wrk VS Hey

> My initial requirement was to send requests with unique parameters. To the best of my knowledge, no tool could do this.

wrk does this with lua. https://github.com/wg/wrk/blob/master/src/wrk.lua

Also even things like the venerable jmeter supported pulling parameters from a csv file.

We used wrk2, a fantastic tool to generate stable load on the server. Wrk2 improves on wrk and adds the ability to generate sustained load at a specific rate (-R parameter).

I am using a tool called wrk to make a bunch of requests to my website, and changing the concurrency of the requests drastically changes the result, with concurrency set to 1, I get 894 requests made in 10 seconds, and when I set concurrency to 10, I get 8549 requests. This linear scaling stops when increasing the concurrency more drastically (18805 requests for 100 and 19814 for 500 concurrency).

Im creating multithreaded async http server for learning purposes and i'm facing problem when benchmarking with wrk. I get socket read errors on every connection:

We use locust at work but I HIGHLY recommend wrk for a very robust yet simple load testing tool.

https://github.com/wg/wrk

And of course, this talk by Gil Tene is fantastic if you're interested in load testing stats https://www.youtube.com/watch?v=lJ8ydIuPFeU

Good morning what tool do you use to test your infra in terms of http load ? A tool that works, I tested : - https://github.com/tsenart/vegeta but it returns 0 errors or a http_net error from Golang - LOIC (Low Orbit Ion Canon) https://github.com/NewEraCracker/LOIC but the requests do not appear in my nginx logs and I feel no slowdown - Apache Jmeter https://jmeter.apache.org/ but I can't drop my infra and I have Java socket closed errors - K6 https://k6.io/ but I can't bring down my infra with - wrk https://github.com/wg/wrk no matter what parameter I put it doesn't make enough requests per second, I put the same parameters as on a tutorial and I don't get the same result...

You could try to just blast it with wrk or bombardier. Can easily get around 50k requests on consumer machine.

Sure, first I did the load testing on the same machine. The same machine ran web servers, php-fpm and ab / wrk programs.

There are http benchmarking tools like wrk [0]. You don't need a ddos service for that.

[0] https://github.com/wg/wrk

The results of the experiment below were based on reproducing approximately 100 cold starts for the duration of our experiment which ran for approximately 1 hour. For it (and all experiments from my previous articles) I used the load test tool hey, but you can use whatever tool you want, like Serverless-artillery or Postman

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.

The results of the experiment below were based on reproducing more than 100 cold and approximately 100.000 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. I ran all these experiments for all 3 scenarios using 2 different compilation options in template.yaml each:

In our experiment we'll re-use the application introduced in part 9 for this. There are basically 2 Lambda functions which both respond to the API Gateway requests and retrieve product by id received from the API Gateway from DynamoDB. One Lambda function GetProductByIdWithPureJava21Lambda can be used with and without SnapStart and the second one GetProductByIdWithPureJava21LambdaAndPriming uses SnapStart and DynamoDB request invocation priming. We'll measure cold and warm starts using the following memory settings in MBs : 256, 512, 768, 1024, 1536 and 2048. I also put the cold starts measured in the part 12 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.

Por último, podemos executar os testes de carga usando hey.

For running our experiments to provoke anomalies we'll use the stress test tool. You can use the tool of your choice (like Gatling, JMeter, Fiddler or Artillery), I personally prefer to use the tool hey as it is easy to use and similar to curl. On Linux this tool can be installed by executing

Hey: is a fast HTTP load testing tool used to test web applications and APIs. It provides a CLI (command-line interface) and supports concurrent requests.

The client and server nodes are CentOS7.9/X86_64. If the HTTP POST requests were sent directly to the server with hey -c 1, there are about 0.2% of cases that may timeout. If the HTTP POST requests were sent through an NGINX proxy on the client node, there are about 20% of cases will timeout. I've confirmed that only one backend node has this problem. All other nodes are 100% succeeded even with higher throughput.

64 concurrent requests isn't a lot. Modern web apps can typically handle much more than that (depending on what the request does, of course). Try it yourself with a load tester like https://github.com/rakyll/hey against a Go HTTP server, for example the one I've built in https://www.golang.dk/articles/go-and-sqlite-in-the-cloud