Newman VS bottleneck

I also put the cold starts measured in the part 19 into the tables to see both cold and warm starts in one place. The results of the experiment below were based on reproducing more than 100 cold and approximately 100.000 warm starts for the duration of our experiment which ran for approximately 1 hour. Here is the code for the sample application. 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. Abbreviation c is for the cold start and w is for the warm start.

The results of the experiments to retrieve the existing product from the database with all approaches by its id with Lambda functions 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 functions first.

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.

bottleneck

I tried to use the Bottleneck library to rate limit a script that needs to make a lot of calls to a 3rd party API in Deno. However, to my surprise it just has no effect, even when tested on small toy examples. I didn't try it in Node or the browser. Is there a reason why this library just wouldn't work on the Deno runtime? Is there a good alternative? It's a hard thing to google for because results tend to be either cron or server-side libraries.

If you have trouble with floods of traffic, use a rate limiter. Check out https://www.npmjs.com/package/bottleneck

Perhaps some streaming (native streams or some observables like rxjs) solution combined with rate limiting like https://www.npmjs.com/package/bottleneck ?

In general, you should avoid reinventing the wheel, so we looked for libraries which could solve our problem. We found BottleneckJS and decided to try to use it for our initial prototype.

Between tiny-async-pool and bottleneck I can suck data from any api very efficiently and within rate limits

Ah, this looks really nice! https://www.npmjs.com/package/bottleneck

As we can see here, in order to not violate the rate limiting rule, we must have 5 attempts at the API per minute or wait at lease 200 milliseconds between the executions. This was not that hard, but wait, JavaScript is asynchronous in nature. How will we make it run synchronously and sequentially ? The real question we are actually asking is, how do we make it that the HTTP requests to the remote API will wait the minimum delay time in between the executions. This is where we are going to use the tool that is called BottleNeck.