serverless-application-model VS Newman

The complete solution with SAM is available here.

There are many options to deploy Serverless Applications in AWS and one of them is SAM, the Serverless Application Model. I chose to use it here, because it doesn't add too many layers of abstraction between what's being deployed and the code we write and our infrastructure is quite simple.

The solution uses AWS SAM with the global configuration for Lambda functions and the public API you can use to access Apache Zeppelin. The stack deployment provides the URL as an output value.

When you combine this with the AWS Serverless Application Model you can also very easily include your dependencies. Or use a compiled language like golang for your Lambda functions. You simply run sam build before you run the aws cloudformation package and aws cloudformation deploy commands. SAM will build the binary and update the template to point to the newly built binary. Package will then upload it to S3 and replace the local reference to the S3 location. Deploy can then create or update the stack or you can use the CloudFormation integration in CodePipeline.

I'm a big fan of using an Infrastructure as Code (IaC) approach for any project. My go to tools for this are the Servlerless Application Model (SAM) and it's associated CLI (SAM CLI). For more official use cases and for cross platform apps I typically use Terraform.

AWS SAM

Kicking off the tour and not starting a war, but I'm going to be using the Serverless Application Model.

The diagram here is super simple. I'm going to write something a little later that shows how this code could fit into a bigger workflow, but for now, I'm keeping it basic. And yes, that's the SAM Squirrel in there.

Interestingly, AWS CDK and SAM are both explicitly mentioned. While CDK broadly addresses Infrastructure as Code, SAM is highlighted for its role in developing serverless data pipelines - a hugely underrated concept.

Naturally, there are several options available to declare your cloud resources. The options with the most popularity are the CDK, AWS CloudFormation, SST, Serverless framework, Terraform, and AWS SAM. There are others, but when talking about Infrastructure as Code (IaC), these are the ones you hear about most often.

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).