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  4. Introduction to Microservices Messaging Protocols

Introduction to Microservices Messaging Protocols

The microservices architectural style subverts many of the problems associated with monolithic scaling, speed, language barriers, and organization.

Sarah Roman user avatar by
Sarah Roman
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Dec. 14, 18 · Opinion
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When companies have pulled together an application based on a variety of services, you can expect that they’re running the microservice architectural structure. Used primarily for implementation, microservices provide patterns, protocols, and deployment of complex applications. Foundationally, this architectural style subverts many of the problems associated with monolithic scaling, speed, language barriers, and organization.

While there’s large-scale adoption of microservices technology due to these reasons, we should home in on two parts of the microservices architecture that is often a stumbling block for developers: communication and messaging.

What's So Different About Communication in a Microservice Architecture?

When transitioning from a monolithic application structure to a multi-independent structure, you’ll find immediately that calling on other components isn’t aligned to a single-process system. Within the single-process system, you would typically call on components using various language methods or via Dependency Injection, like we see with Angular. Since a microservices-based application could be running across a large variety of servers, hosts, and processes, we see communication tilted towards HTTP (Hyper Text Transfer Protocol), TCP (Transmission Control Protocol), and AMQP (Advanced Message Queuing Protocol). All of these protocols are built out for IPC, or interprocess communication, since they’re managing shared data. 

So, how does the microservices architecture tackle communication across a distributed, independent set of processes? A few intersecting ways:

  • Synchronous protocol

  • Asynchronous protocol

  • Single receiver

  • Multiple receivers

Since services, hosts, and clients communicate differently, microservices-based messaging or communication is built on the intersections of protocols and receivers.

Synchronous Protocol 

You’ll find yourself engaging in a synchronous protocol process every day, as it’s built into chat functions, HTTP, instant messaging, and “live” capabilities. It’s a data transfer that occurs at regular intervals and is usually dependent on the microprocessor clock, as there needs to be a clock signal between the sender and receiver. You can also understand this as a protocol that requires a primary/replica configuration, as one device has control over another to ensure synchronicity.

Asynchronous Protocol

The opposite of synchronous, asynchronous protocol works outside of the constraints of a clock signal and occurs at any time and at irregular intervals. As mentioned above, the synchronous protocol is microprocessor-dependent, meaning that these protocols are often used for the processes occurring inside a computer. With asynchronous processes, the lack of this dependence makes them widely used for cloud environments and operating systems. There is no need to wait for a response from the receiver after sending information.

Single Receiver

Implicit in the name, a single receiver setup denotes that each request must be processed by one receiver. So, in the case of data transmission, requests need to be staggered in order to be received, as they cannot be received at the same time.

Multiple Receivers

Multiple receivers can process multiple requests, as each request can be processed by zero to multiple receivers. For example, you’ll usually see multiple receivers used in a Saga pattern, as it needs to be asynchronous and simultaneously promote data consistency.

What Intersection Is Popular for Microservices-Based Architecture?

As you can see, the architecture relies on combinations of protocols and receivers due to the wide variety of services that need to be consolidated and managed. The most commonly used combination tends to be single-receiver communication with synchronous protocol, like HTTP or HTTPS, as it’s calling on a regular web service. You can imagine its frequency when we think about how Docker enabled the use of containers that can easily run web applications.

What's the Overall Importance of This?

While these discussion points could be somewhat topical for you, maintaining and integrating microservices is really the crux of the matter when it comes to communication. Developers want to be able to maintain the independence of each microservice while seamlessly and asynchronously integrating them into an application.

Synchronous communication among microservices in an application is often viewed as a complication, headache, and, at worst, a death knell. This is due to the fact that a microservice-based architecture thrives on the autonomy of the microservices and their instant availability to the consumer. So, even if another microservice is crippled within the application, there isn’t a ripple effect throughout all of the microservices due to synchronous dependencies.

From anecdotal research, developers often are troubled when building out architecture due to data dependencies. Sometimes, you’ll find that one microservice needs the data from another microservice within the application. If you were to use synchronous communication to request the data, there’s no backup in place if that requested microservice were to suddenly stop working. Instead of just one microservice in an “out-of-order” state, there would now be two (or more).

How Do I Avoid Synchronous Dependencies?

Replication and propagation will help sidestep the synchronicity issue. With replication, you can store data in more than one site (like a server). This greatly improves the availability of data and reduces inconsistency. With propagation, you can push and pull the data from server to client, understandably helpful for local access scenarios.

If replication and propagation aren’t current routes to be taken, you could also duplicate data across microservices. This works hand-in-hand with domain-model boundaries for each microservice. When working with domain-model boundaries, you’re looking to focus in on the scope of business capabilities and create understandable and meaningful separations between services. If you achieve meaningful separation, this will also help boost scalability and domain-driven choices for data and iteration.

What Are the Popular Communication Styles?

So, after the larger considerations of microservice-to-microservice communications, what do most people do?

  • Use HTTP/REST (synchronous) communication for services outside of the internal microservices structure. The HTTP/REST communication is ideal for external requests, as it’s built to easily handle items like real-time interactions from a client.

  • Use AMQP (asynchronous) for communication methods within the internal microservices structure.

Ultimately, the microservices architecture follows logical conclusions for the application of messaging and communication protocols within an application. When adopting microservices, there are forward-thinking pieces that you have to make sure you address as you develop and build a multi-faceted application: scalability, infrastructure, and transitions. It’s prudent to lay a strong foundation of communication throughout the services, as it helps it grow and affects other parts of the application down the line.

As you broaden your knowledge on microservices and potentially head into development and implementation, you’ll want to explore more around creating consistency within the application, exploring the case studies around adopting microservices, and the microservices’ impact on the DevOps lifecycle. The microservices-based architecture is extremely agile and powerful, especially when approached after developing the foundational aspects behind communication, understanding the scope of each service, and the front-end needs for clients and consumers.







microservice Protocol (object-oriented programming) application Receiver (information theory) Data (computing) Architecture Web Service

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