Partner – Microsoft – NPI EA (cat = Baeldung)
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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, visit the documentation page.

You can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Microsoft – NPI EA (cat= Spring Boot)
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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, you can get started over on the documentation page.

And, you can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Orkes – NPI EA (cat=Spring)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

Try a 14-Day Free Trial of Orkes Conductor today.

Partner – Orkes – NPI EA (tag=Microservices)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

Try a 14-Day Free Trial of Orkes Conductor today.

eBook – Guide Spring Cloud – NPI EA (cat=Spring Cloud)
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Let's get started with a Microservice Architecture with Spring Cloud:

>> Join Pro and download the eBook

eBook – Mockito – NPI EA (tag = Mockito)
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Mocking is an essential part of unit testing, and the Mockito library makes it easy to write clean and intuitive unit tests for your Java code.

Get started with mocking and improve your application tests using our Mockito guide:

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eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.

Get started with understanding multi-threaded applications with our Java Concurrency guide:

>> Download the eBook

eBook – Reactive – NPI EA (cat=Reactive)
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Spring 5 added support for reactive programming with the Spring WebFlux module, which has been improved upon ever since. Get started with the Reactor project basics and reactive programming in Spring Boot:

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eBook – Java Streams – NPI EA (cat=Java Streams)
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Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.

But these can also be overused and fall into some common pitfalls.

To get a better understanding on how Streams work and how to combine them with other language features, check out our guide to Java Streams:

>> Join Pro and download the eBook

eBook – Jackson – NPI EA (cat=Jackson)
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Do JSON right with Jackson

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eBook – HTTP Client – NPI EA (cat=Http Client-Side)
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Get the most out of the Apache HTTP Client

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eBook – Maven – NPI EA (cat = Maven)
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Get Started with Apache Maven:

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eBook – Persistence – NPI EA (cat=Persistence)
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Working on getting your persistence layer right with Spring?

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eBook – RwS – NPI EA (cat=Spring MVC)
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Building a REST API with Spring?

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Course – LS – NPI EA (cat=Jackson)
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Get started with Spring and Spring Boot, through the Learn Spring course:

>> LEARN SPRING
Course – RWSB – NPI EA (cat=REST)
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Explore Spring Boot 3 and Spring 6 in-depth through building a full REST API with the framework:

>> The New “REST With Spring Boot”

Course – LSS – NPI EA (cat=Spring Security)
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Yes, Spring Security can be complex, from the more advanced functionality within the Core to the deep OAuth support in the framework.

I built the security material as two full courses - Core and OAuth, to get practical with these more complex scenarios. We explore when and how to use each feature and code through it on the backing project.

You can explore the course here:

>> Learn Spring Security

Course – LSD – NPI EA (tag=Spring Data JPA)
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Spring Data JPA is a great way to handle the complexity of JPA with the powerful simplicity of Spring Boot.

Get started with Spring Data JPA through the guided reference course:

>> CHECK OUT THE COURSE

Partner – MongoDB – NPI EA (tag=MongoDB)
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Traditional keyword-based search methods rely on exact word matches, often leading to irrelevant results depending on the user's phrasing.

By comparison, using a vector store allows us to represent the data as vector embeddings, based on meaningful relationships. We can then compare the meaning of the user’s query to the stored content, and retrieve more relevant, context-aware results.

Explore how to build an intelligent chatbot using MongoDB Atlas, Langchain4j and Spring Boot:

>> Building an AI Chatbot in Java With Langchain4j and MongoDB Atlas

Partner – LambdaTest – NPI EA (cat=Testing)
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Accessibility testing is a crucial aspect to ensure that your application is usable for everyone and meets accessibility standards that are required in many countries.

By automating these tests, teams can quickly detect issues related to screen reader compatibility, keyboard navigation, color contrast, and other aspects that could pose a barrier to using the software effectively for people with disabilities.

Learn how to automate accessibility testing with Selenium and the LambdaTest cloud-based testing platform that lets developers and testers perform accessibility automation on over 3000+ real environments:

Automated Accessibility Testing With Selenium

eBook – Java Concurrency – NPI (cat=Java Concurrency)
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Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.

Get started with understanding multi-threaded applications with our Java Concurrency guide:

>> Download the eBook

1. Overview

Java 8’s CompletableFuture is well-suited to handling asynchronous computation. For instance, a web client may employ CompletableFuture when making a server call. It’s easy to get started and handle an individual CompletableFuture response. However, it’s not immediately clear how to collect the results of multiple CompletableFuture executions while also handling exceptions.

In this tutorial, we’ll develop a simple mock microservice client that returns a CompletableFuture, and see how to call it multiple times to generate a summary of successes and failures.

2. An Example Microservice Client

For our example, let’s write a simple microservice client that’s responsible for creating a resource and returning that resource’s identifier.

We’ll declare a simple interface, MicroserviceClient, that we can mock out (using Mockito) in our unit test:

interface MicroserviceClient {
    CompletableFuture<Long> createResource(String resourceName);
}

Unit testing CompletableFuture comes with its own challenges, but testing a single call to MicroserviceClient would be straightforward. Rather than detailing that here, let’s move on to handling multiple client calls that can throw an exception.

3. Combining Multiple Calls to Microservice

Let’s start by creating a unit test and declaring a mock of our MicroserviceClient that returns a successful response for an input of “Good Resource” and throws an exception for an input of “Bad Resource“:

@ParameterizedTest
@MethodSource("clientData")
public void givenMicroserviceClient_whenMultipleCreateResource_thenCombineResults(List<String> inputs,
  int expectedSuccess, int expectedFailure) throws ExecutionException, InterruptedException {
    MicroserviceClient mockMicroservice = mock(MicroserviceClient.class);
    when(mockMicroservice.createResource("Good Resource"))
      .thenReturn(CompletableFuture.completedFuture(123L));
    when(mockMicroservice.createResource("Bad Resource"))
      .thenReturn(CompletableFuture.failedFuture(new IllegalArgumentException("Bad Resource")));
}

We’ll make this a parameterized test and pass in varying sets of data with a MethodSource. We’ll need to create a static method to supply our test with a Stream of JUnit Arguments:

private static Stream<Arguments> clientData() {
    return Stream.of(
      Arguments.of(List.of("Good Resource"), 1, 0),
      Arguments.of(List.of("Bad Resource"), 0, 1),
      Arguments.of(List.of("Good Resource", "Bad Resource"), 1, 1),
      Arguments.of(List.of("Good Resource", "Bad Resource", "Good Resource", "Bad Resource", 
        "Good Resource"), 3, 2)
    );
}

This creates four test executions that pass in a List of inputs and the expected count of successes and failures.

Next, let’s return to our unit test and use the test data to call MicroserviceClient and collect each resulting CompletableFuture into a List:

List<CompletableFuture<Long>> clientCalls = new ArrayList<>();
for (String resource : inputs) {
    clientCalls.add(mockMicroservice.createResource(resource));
}

Now, we have the core part of our problem: a List of CompletableFuture objects that we need to complete and collect the results of, while handling any exceptions we encounter.

3.1. Handling Exceptions

Before getting into how we’ll complete each CompletableFuture, let’s define a helper method for handling exceptions. We’ll also define and mock out a Logger to mimic real-world error handling:

private final Logger logger = mock(Logger.class);

private Long handleError(Throwable throwable) {
    logger.error("Encountered error: " + throwable);
    return -1L;
}

interface Logger {
    void error(String message);
}

The helper method simply “logs” the error message and returns -1, which we’re using to designate an invalid resource.

3.2. Completing a CompletableFuture With Exception Handling

Now, we need to complete all of the CompletableFuture and handle any exceptions appropriately. We can do this by leveraging a few tools CompleteableFuture provides us with:

  • exceptionally(): takes a function to execute if the CompletableFuture completes with an exception
  • join(): returns the result of the CompletableFuture once it completes

Then, we can define a helper method for completion of a single CompletableFuture:

private Long handleFuture(CompletableFuture<Long> future) {
    return future
      .exceptionally(this::handleError)
      .join();
}

Notably, we’re using exceptionally() to handle any exceptions that the MicroserviceClient calls could throw via our handleError() helper method. Finally, we’re calling join() on the CompletableFuture to wait for completion of the client call and return its resource identifier.

3.3. Handling a List of CompletableFuture

Returning to our unit test, we can now leverage our helper methods along with Java’s Stream API to create a simple statement that resolves all of the client calls:

Map<Boolean, List<Long>> resultsByValidity = clientCalls.stream()
  .map(this::handleFuture)
  .collect(Collectors.partitioningBy(resourceId -> resourceId != -1L));

Let’s break down this statement:

  • We map each CompletableFuture into the resulting resource identifier using our handleFuture() helper method
  • We use Java’s Collectors.partitioningBy() utility to split the resulting resource identifiers into separate lists based on validity

We can easily verify our test by using an assertion on the size of the partitioned Lists, as well as checking calls to our mocked Logger:

List<Long> validResults = resultsByValidity.getOrDefault(true, List.of());
assertThat(validResults.size()).isEqualTo(successCount);

List<Long> invalidResults = resultsByValidity.getOrDefault(false, List.of());
assertThat(invalidResults.size()).isEqualTo(errorCount);
verify(logger, times(errorCount))
  .error(eq("Encountered error: java.lang.IllegalArgumentException: Bad Resource"));

Running the test, we can see our partitioned lists match what we expect.

4. Conclusion

In this article, we learned how to handle completing a collection of CompletableFuture. If necessary, we could easily extend our approach to use more robust error handling or complex business logic.

The code backing this article is available on GitHub. Once you're logged in as a Baeldung Pro Member, start learning and coding on the project.
Baeldung Pro – NPI EA (cat = Baeldung)
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Baeldung Pro comes with both absolutely No-Ads as well as finally with Dark Mode, for a clean learning experience:

>> Explore a clean Baeldung

Once the early-adopter seats are all used, the price will go up and stay at $33/year.

Partner – Microsoft – NPI EA (cat = Baeldung)
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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, visit the documentation page.

You can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Microsoft – NPI EA (cat = Spring Boot)
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Azure Container Apps is a fully managed serverless container service that enables you to build and deploy modern, cloud-native Java applications and microservices at scale. It offers a simplified developer experience while providing the flexibility and portability of containers.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, visit the documentation page.

You can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Partner – Orkes – NPI EA (cat = Spring)
announcement - icon

Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

Try a 14-Day Free Trial of Orkes Conductor today.

Partner – Orkes – NPI EA (tag = Microservices)
announcement - icon

Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

Try a 14-Day Free Trial of Orkes Conductor today.

eBook – HTTP Client – NPI EA (cat=HTTP Client-Side)
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The Apache HTTP Client is a very robust library, suitable for both simple and advanced use cases when testing HTTP endpoints. Check out our guide covering basic request and response handling, as well as security, cookies, timeouts, and more:

>> Download the eBook

eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.

Get started with understanding multi-threaded applications with our Java Concurrency guide:

>> Download the eBook

eBook – Java Streams – NPI EA (cat=Java Streams)
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Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.

But these can also be overused and fall into some common pitfalls.

To get a better understanding on how Streams work and how to combine them with other language features, check out our guide to Java Streams:

>> Join Pro and download the eBook

eBook – Persistence – NPI EA (cat=Persistence)
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Working on getting your persistence layer right with Spring?

Explore the eBook

Partner – MongoDB – NPI EA (tag=MongoDB)
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Traditional keyword-based search methods rely on exact word matches, often leading to irrelevant results depending on the user's phrasing.

By comparison, using a vector store allows us to represent the data as vector embeddings, based on meaningful relationships. We can then compare the meaning of the user’s query to the stored content, and retrieve more relevant, context-aware results.

Explore how to build an intelligent chatbot using MongoDB Atlas, Langchain4j and Spring Boot:

>> Building an AI Chatbot in Java With Langchain4j and MongoDB Atlas

Course – LS – NPI EA (cat=REST)

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Get started with Spring Boot and with core Spring, through the Learn Spring course:

>> CHECK OUT THE COURSE

eBook – Java Concurrency – NPI (cat=Java Concurrency)
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Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.

Get started with understanding multi-threaded applications with our Java Concurrency guide:

>> Download the eBook

eBook Jackson – NPI EA – 3 (cat = Jackson)