Orchestrating microservices

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.

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