Tag: springboot

DateTimeFormat Spring Boot example

Spring Example @datetimeformat(pattern = yyyy-mm-dd )

Here is an example of how you might use the @DateTimeFormat annotation in a Spring application:

import org.springframework.format.annotation.DateTimeFormat;

public class Event {
    private String name;
    @DateTimeFormat(pattern = "yyyy-MM-dd")
    private LocalDate date;

    // constructor, getters, and setters...
}

This example creates a class called Event with a name and a date field. The @DateTimeFormat annotation is used to specify that the date field should be formatted as a date in the yyyy-MM-dd format when it is displayed or parsed.

You can use this annotation in combination with Spring’s @Controller and @RequestMapping annotations to specify the format of the date when it is received as a request parameter or when it is included in the model for a view.

For example, you might have a controller method like this:

@PostMapping("/events")
public String createEvent(@ModelAttribute @Valid Event event, BindingResult bindingResult, Model model) {
    if (bindingResult.hasErrors()) {
        return "form";
    }
    // save the event and redirect to the events list
    return "redirect:/events";
}

In this example, the createEvent method handles a POST request to the /events URL and creates a new Event object from the request parameters. The @DateTimeFormat annotation specifies that the date field should be parsed as a date in the yyyy-MM-dd format.

DateTimeFormat Spring Boot example

Here is an example of how you might use the @DateTimeFormat annotation in a Spring Boot application:

import org.springframework.format.annotation.DateTimeFormat;

@Entity
public class Event {
    @Id
    @GeneratedValue(strategy = GenerationType.IDENTITY)
    private Long id;

    private String name;

    @DateTimeFormat(pattern = "yyyy-MM-dd")
    private LocalDate date;

    // constructor, getters, and setters...
}

@DateTimeFormat annotation is used to specify that the date field should be formatted as a date in the yyyy-MM-dd format when it is displayed or parsed.

You can use this annotation in combination with Spring Boot’s @Controller and @RequestMapping annotations to specify the format of the date when it is received as a request parameter or when it is included in the model for a view.

For example, you might have a controller method like this:

@PostMapping("/events")
public String createEvent(@ModelAttribute @Valid Event event, BindingResult bindingResult, Model model) {
    if (bindingResult.hasErrors()) {
        return "form";
    }
    eventRepository.save(event);
    return "redirect:/events";
}

In this example, the createEvent method handles a POST request to the /events URL and creates a new Event object from the request parameters. The @DateTimeFormat annotation specifies that the date field should be parsed as a date in the yyyy-MM-dd format. The eventRepository.save(event) method saves the Event object to the database, and the user is redirected to the /events URL.

@datetimeformat(pattern = “yyyy-mm-dd hh:mm:ss”)

The @DateTimeFormat annotation allows you to specify the format of a date-time field when it is displayed or parsed. In your example, the pattern is specified as “yyyy-mm-dd hh:mm:ss”, which indicates that the date should be formatted as a string with the year, month, and day in the yyyy-mm-dd format and the hour, minute, and second in the hh:mm:ss format.

Here is an example of how you might use the @DateTimeFormat annotation with this pattern:

import org.springframework.format.annotation.DateTimeFormat;

public class Event {
    private String name;
    @DateTimeFormat(pattern = "yyyy-MM-dd HH:mm:ss")
    private LocalDateTime date;

    // constructor, getters, and setters...
}

In this example, the Event class has a name field and a date field, which is annotated with the @DateTimeFormat annotation and the “yyyy-MM-dd HH:mm:ss” pattern. This specifies that the date field should be formatted as a date and time in the yyyy-MM-dd HH:mm:ss format when it is displayed or parsed.

You can use this annotation in combination with Spring’s @Controller and @RequestMapping annotations to specify the format of the date when it is received as a request parameter or when it is included in the model for a view.

For example, you might have a controller method like this:

@PostMapping("/events")
public String createEvent(@ModelAttribute @Valid Event event, BindingResult bindingResult, Model model) {
    if (bindingResult.hasErrors()) {
        return "form";
    }
    // save the event and redirect to the events list
    return "redirect:/events";
}

In this example, the createEvent method handles a POST request to the /events URL and creates a new Event object from the request parameters. The @DateTimeFormat annotation specifies that the date field should be parsed as a date and time in the yyyy-MM-dd HH:mm:ss format.

Spring Boot Date format validation annotation

In Spring Boot, you can use the @DateTimeFormat annotation to specify the format of a date-time field when it is displayed or parsed. For example:

import org.springframework.format.annotation.DateTimeFormat;

@Entity
public class Event {
    @Id
    @GeneratedValue(strategy = GenerationType.IDENTITY)
    private Long id;

    private String name;

    @DateTimeFormat(pattern = "yyyy-MM-dd HH:mm:ss")
    private LocalDateTime date;

    // constructor, getters, and setters...
}

In this example, the Event class has a name field and a date field, which is annotated with the @DateTimeFormat annotation and the “yyyy-MM-dd HH:mm:ss” pattern. This specifies that the date field should be formatted as a date and time in the yyyy-MM-dd HH:mm:ss format when it is displayed or parsed.

You can use this annotation in combination with Spring Boot’s @Controller and @RequestMapping annotations to specify the format of the date when it is received as a request parameter or when it is included in the model for a view.

If you want to validate the format of the date, you can use the @Valid annotation and the BindingResult class to check for errors. For example:

@PostMapping("/events")
public String createEvent(@ModelAttribute @Valid Event event, BindingResult bindingResult, Model model) {
    if (bindingResult.hasErrors()) {
        return "form";
    }
    eventRepository.save(event);
    return "redirect:/events";
}

In this example, the createEvent method handles a POST request to the /events URL and creates a new Event object from the request parameters. The @Valid annotation triggers validation of the Event object, and the bindingResult object holds any validation errors. If there are any errors, the user is shown the form again. If the validation is successful, the eventRepository.save(event) method saves the Event object to the database, and the user is redirected to the /events URL.

Cannot deserialize value of type java util date from String

It sounds like you are trying to deserialize a JSON string that contains a date field into a Java object, and you are getting an error saying “Cannot deserialize value of type java.util.Date from String.” This error occurs when the JSON string contains a date in a format that cannot be parsed into a java.util.Date object.

To fix this error, you will need to make sure that the JSON string contains the date in a format that can be parsed into a java.util.Date object. You can use the @JsonFormat annotation to specify the format of the date when it is serialized and deserialized.

For example, if the JSON string contains the date in the yyyy-MM-dd’T’HH:mm:ss’Z’ format, you can use the following @JsonFormat annotation:

import com.fasterxml.jackson.annotation.JsonFormat;

public class MyClass {
    @JsonFormat(shape = JsonFormat.Shape.STRING, pattern = "yyyy-MM-dd'T'HH:mm:ss'Z'")
    private Date date;
    // other fields and methods...
}

You can also use the @JsonDeserialize and @JsonSerialize annotations to specify custom deserializers and serializers for the date field.

For example:

import com.fasterxml.jackson.databind.annotation.JsonDeserialize;
import com.fasterxml.jackson.databind.annotation.JsonSerialize;

public class MyClass {
    @JsonDeserialize(using = CustomDateDeserializer.class)
    @JsonSerialize(using = CustomDateSerializer.class)
    private Date date;
    // other fields and methods...
}

In this example, the CustomDateDeserializer class is a custom deserializer that knows how to parse the date from the JSON string, and the CustomDateSerializer class is a custom serializer that knows how to format the date as a JSON string.

What is Spring Filter example code

What is Spring Filter API

In the context of the Spring Framework, a filter is a Java object that can be used to intercept requests and responses made by a web application. Filters can be used to perform various tasks, such as modifying request or response headers, adding security checks, or logging requests and responses.

Spring filters are typically implemented as classes that implement the javax.servlet.Filter interface. This interface defines three methods that a filter must implement: init, doFilter, and destroy. The init method is called when the filter is initialized, the doFilter method is called for each request and response that passes through the filter, and the destroy method is called when the filter is taken out of service.

Filters can be configured in the web application’s deployment descriptor (web.xml) or using Java configuration classes. In a Spring application, filters can be configured using the FilterRegistrationBean class.

Filters are useful for tasks that need to be performed on a large number of requests and responses, as they can be easily applied to an entire web application or a specific group of URLs. They can also be used to add functionality to a web application without modifying the application’s existing code.

SpringBoot Filter API example code

Here is an example of how you can create a filter in Spring Boot:

import javax.servlet.Filter;
import javax.servlet.FilterChain;
import javax.servlet.ServletException;
import javax.servlet.ServletRequest;
import javax.servlet.ServletResponse;
import javax.servlet.http.HttpServletRequest;
import java.io.IOException;

public class MyFilter implements Filter {

    @Override
    public void doFilter(ServletRequest request, ServletResponse response, FilterChain chain)
            throws IOException, ServletException {

        HttpServletRequest req = (HttpServletRequest) request;
        String requestURI = req.getRequestURI();
        System.out.println("Request URI: " + requestURI);

        // You can add your own logic here to do something with the request before it is processed by the controller

        // Call the next filter in the chain
        chain.doFilter(request, response);
    }
}

To use this filter, you can either register it in your Spring Boot application by creating a @Bean of type FilterRegistrationBean, or by using the @WebFilter annotation on the filter class.

For example, you can register the filter using FilterRegistrationBean like this:

import org.springframework.boot.web.servlet.FilterRegistrationBean;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

@Configuration
public class MyFilterConfig {

    @Bean
    public FilterRegistrationBean myFilter() {
        FilterRegistrationBean registrationBean = new FilterRegistrationBean<>();
        registrationBean.setFilter(new MyFilter());
        registrationBean.addUrlPatterns("/api/*");
        return registrationBean;
    }
}

Alternatively, you can use the @WebFilter annotation on the filter class like this:

import javax.servlet.annotation.WebFilter;

@WebFilter(urlPatterns = "/api/*")
public class MyFilter implements Filter {
    // implementation as shown above
}

How many built-in Filter in SpringBoot

Spring Boot does not provide any built-in filters. However, it does provide several convenient features for working with filters, such as support for registering filters using FilterRegistrationBean or the @WebFilter annotation, and automatic ordering of filters based on their @Order annotation or the order property of FilterRegistrationBean.

You can create your own filters and register them in your Spring Boot application as needed. For example, you might create a filter to add security checks, modify the request or response, or perform logging.

There are also many third-party libraries that provide useful filters that you can use in your Spring Boot application, such as the Spring Security filter chain for adding security checks to your application.

Use-case to work with Filter in Spring

There are many use cases for using filters in a Spring application. Here are a few examples:

1. Security: You can use filters to add security checks to your application, such as authenticating users or checking for the presence of valid security tokens.

2. Request and response modification: You can use filters to modify the request or response before it is processed by the rest of the application. For example, you might use a filter to add headers to the response, or to transform the request body.

3. Logging: You can use filters to perform logging, such as recording the details of each request and response.

4. Performance monitoring: You can use filters to monitor the performance of your application, such as measuring the time it takes to process each request.

5. Caching: You can use filters to cache the results of certain requests, so that subsequent requests for the same data can be served more quickly.

6. Compression: You can use filters to compress the response body, to reduce the amount of data that needs to be transmitted over the network.

7. Internationalization: You can use filters to handle internationalization, such as selecting the appropriate language or locale based on the user’s preferences.

8. Error handling: You can use filters to handle errors that occur during the processing of a request, such as by returning a custom error page or logging the error details.

9. Redirection: You can use filters to redirect requests to different URLs based on certain conditions, such as the user’s role or the type of request.

Springboot Amazon Map/Reduce Example Code

What is AWS Map/Reduce?

Amazon Elastic MapReduce (EMR) is a web service that makes it easy to process large amounts of data quickly and cost-effectively. It is based on the popular open-source Apache Hadoop and Apache Spark frameworks for data processing and analysis.

With Amazon EMR, you can set up and scale a data processing cluster in the cloud with just a few clicks. You can then use EMR to run a variety of big data processing workloads, including batch processing, streaming data analysis, machine learning, and more.

MapReduce is a programming model that was developed to allow distributed processing of large data sets across a cluster of computers. It consists of two main phases: the “map” phase and the “reduce” phase. In the map phase, the input data is divided into smaller chunks and processed in parallel by the cluster nodes. In the reduce phase, the results from the map phase are combined and aggregated to produce the final output.

Amazon EMR makes it easy to run MapReduce jobs on large amounts of data stored in Amazon S3 or other data stores. You can use EMR to process and analyze data using a variety of tools and frameworks, including Hadoop, Spark, and others.

Example AWS Map/Reduce commandline

Here is an example of how you can use the AWS Command Line Interface (CLI) to submit a MapReduce job to Amazon EMR:

1. First, make sure that you have the AWS CLI installed and configured with your AWS credentials.

2. Next, create an Amazon S3 bucket to store your input data and output results.

3. Upload your input data to the S3 bucket.

4. Use the aws emr create-cluster command to create a new Amazon EMR cluster. For example:

aws emr create-cluster \
  --name "My Cluster" \
  --release-label emr-6.2.0 \
  --applications Name=Hadoop Name=Spark \
  --ec2-attributes KeyName=my-key-pair,InstanceProfile=EMR_EC2_DefaultRole \
  --instance-type m4.large \
  --instance-count 3 \
  --use-default-roles

5. Use the aws emr add-steps command to add a MapReduce job to the cluster. For example:

aws emr add-steps \
  --cluster-id j-1234567890ABCDEF \
  --steps Type=CUSTOM_JAR,Name="My MapReduce Job",ActionOnFailure=CONTINUE,Jar=s3://my-bucket/my-mapreduce-job.jar,Args=["s3://input-bucket/input.txt","s3://output-bucket/output"]

6. Use the aws emr list-steps command to check the status of the job. When the job is complete, the output will be available in the S3 bucket that you specified.

Keep in mind that this is just a basic example, and you can customize the MapReduce job and cluster configuration as needed to fit your specific requirements. You can find more information and examples in the AWS EMR documentation.

Step by step to setup Amazon Elastic Map Reduce EMR

Here is a step-by-step guide to setting up Amazon Elastic MapReduce (EMR) in your AWS account:

1. Sign up for an AWS account if you don’t already have one.

2. Go to the Amazon EMR dashboard in the AWS Management Console.

3. Click the “Create cluster” button.

4. Select the EMR release that you want to use.

5. Choose the instance types and number of instances that you want to use for your cluster.

6. Select the applications that you want to install on the cluster, such as Hadoop, Spark, or others.

7. Choose a name for your cluster and specify the IAM role that will be used to create and manage the cluster.

8. Configure the network and security settings for your cluster.

9. Review the cluster configuration and click the “Create cluster” button to create the cluster.

It may take a few minutes for the cluster to be created and configured. Once the cluster is up and running, you can use it to run MapReduce jobs or other big data processing tasks.

Keep in mind that this is just a basic guide, and you can customize the cluster configuration as needed to fit your specific requirements. You can find more information and examples in the AWS EMR documentation.

Springboot Amazon Map/Reduce Example Code

Sure, here is an example of how you can use Amazon Elastic MapReduce (EMR) with Spring Boot to perform a word count on a set of documents:

1. First, you will need to set up an Amazon Web Services (AWS) account and create an Amazon EMR cluster.

2. Next, you will need to create a Spring Boot application and add the following dependencies to your pom.xml file:


  org.springframework.cloud
  spring-cloud-aws-context
  2.3.0.RELEASE


  org.springframework.cloud
  spring-cloud-aws-elasticmapreduce
  2.3.0.RELEASE

3. In your Spring Boot application, create a configuration class that enables AWS resource injection:

@Configuration
@EnableRdsInstance
@EnableElasticMapReduce
public class AWSConfiguration {
}

4. Create a service class that will submit the MapReduce job to Amazon EMR and handle the results:

@Service
public class WordCountService {
  @Autowired
  private AmazonElasticMapReduce amazonElasticMapReduce;

  public void countWords(List inputLocations, String outputLocation) {
    // Create a new Hadoop Jar step to run the word count example
    HadoopJarStepConfig hadoopJarStep = new HadoopJarStepConfig()
        .withJar("command-runner.jar")
        .withArgs("spark-submit", "--class", "org.apache.spark.examples.JavaWordCount",
            "--master", "yarn", "lib/spark-examples.jar", "s3://input-bucket/input.txt", "s3://output-bucket/output");

    // Create a step to submit the Hadoop Jar step to the EMR cluster
    StepConfig stepConfig = new StepConfig()
        .withName("Word Count")
        .withHadoopJarStep(hadoopJarStep)
        .withActionOnFailure("TERMINATE_JOB_FLOW");

    // Create a new EMR cluster with 1 master and 2 core nodes
    JobFlowInstancesConfig instances = new JobFlowInstancesConfig()
        .withInstanceCount(3)
        .withMasterInstanceType(InstanceType.M4Large.toString())
        .withSlaveInstanceType(InstanceType.M4Large.toString())
        .withHadoopVersion("2.8.5");

    // Create a new EMR cluster with the step and instance configuration
    RunJobFlowRequest request = new RunJobFlowRequest()
        .withName("Word Count")
        .withInstances(instances)
        .withSteps(stepConfig)
        .withLogUri("s3://log-bucket/");

    // Submit the job to the EMR cluster and wait for it to complete
    RunJobFlowResult result = amazonElasticMapReduce.runJobFlow(request);

Amazon S3 and SpringBoot code example

What is Amazon S3?

Amazon S3 (Simple Storage Service) is an object storage service provided by Amazon Web Services (AWS). It allows you to store and retrieve data from anywhere on the web, making it a useful service for storing and accessing large amounts of data.

Objects in Amazon S3 are stored in buckets, which are containers for objects. Objects are stored as binary data, along with metadata that describes the object. The metadata includes information such as the object’s size, content type, and access control information.

Amazon S3 provides a range of storage classes that offer different levels of durability and availability. The storage classes include Standard, Standard-Infrequent Access (Standard-IA), and One Zone-Infrequent Access (One Zone-IA), as well as options for storing data in a specific region or for archival purposes.

Amazon S3 is a highly scalable, reliable, and secure service, making it a popular choice for storing and accessing data in the cloud. It is widely used for storing and serving static assets, such as images and documents, as well as for storing data for backup and disaster recovery purposes.

Aws S3 Commandline example

You can use the AWS command-line interface (CLI) to manage Amazon S3 from the command line.

To install the AWS CLI, follow the instructions in the AWS documentation: https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-install.html.

Once the AWS CLI is installed, you can use it to perform various actions on Amazon S3. Here are a few examples:

1. List buckets
To list all of the buckets in your AWS account, use the aws s3 ls command:

aws s3 ls

This will list the names of all of the buckets in your account.

2. Create a bucket
To create a new bucket in S3, use the aws s3 mb command followed by the name of the bucket:

aws s3 mb s3://my-new-bucket

This will create a new bucket with the given name.

3. Upload an object
To upload an object to S3, use the aws s3 cp command followed by the path to the local file and the destination in S3:

aws s3 cp local/file/path s3://my-bucket/path/to/object/in/s3.txt

This will upload the local file to the specified path in the bucket.

4. Download an object
To download an object from S3, use the aws s3 cp command followed by the path to the object in S3 and the local destination:

aws s3 cp s3://my-bucket/path/to/object/in/s3.txt local/file/path

This will download the object from S3 to the specified local destination.

You can find more information about the AWS CLI and the various actions you can perform with it in the AWS documentation: https://aws.amazon.com/documentation/cli/.

SpringBoot Amazon S3 Put object

To store an object in Amazon S3 using Spring Boot, you can follow these steps:

1. Add the AWS SDK for Java to your project dependencies. You can do this by including the following dependency in your pom.xml file if you are using Maven:


    com.amazonaws
    aws-java-sdk-s3
    1.11.875

2. Create an AmazonS3 client using your AWS access key and secret key. You can find these in the AWS Management Console under “My Security Credentials”.

AWSCredentials credentials = new BasicAWSCredentials(accessKey, secretKey);
AmazonS3 s3Client = AmazonS3ClientBuilder.standard()
                    .withCredentials(new AWSStaticCredentialsProvider(credentials))
                    .withRegion(region)
                    .build();

3. Create an InputStream for the object you want to upload. This can be done using a FileInputStream if you want to upload a file from the local file system, or using any other method that returns an InputStream.

4. Use the putObject method of the AmazonS3 client to store the object in S3.

String bucketName = "my-s3-bucket";
String key = "path/to/object/in/s3.txt";
s3Client.putObject(bucketName, key, inputStream, new ObjectMetadata());

This will store the object with the given key in the specified bucket. The ObjectMetadata parameter allows you to set metadata for the object, such as content type and content encoding.

SpringBoot Amazon S3 Delete Object

To expose a REST API for deleting an object from Amazon S3 using Spring Boot, you can follow these steps:

1. Add the AWS SDK for Java to your project dependencies as described in the previous answer.

2. Create an AmazonS3 client using your AWS access key and secret key, as described in the previous answer.

3. Create a REST controller class with a method that accepts a request to delete an object from S3.

@RestController
public class S3Controller {

    @DeleteMapping("/s3/{bucketName}/{key}")
    public ResponseEntity deleteObject(@PathVariable String bucketName, @PathVariable String key) {
        // Delete object from S3
        s3Client.deleteObject(bucketName, key);
        return ResponseEntity.ok().build();
    }
}

This controller method will handle DELETE requests to the /s3/{bucketName}/{key} endpoint, where {bucketName} and {key} are path variables representing the name of the bucket and the key of the object to delete, respectively. The method will delete the object from S3 and return an HTTP 200 response.

SpringBoot Amazon S3 List Object example

To list the objects in a bucket in Amazon S3 using Spring Boot, you can use the listObjects method of the AmazonS3 client.

1. Add the AWS SDK for Java to your project dependencies as described in the previous answer.

2. Create an AmazonS3 client using your AWS access key and secret key, as described in the previous answer.

3. Use the listObjects method to retrieve a list of objects in the bucket.

String bucketName = "my-s3-bucket";
ObjectListing objectListing = s3Client.listObjects(bucketName);
List objectSummaries = objectListing.getObjectSummaries();
for (S3ObjectSummary objectSummary : objectSummaries) {
    System.out.println("Key: " + objectSummary.getKey());
    System.out.println("Size: " + objectSummary.getSize());
    System.out.println("Last modified: " + objectSummary.getLastModified());
}

This will retrieve a list of S3ObjectSummary objects, which contain information about the objects in the bucket, such as the key, size, and last modified date. You can then iterate through the list and print out the desired information.

You can use the listObjects method to retrieve a list of objects in a bucket, or a list of objects that match a specific prefix or delimiter. You can find more information about the listObjects method and its options in the AWS documentation: https://docs.aws.amazon.com/AmazonS3/latest/dev/ListingObjectKeysUsingJava.html.

You can also expose this functionality as a REST API using a Spring Boot REST controller, as described in the previous answer.

SpringBoot AWS StackLocal example

What is StackLocal

AWS Stack Local is a command-line interface (CLI) tool that allows you to use AWS CloudFormation templates to create and manage local stacks in your development environment. Local stacks provide an easy way to develop and test your cloud applications locally, without the need for an internet connection or for creating actual resources in the cloud.

With AWS Stack Local, you can create and delete stacks, view stack events and resources, and view stack output. You can also use it to validate CloudFormation templates and perform drift detection on stacks.

To use AWS Stack Local, you need to install the AWS CLI and the AWS SAM CLI, and then configure your development environment to use the local endpoints for AWS services. For more information, see the AWS Stack Local documentation.

How to step by step create a StackLocal with Mac commandline

Here are the steps to create a Stack Local environment on your Mac using the command line:

1. Install the AWS CLI:

pip3 install awscli --upgrade --user

2. Install the AWS SAM CLI:

pip3 install aws-sam-cli --upgrade --user

3. Configure your AWS CLI credentials by running the following command and following the prompts:

aws configure

4. Create a directory for your project and navigate to it:

mkdir my-project
cd my-project

5. Initialize a new SAM project by running the following command:

sam init --runtime python3.8

6. This will create a new directory called hello-world with a basic SAM template and some example code. Navigate to the hello-world directory:

cd hello-world

7. Run the following command to create a Stack Local environment:

sam local start-api

8. This will start a local instance of the API Gateway and the Lambda function specified in the SAM template. You can now test the API by sending a request to the local endpoint, which should be displayed in the output of the command.

9. To stop the Stack Local environment, press CTRL+C in the terminal window where the sam local start-api command is running.

That’s it! You should now have a working Stack Local environment on your Mac. You can use the AWS SAM CLI and the AWS CLI to manage and deploy your local stacks. For more information, see the AWS Stack Local documentation.

Aws StackLocal with SNS commandline Example

Here is an example of how you can use AWS Stack Local with the Simple Notification Service (SNS) using the command line on a Mac:

Follow the steps 1-4 from the previous example to install and configure the AWS CLI and the AWS SAM CLI, and create a new directory for your project.

Create a new file called template.yaml in your project directory with the following content:

AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Resources:
  MyTopic:
    Type: AWS::SNS::Topic
  MyFunction:
    Type: AWS::Serverless::Function
    Properties:
      FunctionName: my-function
      Runtime: python3.8
      CodeUri: src/
      Handler: index.lambda_handler
      Events:
        MyEvent:
          Type: SNS
          Properties:
            Topic: !Ref MyTopic

This template creates an SNS topic and a Lambda function that is triggered when a message is published to the topic.

3. Create a file called src/index.py in your project directory with the following content:

def lambda_handler(event, context):
    print(event)

This is a basic Lambda function that simply prints the event data to the console when it is triggered.

4. Run the following command to create a Stack Local environment:

sam local start-api

5. This will start a local instance of the API Gateway and the Lambda function specified in the SAM template. The output of the command will show the local endpoint for the API.

6. In a new terminal window, run the following command to publish a message to the SNS topic:

aws sns publish --topic-arn arn:aws:sns:us-east-1:123456789012:MyTopic --message "Hello, world!"

Replace 123456789012 with your own AWS account ID.

This will trigger the Lambda function and you should see the event data printed to the console in the terminal window where the sam local start-api command is running.

To stop the Stack Local environment, press CTRL+C in the terminal window where the sam local start-api command is running.

Springboot with Aws StackLocal Example

Here is an example of how you can use AWS LocalStack with a Spring Boot application to develop and test your application locally:

1. Install the AWS CLI and the AWS SAM CLI by running the following commands:

pip3 install awscli --upgrade --user
pip3 install aws-sam-cli --upgrade --user

2. Configure your AWS CLI credentials by running the following command and following the prompts:

aws configure

3. Install the LocalStack Docker image by running the following command:

docker pull localstack/localstack

4. Start the LocalStack Docker container by running the following command:

docker run -p 4566-4599:4566-4599 -e SERVICES=s3,dynamodb,sqs localstack/localstack

This will start a LocalStack container with the S3, DynamoDB, and SQS services. You can specify other services by modifying the SERVICES environment variable.

5. In your Spring Boot application, add the following dependency to your pom.xml file:


  com.amazonaws
  aws-java-sdk-localstack
  1.11.823

This will allow you to use the AWS Java SDK with LocalStack.

6. In your application code, use the LocalstackEndpointConfiguration class to specify the local endpoint for the AWS service you want to use. For example, to use the S3 service with LocalStack, you can do the following:

AmazonS3 s3Client = AmazonS3ClientBuilder
  .standard()
  .withEndpointConfiguration(new LocalstackEndpointConfiguration("http://localhost:4566"))
  .build();

7. You can now use the s3Client object to perform operations on the S3 service, such as creating buckets and uploading objects.

Aws StackLocal commandline example

Here are some common AWS Stack Local commands that you can use from the command line:

  • sam local start-api: Start a local instance of the API Gateway and the Lambda functions specified in the SAM template.
  • sam local generate-event apigateway : Generate an event of the specified type (e.g., apigateway:POST) and send it to the local API Gateway.
  • sam local invoke : Invoke the specified Lambda function locally.
  • sam local start-lambda: Start a local instance of the Lambda runtime and run the functions specified in the SAM template.
  • sam local start-function : Start a local instance of the specified Lambda function.
  • sam local validate: Validate the SAM template.
  • sam local package: Package the SAM template and the function code for deployment.
  • sam local deploy: Deploy the packaged template and code to the cloud.

For a complete list of commands and options, see the AWS SAM CLI documentation.