Orchestrating microservices

What is the standard pattern of orchestrating microservices?

If a microservice only knows about its own domain, but there is a flow of data that requires that multiple services interact in some manner, what's the way to go about it?

Let's say we have something like this:

• Invoicing
• Shipment

And for the sake of the argument, let's say that once an order has been shipped, the invoice should be created.

Somewhere, someone presses a button in a GUI, "I'm done, let's do this!" In a classic monolith service architecture, I'd say that there is either an ESB handling this, or the Shipment service has knowledge of the invoice service and just calls that.

But what is the way people deal with this in this brave new world of microservices?

I do get that this could be considered highly opinion-based. but there is a concrete side to it, as microservices are not supposed to do the above. So there has to be a "what should it by definition do instead", which is not opinion-based.

Shoot.

The Book Building Microservices describes in detail the styles mentioned by @RogerAlsing in his answer.

On page 43 under Orchestration vs Choreography the book says:

> As we start to model more and more complex logic, we have to deal with > the problem of managing business processes that stretch across the > boundary of individual services. And with microservices, we’ll hit > this limit sooner than usual. [...] When it comes to actually > implementing this flow, there are two styles of architecture we could > follow. With orchestration, we rely on a central brain to guide and > drive the process, much like the conductor in an orchestra. With > choreography, we inform each part of the system of its job and let it > work out the details, like dancers all find‐ ing their way and > reacting to others around them in a ballet.

The book then proceeds to explain the two styles. The orchestration style corresponds more to the SOA idea of orchestration/task services, whereas the choreography style corresponds to the dumb pipes and smart endpoints mentioned in Martin Fowler's article.

Orchestration Style

Under this style, the book above mentions:

> Let’s think about what an orchestration solution would look like for > this flow. Here, probably the simplest thing to do would be to have > our customer service act as the central brain. On creation, it talks > to the loyalty points bank, email service, and postal service [...], > through a series of request/response calls. The > customer service itself can then track where a customer is in this > process. It can check to see if the customer’s account has been set > up, or the email sent, or the post delivered. We get to take the > flowchart [...] and model it directly into code. We could even use > tooling that implements this for us, perhaps using an appropriate > rules engine. Commercial tools exist for this very purpose in the form > of business process modeling software. Assuming we use synchronous > request/response, we could even know if each stage has worked [...] > The downside to this orchestration approach is that the customer > service can become too much of a central governing authority. It can > become the hub in the middle of a web and a central point where logic > starts to live. I have seen this approach result in a small number of > smart “god” services telling anemic CRUD-based services what to do.

Note: I suppose that when the author mentions tooling he's referring to something like BPM (e.g. Activity, Apache ODE, Camunda). As a matter of fact, the Workflow Patterns Website has an awesome set of patterns to do this kind of orchestration and it also offers evaluation details of different vendor tools that help to implement it this way. I don't think the author implies one is required to use one of these tools to implement this style of integration though, other lightweight orchestration frameworks could be used e.g. Spring Integration, Apache Camel or Mule ESB

However, other books I've read on the topic of Microservices and in general the majority of articles I've found in the web seem to disfavor this approach of orchestration and instead suggest using the next one.

Choreography Style

Under choreography style the author says:

> With a choreographed approach, we could instead just have the customer > service emit an event in an asynchronous manner, saying Customer > created. The email service, postal service, and loyalty points bank > then just subscribe to these events and react accordingly [...] > This approach is significantly more decoupled. If some > other service needed to reach to the creation of a customer, it just > needs to subscribe to the events and do its job when needed. The > downside is that the explicit view of the business process we see in > [the workflow] is now only implicitly reflected in our system [...] > This means additional work is needed to ensure that you can monitor > and track that the right things have happened. For example, would you > know if the loyalty points bank had a bug and for some reason didn’t > set up the correct account? One approach I like for dealing with this > is to build a monitoring system that explicitly matches the view of > the business process in [the workflow], but then tracks what each of > the services do as independent entities, letting you see odd > exceptions mapped onto the more explicit process flow. The [flowchart] > [...] isn’t the driving force, but just one lens through > which we can see how the system is behaving. In general, I have found > that systems that tend more toward the choreographed approach are more > loosely coupled, and are more flexible and amenable to change. You do > need to do extra work to monitor and track the processes across system > boundaries, however. I have found most heavily orchestrated > implementations to be extremely brittle, with a higher cost of change. > With that in mind, I strongly prefer aiming for a choreographed > system, where each service is smart enough to understand its role in > the whole dance.

Note: To this day I'm still not sure if choreography is just another name for event-driven architecture (EDA), but if EDA is just one way to do it, what are the other ways? (Also see What do you mean by "Event-Driven"? and The Meanings of Event-Driven Architecture). Also, it seems that things like CQRS and EventSourcing resonate a lot with this architectural style, right?

Now, after this comes the fun. The Microservices book does not assume microservices are going to be implemented with REST. As a matter of fact in the next section in the book, they proceed to consider RPC and SOA-based solutions and finally REST. An important point here is that Microservices does not imply REST.

So, What About HATEOAS? (Hypermedia as the Engine of Application State)

Now, if we want to follow the RESTful approach we cannot ignore HATEOAS or Roy Fielding will be very much pleased to say in his blog that our solution is not truly REST. See his blog post on REST API Must be Hypertext Driven:

> I am getting frustrated by the number of people calling any HTTP-based > interface a REST API. What needs to be done to make the REST > architectural style clear on the notion that hypertext is a > constraint? In other words, if the engine of application state (and > hence the API) is not being driven by hypertext, then it cannot be > RESTful and cannot be a REST API. Period. Is there some broken manual > somewhere that needs to be fixed?

So, as you can see, Fielding thinks that without HATEOAS you are not truly building RESTful applications. For Fielding, HATEOAS is the way to go when it comes to orchestrating services. I am just learning all this, but to me, HATEOAS does not clearly define who or what is the driving force behind actually following the links. In a UI that could be the user, but in computer-to-computer interactions, I suppose that needs to be done by a higher level service.

According to HATEOAS, the only link the API consumer truly needs to know is the one that initiates the communication with the server (e.g. POST /order). From this point on, REST is going to conduct the flow, because, in the response of this endpoint, the resource returned will contain the links to the next possible states. The API consumer then decides what link to follow and move the application to the next state.

Despite how cool that sounds, the client still needs to know if the link must be POSTed, PUTed, GETed, PATCHed, etc. And the client still needs to decide what payload to pass. The client still needs to be aware of what to do if that fails (retry, compensate, cancel, etc.).

I am fairly new to all this, but for me, from HATEOAs perspective, this client, or API consumer is a high order service. If we think it from the perspective of a human, you can imagine an end-user on a web page, deciding what links to follow, but still, the programmer of the web page had to decide what method to use to invoke the links, and what payload to pass. So, to my point, in a computer-to-computer interaction, the computer takes the role of the end-user. Once more this is what we call an orchestrations service.

I suppose we can use HATEOAS with either orchestration or choreography.

The API Gateway Pattern

Another interesting pattern is suggested by Chris Richardson who also proposed what he called an API Gateway Pattern.

> In a monolithic architecture, clients of the application, such as web > browsers and native applications, make HTTP requests via a load > balancer to one of N identical instances of the application. But in a > microservice architecture, the monolith has been replaced by a > collection of services. Consequently, a key question we need to answer > is what do the clients interact with? > > An application client, such as a native mobile application, could make > RESTful HTTP requests to the individual services [...] On the surface > this might seem attractive. However, there is likely to be a > significant mismatch in granularity between the APIs of the individual > services and data required by the clients. For example, displaying one > web page could potentially require calls to large numbers of services. > Amazon.com, for example, > describes how some > pages require calls to 100+ services. Making that many requests, even > over a high-speed internet connection, let alone a lower-bandwidth, > higher-latency mobile network, would be very inefficient and result in > a poor user experience. > > A much better approach is for clients to make a small number of > requests per-page, perhaps as few as one, over the Internet to a > front-end server known as an API gateway. > > The API gateway sits between the application’s clients and the > microservices. It provides APIs that are tailored to the client. The > API gateway provides a coarse-grained API to mobile clients and a > finer-grained API to desktop clients that use a high-performance > network. In this example, the desktop clients make multiple requests > to retrieve information about a product, whereas a mobile client > makes a single request. > > The API gateway handles incoming requests by making requests to some > number of microservices over the high-performance LAN. Netflix, for > example, > describes > how each request fans out to on average six backend services. In this > example, fine-grained requests from a desktop client are simply > proxied to the corresponding service, whereas each coarse-grained > request from a mobile client is handled by aggregating the results of > calling multiple services. > > Not only does the API gateway optimize communication between clients > and the application, but it also encapsulates the details of the > microservices. This enables the microservices to evolve without > impacting the clients. For example, two microservices might be > merged. Another microservice might be partitioned into two or more > services. Only the API gateway needs to be updated to reflect these > changes. The clients are unaffected. > > Now that we have looked at how the API gateway mediates between the > application and its clients, let’s now look at how to implement > communication between microservices.

This sounds pretty similar to the orchestration style mentioned above, just with a slightly different intent, in this case, it seems to be all about performance and simplification of interactions.

Trying to aggregate the different approaches here.

Domain Events

The dominant approach for this seems to be using domain events, where each service publish events regarding what have happened and other services can subscribe to those events. This seems to go hand in hand with the concept of smart endpoints, dumb pipes that is described by Martin Fowler here: http://martinfowler.com/articles/microservices.html#SmartEndpointsAndDumbPipes

Proxy

Another apporach that seems common is to wrap the business flow in its own service. Where the proxy orchestrates the interaction between the microservices like shown in the below picture:

.

Other patterns of the composition

This page contains various composition patterns.

So, how is orchestration of microservices different from orchestration of old SOA services that are not “micro”? Not much at all.

Microservices usually communicate using http (REST) or messaging/events. Orchestration is often associated with orchestration platforms that allow you to create a scripted interaction among services to automate workflows. In the old SOA days, these platforms used WS-BPEL. Today's tools don't use BPEL. Examples of modern orchestration products: Netflix Conductor, Camunda, Zeebe, Azure Logic Apps, Baker.

Keep in mind that orchestration is a compound pattern that offers several capabilities to create complex compositions of services. Microservices are more often seen as services that should not participate in complex compositions and rather be more autonomous.

I can see a microservice being invoked in an orchestrated workflow to do some simple processing, but I don’t see a microservice being the orchestrator service, which often uses mechanisms such as compensating transactions and state repository (dehydration).

So you're having two services:

1. Invoice micro service
2. Shipment micro service

In real life, you would have something where you hold the order state. Let's call it order service. Next you have order processing use cases, which know what to do when the order transitions from one state to another. All these services contain a certain set of data, and now you need something else, that does all the coordination. This might be:

• A simple GUI knowing all your services and implementing the use cases ("I'm done" calls the shipment service)
• A business process engine, which waits for an "I'm done" event. This engine implements the use cases and the flow.
• An orchestration micro service, let's say the order processing service itself that knows the flow/use cases of your domain
• Anything else I did not think about yet

The main point with this is that the control is external. This is because all your application components are individual building blocks, loosely coupled. If your use cases change, you have to alter one component in one place, which is the orchestration component. If you add a different order flow, you can easily add another orchestrator that does not interfere with the first one. The micro service thinking is not only about scalability and doing fancy REST API's but also about a clear structure, reduced dependencies between components and reuse of common data and functionality that are shared throughout your business.

HTH, Mark

If the State needs to be managed then the Event Sourcing with CQRS is the ideal way of communication. Else, an Asynchronous messaging system (AMQP) can be used for inter microservice communication.

From your question, it is clear that the ES with CQRS should be the right mix. If using java, take a look at Axon framework. Or build a custom solution using Kafka or RabbitMQ.

You can implement orchestration by using spring State machine model.

Steps

1. Add below dependency to your project ( if you are using Maven)

    <dependency>
    	<groupId>org.springframework.statemachine</groupId>
    	<artifactId>spring-statemachine-core</artifactId>
    	<version>2.2.0.RELEASE</version>
    </dependency>
   

2. Define states and events e.g. State 1, State 2 and Event 1 and Event 2

3. Provide state machine implementation in buildMachine() method.

   configureStates
   configureTransitions
   

4. Send events to state machine

Refer to documentation page for complete code

i have written few posts on this topic:

Maybe these posts can also help:

API Gateway pattern - Course-grained api vs fine-grained apis

https://www.linkedin.com/pulse/api-gateway-pattern-ronen-hamias/ https://www.linkedin.com/pulse/successfulapi-ronen-hamias/

Coarse-grained vs Fine-grained service API

>By definition a coarse-grained service operation has broader scope than a fine-grained service, although the terms are relative. coarse-grained increased design complexity but can reduce the number of calls required to complete a task. at micro-services architecture coarse-grained may reside at the API Gateway layer and orchestrate several micro-services to complete specific business operation. coarse-grained APIs needs to be carefully designed as involving several micro-services that managing different domain of expertise has a risk to mix-concerns in single API and breaking the rules described above. coarse-grained APIs may suggest new level of granularity for business functions that where not exist otherwise. for example hire employee may involve two microservices calls to HR system to create employee ID and another call to LDAP system to create a user account. alternatively client may have performed two fine-grained API calls to achieve the same task. while coarse-grained represents business use-case create user account, fine-grained API represent the capabilities involved in such task. further more fine-grained API may involve different technologies and communication protocols while coarse-grained abstract them into unified flow. when designing a system consider both as again there is no golden approach that solve everything and there is trad-off for each. Coarse-grained are particularly suited as services to be consumed in other Business contexts, such as other applications, line of business or even by other organizations across the own Enterprise boundaries (typical B2B scenarios).

the answer to the original question is SAGA pattern.