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:

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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:

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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

Partner – LambdaTest – NPI (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

1. Overview

Test containers help us spin up containers before running tests and stop them afterward by defining them in our code.

In this tutorial, we’ll take a look at configuring Testcontainers with MongoDB. Next, we’ll see how to create a base integration for our tests. Finally, we’ll learn how to use the library for the data access layer and application integration tests with MongoDB.

2. Configuration

To use Testcontainers with MongoDB in our tests, we need to add the following dependencies to our pom.xml file with test scope:

<dependency>
    <groupId>org.testcontainers</groupId>
    <artifactId>testcontainers</artifactId>
    <version>1.18.3</version>
    <scope>test</scope>
</dependency>
<dependency>
    <groupId>org.testcontainers</groupId>
    <artifactId>junit-jupiter</artifactId>
    <version>1.18.3</version>
    <scope>test</scope>
</dependency>
<dependency>
    <groupId>org.testcontainers</groupId>
    <artifactId>mongodb</artifactId>
    <version>1.18.3</version>
    <scope>test</scope>
</dependency>

We have three dependencies. First is the core dependency that provides the main functionality of Testcontainers, such as starting and stopping containers. The next dependency is the JUnit 5 extension, and the last dependency is the MongoDB module.

We need Docker installed on our machine to run the MongoDB container.

2.1. Creating the Model

Let’s start by creating the entity corresponding to the Product table using the @Document annotation:

@Document(collection = "Product")
public class Product {

    @Id
    private String id;

    private String name;

    private String description;

    private double price;

    // standard constructor, getters, setters
}

2.2. Creating the Repository

Then, we’ll create our ProductRepository class extending from MongoRepository:

@Repository
public interface ProductRepository extends MongoRepository<Product, String> {

    Optional<Product> findByName(String name);
}

2.3. Creating the REST Controller

Finally, let’s expose a REST API by creating a controller to interact with the repository:

@RestController
@RequestMapping("/products")
public class ProductController {

    private final ProductRepository productRepository;

    public ProductController(ProductRepository productRepository) {
        this.productRepository = productRepository;
    }

    @PostMapping
    public String createProduct(@RequestBody Product product) {
        return productRepository.save(product)
          .getId();
  }

    @GetMapping("/{id}")
    public Product getProduct(@PathVariable String id) {
        return productRepository.findById(id)
          .orElseThrow(() -> new RuntimeException("Product not found"));
  }

}

3. Testcontainers MongoDB Integration Base

We’ll create an abstract base class that extends to all classes that need to start and stop the MongoDB container before and after running the tests:

@Testcontainers
@SpringBootTest(classes = MongoDbTestContainersApplication.class)
public abstract class AbstractBaseIntegrationTest {

    @Container
    static MongoDBContainer mongoDBContainer = new MongoDBContainer("mongo:7.0").withExposedPorts(27017);

    @DynamicPropertySource
    static void containersProperties(DynamicPropertyRegistry registry) {
        mongoDBContainer.start();
        registry.add("spring.data.mongodb.host", mongoDBContainer::getHost);
        registry.add("spring.data.mongodb.port", mongoDBContainer::getFirstMappedPort);
    }
}

We added the @Testcontainers annotation to enable Testcontainers support in our tests and the @SpringBootTest annotation to start the Spring Boot application context.

We also defined a MongoDB container field that starts the MongoDB container with the mongo:7.0 Docker image and exposes port 27017. The @Container annotation starts the MongoDB container before running the tests.

3.1. Data Access Layer Integration Tests

Data access layer integration tests the interaction between our application and the database. We’ll create a simple data access layer for a MongoDB database and write integration tests for it.

Let’s create our data access integration test class that extends the AbstractBaseIntegrationTest class:

public class ProductDataLayerAccessIntegrationTest extends AbstractBaseIntegrationTest {

    @Autowired
    private ProductRepository productRepository;

    // ..
    
}

Now, we can write integration tests for our data access layer:

@Test
public void givenProductRepository_whenSaveAndRetrieveProduct_thenOK() {
    Product product = new Product("Milk", "1L Milk", 10);

    Product createdProduct = productRepository.save(product);
    Optional<Product> optionalProduct = productRepository.findById(createdProduct.getId());

    assertThat(optionalProduct.isPresent()).isTrue();

    Product retrievedProduct = optionalProduct.get();
    assertThat(retrievedProduct.getId()).isEqualTo(product.getId());
}
@Test
public void givenProductRepository_whenFindByName_thenOK() {
    Product product = new Product("Apple", "Fruit", 10);

    Product createdProduct = productRepository.save(product);
    Optional<Product> optionalProduct = productRepository.findByName(createdProduct.getName());

    assertThat(optionalProduct.isPresent()).isTrue();

    Product retrievedProduct = optionalProduct.get();
    assertThat(retrievedProduct.getId()).isEqualTo(product.getId());
}

We created two scenarios: the first saves and retrieves a product and the second finds a product by name. Both tests interact with the MongoDB database spun up by Testcontainers.

3.2. Application Integration Tests

Application integration tests are used to test the interaction between different application components. We’ll create a simple application that uses the data access layer we created earlier and write integration tests for it.

Let’s create our application integration test class that extends the AbstractBaseIntegrationTest class:

@AutoConfigureMockMvc
public class ProductIntegrationTest extends AbstractBaseIntegrationTest {

    @Autowired
    private MockMvc mvc;
    private ObjectMapper objectMapper = new ObjectMapper();

    // ..

}

We need the @AutoConfigureMockMvc annotation to enable the MockMvc support in our tests and the MockMvc field to perform HTTP requests to our application.

Now, we can write integration tests for our application:

@Test
public void givenProduct_whenSave_thenGetProduct() throws Exception {
    MvcResult mvcResult = mvc.perform(post("/products").contentType("application/json")
      .content(objectMapper.writeValueAsString(new Product("Banana", "Fruit", 10))))
      .andExpect(status().isOk())
      .andReturn();

    String productId = mvcResult.getResponse()
      .getContentAsString();

    mvc.perform(get("/products/" + productId))
      .andExpect(status().isOk());
}

We developed a test to save a product and then retrieve it using HTTP. This process involves storing the data in a MongoDB database, which Testcontainers initializes.

4. Conclusion

In this article, we learned how to configure Testcontainers with MongoDB and write integration tests for a data access layer and an application that uses MongoDB.

We started with configuring the library with MongoDB to do the setup. Next, we created a base integration test for our tests.

Finally, we wrote data access and application integration tests that use the MongoDB database provisioned by Testcontainers.

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

Partner – MongoDB – NPI (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

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