initializr VS Newman

The best way, for generating a ready-to-run application in Java you can use the Spring Boot Initializr tool.

curl --location 'https://start.spring.io/starter.zip?type=maven-project&language=java&bootVersion=3.2.2&baseDir=ms-xcoffee&groupId=com.xcoffee&artifactId=ms-xcoffee&name=ms-xcoffee&description=Demo%20project%20for%20Spring%20Boot&packageName=com.xcoffee.ms-xcoffee&packaging=jar&javaVersion=21&dependencies=webflux%2Clombok%2Cvalidation' | tar -xzvf -

In this segment we will create a basic Spring boot app from Spring Initializer. Add the below dependencies:

Add the following MongoDB dependencies in your pom.xml or use spring initializer and select the Spring Data MongoDB dependency:

I created all of these applications using start.spring.io's REST API and HTTPie.

An easy way to create the skeleton project is to visit Spring Initializr, I set the Project to Gradle - Groovy, Language to Java, and add Spring Web dependency. Then it's just to generate the project and unpack it.

Create a new Spring Boot application using the Spring Initializr. You can use the web version or the curl command below. Use the default for most of the options. For the dependencies, select web, and okta. For the build tool, select Gradle.

I will start with a simple example of a cloud function, which is the same as a rest endpoint in the classical spring boot web application. You can create a project from your favorite IDE or from Spring Initliazr.

There are several testing approaches you can take to ascertain the functionality of the auth API. One way would be to automate the testing using unit tests with tools like Jest and Supertest. Alternatively, you can make use of API clients like Postman or the Thunder Client VS Code extension to test the API.

I'm excited to be speaking at POSTCON, where I will dive into the world of real-time data using Zoom's innovative WebSockets. We'll seamlessly test these functionalities with the help of POSTMAN. This session is designed to give you a glimpse into how we at Zoom are enhancing the real-time capabilities of our platform to ensure faster, more reliable communication. During this session, we'll explore the limitations with Webhooks and why WebSockets are becoming a preferable alternative for real-time, bi-directional communication.

The results of the experiment below were based on reproducing more than 100 cold and approximately 100.000 warm starts with Lambda function with 1024 MB memory setting for the duration of 1 hour. For it I used the load test tool hey, but you can use whatever tool you want, like Serverless-artillery or Postman.

Testing Tools: Select suitable automated testing tools, such as OWASP Zap and Postman, for security and functionality testing.

Postman - API platform for easy endpoint testing

The results of the experiment to retrieve the existing product from the database by its id see GetProductByIdViaAuroraServerlessV2DataApiHandler with Lambda function with 1024 MB memory setting were based on reproducing more than 100 cold and approximately 10.000 warm starts with experiment which ran for approximately 1 hour. For it (and experiments from my previous article) I used the load test tool hey, but you can use whatever tool you want, like Serverless-artillery or Postman. We won't enable SnapStart on the Lambda function first.

Use tools like Postman or Insomnia to test the API endpoints and ensure they behave as expected.

Products are available on our Strapi server. We need to be able to send HTTP requests that will allow clients or users to perform CRUD operations on these product resources. Postman will be our tool for making requests to the Strapi REST API.

We will be performing all of the authentication requests manually, however for testing purposes, you might want to use an API testing tool such as Postman or Insomnia.

As you can see in the above diagram, a lambda function is scheduled to be executed periodically by EventBridge. This lambda function retrieves the assets exported from Postman (test collection, environment, and global variables), injects secrets from the secrets manager and executes the tests using the newman npm package, and, in case of failures, updates metrics in CloudWatch and stores test results in the S3 bucket. An alarm is triggered in case the metrics exceed a threshold (in this case, a count of 1).