layout | title | categories | author_picture | author_github | seo-title | seo-description | blog_description | additional_authors | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
post |
Asynchronous programming made resilient with MicroProfile Fault Tolerance - Part 1 |
blog |
Asynchronous programming made resilient with MicroProfile Fault Tolerance - OpenLiberty.io |
MicroProfile Fault Tolerance's @Asynchronous annotation allows you to easily apply Fault Tolerance to asynchronous API calls, and also allows you to do multiple synchronous things in parallel with resilience. |
MicroProfile Fault Tolerance's @Asynchronous annotation allows you to easily apply Fault Tolerance to asynchronous API calls, and also allows you to do multiple synchronous things in parallel with resilience. |
|
Java 8 has long-term support and is the most commonly used Java version. It has many awesome features—one of which is the CompletionStage interface. CompletionStage
provides new ways to write asynchronous code. Great stuff! However, you might have the following questions:
How can I make my asynchronous methods resilient to faults? What if an asynchronous method unexpectedly returns an exception?
MicroProfile Fault Tolerance is here to help! There are many different annotations that MicroProfile Fault Tolerance provides to help you deal with failure: @Retry, @Timeout, @CircuitBreaker, @Bulkhead and @Fallback.
But there’s one, in particular, that’s going to help you make your asynchronous methods resilient to faults: @Asynchronous. Let’s look what @Asynchronous
does and how it does it.
Adding the @Asynchronous
annotation to a method does two things:
-
Runs the method asynchronously
-
If the method returns a
CompletionStage
, applies other Fault Tolerance strategies to the result of theCompletionStage
, rather than to the result of the method
Adding the @Asynchronous
annotation to a method makes the method run asynchronously, meaning that rather than the annotated method running straight away on the main thread when it’s called, it will run sometime later, usually on another thread. To use it, you need to add the @Asynchronous
annotation to a method, and it must return either a CompletionStage
or a Future
. You cannot apply Fault Tolerance to a returned Future
, so a CompletionStage
is preferred.
@Asynchronous
public CompletionStage<String> serviceA() {
return CompletableFuture.completedFuture("serviceA");
}
This example uses CompletableFuture.completedFuture()
to make the result compatible with the CompletionStage
return type. CompletableFuture
is an implementation of the CompletionStage
and Future
interfaces.
What happens when the serviceA()
method is called?
Usually when a method is called, it returns a result. However, when the @Asynchronous
annotation is used, Fault Tolerance intervenes. When the annotated method is called, Fault Tolerance first schedules the method to run later on a different thread, then it returns a CompletionStage
or Future
. This isn’t the CompletionStage
or Future
that’s returned from the method, because the method hasn’t run yet. It’s an object that Fault Tolerance creates.
Sometime later, the method runs and returns a CompletionStage
or Future
.
If the method returns a Future
, then the last step is for Fault Tolerance to update the Future
it previously returned to the user so that it delegates to the Future
returned from the method, allowing the user to see the result from the method.
However, if the method returns a CompletionStage
, Fault Tolerance waits for the CompletionStage
to complete, before completing the CompletionStage
it previously returned to the user. Additionally, if the CompletionStage
from the method completes with an exception, then other Fault Tolerance policies are applied, just as if that exception was thrown from the method body itself. This last step is crucial for allowing Fault Tolerance to work with other APIs that return a CompletionStage
, as we’ll see in the next section.
So @Asynchronous
sounds great, right? But how can you use it to make your asynchronous programs resilient? Let’s go through two use cases:
One use of @Asynchronous
is to apply Fault Tolerance to an asynchronous API call, which returns a CompletionStage
. Without @Asynchronous
, you wouldn’t be able to apply Fault Tolerance to the call. Let’s see why.
In this example, we’ll use the .rx()
method in the JAX-RS client API for calling remote REST services asynchronously. This method was introduced in JAX-RS 2.1. We can build up a request to fetch a String from a given URL with a GET request, where the return type is a CompletionStage
of String:
private Client client = ClientBuilder.newClient();
public CompletionStage<String> clientDemo() {
CompletionStage<String> response = client.target("http://example.com/resource")
.request(MediaType.TEXT_PLAIN)
.rx()
.get(String.class);
return response;
}
If we call the clientDemo()
method without any annotations, it works as we expect. We call it, receive a CompletionStage<String>
(named response
in the example), and then we can add an action to take when the CompletionStage
completes:
response.thenAccept(System.out::println);
--> responseText
If we wanted to retry any failed requests, we might add the @Retry
annotation to the method, but surprisingly this wouldn’t work!
Even if the HTTP request fails, the request doesn’t get retried because Fault Tolerance acts around method calls. Normally, if you annotate a method with @Retry
and it throws an exception, then it gets retried. However, when we do an HTTP request through this JAX-RS client API, it can’t throw an exception if there’s a problem with a request. The request is processed asynchronously, so when the method returns, the request probably hasn’t started yet, let alone found out that it failed. If an exception does occur, it’s propagated to the CompletionStage
and can be handled there. The result is that the method will never throw an exception, even if the request fails, meaning that the request will never be retried.
@Asynchronous
to the rescue!
If we add the @Asynchronous
annotation and the method returns a CompletionStage
, then the Fault Tolerance logic gets applied when the CompletionStage
completes, rather than when the method returns:
@Asynchronous
@Retry
public CompletionStage<String> clientDemo() {
...
}
When we call the clientDemo()
method and it returns a CompletionStage
, Fault Tolerance looks at the result and decides whether to retry when the returned CompletionStage
completes. If the request fails, the CompletionStage
completes with an exception, and Fault Tolerance decides that a retry is needed and calls the method again. As before, Fault Tolerance intercepts the method call, so the CompletionStage
returned to the caller is a different CompletionStage
so that the caller doesn’t get the result until all retries are completed.
To recap, to use Fault Tolerance with an asynchronous method you must:
-
Return a
CompletionStage
from your method - You can’t do this with aFuture
, it must be with aCompletionStage
. -
Use the
@Asynchronous
annotation - Without it, the method will never throw an exception, even if it fails.
When you do these two things, all the other Fault Tolerance logic is applied when the CompletionStage
completes, rather than when the method returns.
You can also use other Fault Tolerance annotations with @Asynchronous
to make your asynchronous method resilient. For more detail on that, see Part 2 of this blog post.
To run multiple methods in parallel, we can write methods that call other services, annotate them with the @Asynchronous
annotation, then call them like this:
@Inject
private RequestScopedClass1 requestScopedBean1;
@Inject
private RequestScopedClass2 requestScopedBean2;
public CompletionStage<String> callServicesAsynchronously() {
CompletionStage<String> result1 = requestScopedBean1.serviceA(); // Where serviceA is annotated with @Asynchronous
CompletionStage<String> result2 = requestScopedBean2.serviceB(); // Where serviceB is annotated with @Asynchronous
...
}
First, serviceA()
is called, and then serviceB()
. However, because both services are annotated with @Asynchronous
, they are executed simultaneously on different threads, rather than sequentially.
Any other Fault Tolerance annotations can also be used. For example, we can add a @Retry
to serviceA()
and a @Timeout
to serviceB()
:
@RequestScoped
public class RequestScopedClass1 {
@Retry
@Asynchronous
public CompletionStage<String> serviceA() {
doSomethingWhichMightFail()
return CompletableFuture.completedFuture("serviceA");
}
}
@RequestScoped
public class RequestScopedClass2 {
@Timeout
@Asynchronous
public CompletionStage<String> serviceB() {
doSomethingWhichMightFail()
return CompletableFuture.completedFuture("serviceB");
}
}
If serviceA()
needs several retries, then a call to retrieve the result, such as CompletionStage.thenAccept()
, won’t return until all the retries are complete.
We hope you’ve learned how to use MicroProfile Fault Tolerance to make your asynchronous programming resilient. If you want to learn more about Fault Tolerance, check out some Open Liberty Fault Tolerance guides. If you want to get involved in MicroProfile Fault Tolerance, check out the Git repo. For more information about using @Asynchronous
, including how @Asynchronous
interacts with other Fault Tolerance annotations and the limitations of using a Future
, head over to Part 2 of this blog post.