Micronaut’s HTTP client is a game-changer when it comes to optimizing API responses. I’ve been tinkering with it lately, and I’m blown away by how it handles reactive and non-blocking requests. Let’s dive into the nitty-gritty of making your Micronaut apps blazing fast.

First things first, you’ll want to add the Micronaut HTTP client dependency to your project. If you’re using Gradle, add this to your build.gradle file:

implementation("io.micronaut:micronaut-http-client")

For Maven users, pop this into your pom.xml:

<dependency>
    <groupId>io.micronaut</groupId>
    <artifactId>micronaut-http-client</artifactId>
</dependency>

Now that we’ve got that sorted, let’s create a simple HTTP client. Micronaut makes this super easy with its declarative approach. Check this out:

@Client("https://api.example.com")
public interface ExampleClient {
    @Get("/users")
    Flux<User> getUsers();
}

This little snippet creates a client that’ll hit the “https://api.example.com” base URL. The getUsers() method will make a GET request to the “/users” endpoint and return a Flux of User objects. Pretty neat, huh?

But wait, there’s more! Micronaut’s HTTP client is built on Netty, which means it’s non-blocking by default. This is huge for performance, especially when you’re dealing with multiple concurrent requests.

Let’s say you want to fetch data from multiple endpoints in parallel. Here’s how you could do that:

@Inject
ExampleClient client;

public Flux<Data> getDataFromMultipleEndpoints() {
    return Flux.merge(
        client.getUsers(),
        client.getPosts(),
        client.getComments()
    );
}

This will fire off all three requests simultaneously and combine the results into a single Flux. It’s way faster than making these requests sequentially.

Now, let’s talk about error handling. In the real world, things don’t always go smoothly, so we need to be prepared for when API calls fail. Micronaut’s got our back here too. Check out this example:

@Get("/users/{id}")
Single<User> getUser(long id);

public Mono<User> getUserSafely(long id) {
    return Mono.from(client.getUser(id))
        .onErrorResume(error -> {
            log.error("Failed to fetch user: " + error.getMessage());
            return Mono.empty();
        });
}

This method will return an empty Mono if the API call fails, instead of throwing an exception. It’s a simple way to make your app more resilient.

One thing I love about Micronaut is how easy it makes it to customize your HTTP requests. Need to add headers? No problem:

@Headers({
    @Header(name = "User-Agent", value = "Micronaut HTTP Client"),
    @Header(name = "Authorization", value = "Bearer ${my.api.token}")
})
@Client("https://api.example.com")
public interface ExampleClient {
    // methods here
}

You can even use configuration properties in your headers, like we did with the Authorization header above. Just make sure you’ve got my.api.token set in your application.yml file.

Speaking of configuration, Micronaut gives you tons of options to fine-tune your HTTP client. Here’s a taste of what you can do in your application.yml:

micronaut:
  http:
    client:
      read-timeout: 5s
      connect-timeout: 5s
      pool:
        enabled: true
        max-connections: 50

This sets read and connect timeouts to 5 seconds, enables connection pooling, and sets a maximum of 50 connections in the pool. Play around with these settings to find what works best for your app.

Now, let’s talk about reactive programming. Micronaut’s HTTP client plays really well with reactive streams. Here’s an example of how you might process a stream of data:

@Get("/events")
Flux<Event> getEventStream();

public void processEvents() {
    client.getEventStream()
        .filter(event -> event.isImportant())
        .flatMap(this::processEvent)
        .subscribe(
            result -> log.info("Processed event: " + result),
            error -> log.error("Error processing event: " + error.getMessage())
        );
}

private Mono<String> processEvent(Event event) {
    // Do some processing here
    return Mono.just("Processed " + event.getId());
}

This setup will continuously process important events as they come in, all without blocking. It’s a great way to handle real-time data streams.

One thing that caught me out when I first started with Micronaut was how it handles JSON. By default, it uses Jackson for JSON serialization and deserialization. If you’re used to working with JSON directly, you might need to adjust your thinking a bit. Here’s a quick example:

public class User {
    private String name;
    private int age;

    // getters and setters
}

@Get("/user")
Single<User> getUser();

When you call getUser(), Micronaut will automatically deserialize the JSON response into a User object. No need to manually parse the JSON!

Now, let’s talk about testing. Micronaut makes it super easy to test your HTTP clients. Check this out:

@MicronautTest
class ExampleClientTest {
    @Inject
    EmbeddedServer embeddedServer;

    @Inject
    @Client("/")
    ExampleClient client;

    @Test
    void testGetUser() {
        User user = client.getUser(1).blockingGet();
        assertNotNull(user);
        assertEquals("John Doe", user.getName());
    }
}

This test starts up an embedded server, injects our client, and tests it against the server. It’s a great way to ensure your client is working correctly without having to hit a real API.

One feature of Micronaut’s HTTP client that I absolutely love is its support for streaming responses. This is super useful when you’re dealing with large amounts of data. Here’s how you might use it:

@Get("/large-data")
Flux<ByteBuffer> getLargeData();

public void processLargeData() {
    client.getLargeData()
        .map(buffer -> {
            // Process each chunk of data
            return processChunk(buffer);
        })
        .subscribe(
            result -> log.info("Processed chunk: " + result),
            error -> log.error("Error processing data: " + error.getMessage()),
            () -> log.info("Finished processing all data")
        );
}

This approach allows you to process data as it comes in, rather than waiting for the entire response to be downloaded. It’s a huge memory saver for large datasets.

Another cool feature is the ability to use fallbacks. This is great for implementing circuit breaker patterns. Here’s a simple example:

@Client("https://api.example.com")
public interface ExampleClient {
    @Get("/users")
    @Fallback(UserFallback.class)
    Flux<User> getUsers();
}

@Singleton
public class UserFallback implements ExampleClient {
    @Override
    public Flux<User> getUsers() {
        return Flux.just(new User("Fallback User", 0));
    }
}

If the getUsers() call fails, it’ll automatically fall back to the UserFallback implementation. This can help keep your app running smoothly even when external services are having issues.

One thing to keep in mind when working with Micronaut’s HTTP client is that it’s designed to be lightweight and fast. This means it doesn’t have some of the bells and whistles you might be used to from other HTTP clients. For example, it doesn’t have built-in support for request signing or complex authentication schemes. If you need these features, you’ll need to implement them yourself or use a third-party library.

That said, for most use cases, Micronaut’s HTTP client is more than capable. And its performance is hard to beat. I’ve seen significant improvements in response times and throughput when switching from other HTTP clients to Micronaut’s.

Let’s talk a bit about retries. In distributed systems, temporary failures are a fact of life. Micronaut’s got a neat retry mechanism built in. Here’s how you might use it:

@Retryable(attempts = "3", delay = "1s")
@Get("/flaky-endpoint")
Single<String> getFlakyData();

This will automatically retry the request up to 3 times, with a 1-second delay between attempts. It’s a simple way to make your app more resilient to transient failures.

One last thing I want to mention is Micronaut’s support for HTTP/2. This can lead to significant performance improvements, especially for apps that make lots of requests to the same server. To enable HTTP/2, you just need to add this to your application.yml:

micronaut:
  http:
    client:
      ssl:
        enabled: true
      http-version: HTTP_2_0

Make sure your server supports HTTP/2, and you’re good to go!

In conclusion, Micronaut’s HTTP client is a powerful tool for building fast, efficient, and resilient microservices. Its reactive nature, combined with features like non-blocking I/O, connection pooling, and automatic retries, make it a top choice for modern Java applications. Whether you’re building a simple REST client or a complex distributed system, Micronaut’s got you covered. So go ahead, give it a try in your next project. I think you’ll be as impressed as I am!