues offer granular scalability where needed. As workloads peak, multiple components can continue to add requests to the queue without risking collision. As queues get longer with incoming requests, the workload can be distributed across multiple message consumers. Message queues, message producers, and message consumers can all scale up or down on demand.
Message queues eliminate dependencies between system components and simplify decoupling. When software components aren’t burdened by communication code they can be designed to perform a discrete business function. Queues are a simple way to decouple any type of distributed system, including monolithic applications, microservices, or serverless architectures.
Queues can help break up applications. Instead of performing several functions within a single executable, multiple programs can exchange information. Being able to send messages between processes makes them easier to test, debug, evolve, and scale. Message queuing services help with microservices integration. Microservices integration patterns based on events and asynchronous messaging are more resilient and scalable. Queuing is useful when coordinating multiple microservices, notifying microservices of data changes, or processing Internet of Things (IoT), social, and real-time data. The implementations of message queues help with the shift to serverless architectures. They provide reliable, scalable serverless notifications, inter-process communications, and visibility of serverless functions.
Implementing a messaging system addresses a variety of business needs across various industries with diverse computing environments. Brokers are helpful whenever reliable inter-application communication and guaranteed message delivery are necessary. Some common use cases for brokers include financial transactions and payment processing, e-commerce order processing and fulfillment, and protecting sensitive data at rest and in motion.