Microservices can rarely be designed in a manner that they do not need to communicate with each other. However, if you base your Microservices system on the DDD principle, there should be minimal communication required between the participant Microservices.
Cross-domain interactions of Microservices help reduce the complexity of individual services and duplication of code. We will take a look at some of the communication patterns in Chapter 8, Microservices Architectural Patterns. However, let us look at the various types of communication.
In most cases, the usability of a system is determined through the frontend. A system designed using Microservices should avoid using a monolithic user interface. There are several proponents of the idea that Microservices should contain a user interface and we agree with that.
Tying a service with a user interface gives high flexibility to the system to incorporate changes and add new features. This also ensures that distribution of teams is not by the communication hierarchy of the organization but by domains that Microservices are a part of. This practice also has the benefit of ensuring that the user interface will not become a deployment monolith at any point in time.
Although there are several challenges associated with integrating the user interface of Microservices, there are several ways to enable this integration. Let's take a look at a few.
To ensure a consistent look and feel of the end user portal, code that ensures consistency can be shared with the other frontends. However, care should be taken to ensure that no business logic, binding logic, or any other logic creeps into the shared code.
Your shared code should always be in a state of being released publicly. This will ensure that no breaking changes or business logic gets added to the shared library.
Several high-scale websites such as Facebook and MSN combine data from multiple services on their page. Such websites compose their frontend out of multiple components. Each of these components could be the user interface provided by individual Microservices. A great example of this approach is Facebook's BigPipe technology, which composes its web page from small reusable chunks called pagelets and pipes them through several executing stages inside web servers and browsers:
Facebook BigPipe (source: https://www.facebook.com/notes/facebook-engineering/bigpipe-pipelining-web-pages-for-high-performance/389414033919/)
The composition of a user interface can take place at multiple levels, ranging from development to execution. The flexibility of such integrations varies with the level they are carried out at.
The most primitive form of composition can be the sharing of code, which can be done at the time of development. However, using this integration, you have to rely on deployment monoliths as the various versions of user interface can't be deployed in parallel.
A much more flexible integration can also take place at runtime. For instance, Asynchronous JavaScript and XML (AJAX), HTML, and other dependencies can be loaded in the browser. Several JavaScript frameworks, such as Angular.js, Ember.js, and Ext.js, can help realize composition in single-page applications.
In cases where integration through JavaScript is not feasible, middleware may be used which fetches the HTML component of each Microservice and composes them to return a single HTML document to the client. Some typical examples of such compositions are the edge side includes of varnish or squid, which are proxies and caches. Server-side includes such as those available on Apache and NGINX can also be used to carry out transformations on servers rather than on caches.
Unlike web applications, rich clients need to be deployed as monoliths. Any change in the Microservices would require a fresh deployment of the client application. Unlike web applications where each Microservice consists of a user interface, it is not the case for mobile or desktop applications. Moreover, structuring the teams in a manner that each team has a frontend developer for each rich client that the application can be deployed to is not feasible.
A way in which this dependency can be minimized is by having a backend for the rich client applications which is deployed with the application:
Microservices for rich clients
Although this approach is not perfect, it does ensure that part of the system conforms to Microservices architecture. Care should be taken to not alter any Microservice to encapsulate the business logic of the rich client. The mobile and desktop clients should optimize content delivery as per their needs.
A simple solution for synchronous communication between services is to use REST and transfer JSON data over HTTP. REST can also help in service discovery by using Hypermedia as the Engine of Application State (HATEOAS). HATEOAS is a component of REST which models relationships between resources by using links. Once the client queries the entry point of the service, it can use the links it receives to navigate to other Microservices.
If text-based transfers are not desired, protocol buffers (Google's data interchange format) may be used to transmit data. This protocol has been implemented in several languages to increase its adoption, for example, Ruby protobuf.
A protocol that can be used to transmit structured data across a network is Simple Object Access Protocol (SOAP). It can be used to make calls to different Microservices using various transport mechanisms such as JMS, TCP, or UDP. SOAP is language-neutral and highly extensible.
Asynchronous message passing has the benefit of truly decoupling Microservices from each other. Since the communication is carried out by a broker, individual services need not be aware of the location of the receiver of the request. This also gives individual services the ability to scale independently and recover and respond to messages in case of failure. However, this communication pattern lacks the feature of immediate feedback and is slower than the synchronous communication format.
There are several tools available for such communication, such as MSMQ and Rabbit MQ. Microsoft Azure offers Service Bus Queues and Microsoft Azure Storage Queue for asynchronous messaging on cloud. Amazon SQS provides similar functionality in Amazon Web Services.
This process is similar to the asynchronous communication process that we discussed earlier. Orchestrated communication still uses message stores to transmit data; however, the Microservice sending the data would insert different messages in different queues in order to complete the action. For example, an Order Microservice would insert the message in the queue consumed by the Inventory Microservice and another message in the queue consumed by the Shipment Microservice:
Orchestrated communications using queues
The orchestration may be carried out by a separate component, which is known as Saga, which we will read more about in Chapter 8, Microservices Architectural Patterns.
Microservices should not share the same data store. Sharing data representation can make altering the database very difficult, and even if done, such a change always runs the risk of causing failure to services that are still using the old data representation. Such challenges ultimately lead to a bloated and complex database and accumulation of lots of dead data over time.
Data replication is a possible solution to sharing data across Microservices. However, data should not be blindly replicated across Microservices as the same problems that are present with shared databases would still remain. A custom transformation process should convert data available from the database to the schema used by the data store of the Microservice. The replication process can be triggered in batches or on certain events in the system.