f1

README

f1

f1 is a flexible load testing framework using the go language for test scenarios. This allows test scenarios to be developed as code, utilising full development principles such as test driven development. Test scenarios with multiple stages and multiple modes are ideally suited to this environment.

At Form3, many of our test scenarios using this framework combine REST API calls with asynchronous notifications from message queues. To achieve this, we need to have a worker pool listening to messages on the queue and distribute them to the appropriate instance of an active test run. We use this with thousands of concurrent test iterations in tests covering millions of iterations and running for multiple days.

Usage

Writing load tests

Test scenarios consist of two stages:

• Setup - represented by ScenarioFn which is called once at the start of a test; this may be useful for generating resources needed for all tests, or subscribing to message queues.
• Run - represented by RunFn which is called for every iteration of the test, often in parallel with multiple goroutines.

Cleanup functions can be provided for both stages: Setup and Run which will be executed in LIFO order. These ScenarioFn and RunFn functions are defined as types in f1:

// ScenarioFn initialises a scenario and returns the iteration function (RunFn) to be invoked for every iteration
// of the tests.
type ScenarioFn func(t *T) RunFn

// RunFn performs a single iteration of the scenario. 't' may be used for asserting
// results or failing the scenario.
type RunFn func(t *T)

Writing tests is simply a case of implementing the types and registering them with f1:

package main

import (
	"fmt"

	"github.com/form3tech-oss/f1/v2/pkg/f1"
	"github.com/form3tech-oss/f1/v2/pkg/f1/testing"
)

func main() {
	// Create a new f1 instance, add all the scenarios and execute the f1 tool.
	// Any scenario that is added here can be executed like: `go run main.go run constant mySuperFastLoadTest`
	f1.New().Add("mySuperFastLoadTest", setupMySuperFastLoadTest).Execute()
}

// Performs any setup steps and returns a function to run on every iteration of the scenario
func setupMySuperFastLoadTest(t *testing.T) testing.RunFn {
	fmt.Println("Setup the scenario")
	
	// Register clean up function which will be invoked at the end of the scenario execution to clean up the setup
	t.Cleanup(func() {
		fmt.Println("Clean up the setup of the scenario")
	})
	
	runFn := func(t *testing.T) {
	    fmt.Println("Run the test")

		// Register clean up function for each test which will be invoked in LIFO order after each iteration 
		t.Cleanup(func() {
			fmt.Println("Clean up the test execution")
		})
	}

	return runFn
}

Running load tests

Once you have written a load test and compiled a binary test runner, you can use the various "trigger modes" that f1 supports. These are available as subcommands to the run command, so try running f1 run --help for more information). The trigger modes currently implemented are as follows:

• constant - applies load at a constant rate (e.g. one request per second, irrespective of request duration).
• staged - applies load at various stages (e.g. one request per second for 10s, then two per second for 10s).
• users - applies load from a pool of users (e.g. requests from two users being sent sequentially - they are as fast or as slow as the requests themselves).
• gaussian - applies load based on a Gaussian distribution (e.g. varies load throughout a given duration with a mean and standard deviation).
• ramp - applies load constantly increasing or decreasing an initial load during a given ramp duration (e.g. from 0/s requests to 100/s requests during 10s).
• file - applies load based on a yaml config file - the file can contain any of the previous load modes (e.g. "config-file-example.yaml").

Output description

Currently, output from running f1 load tests looks like that:

[   1s]  ✔    20  ✘     0 (20/s)   p(50): 16.899154ms,  p(95): 19.1134ms, p(100): 21.435088ms

It provides the following information:

• [ 1s] how long the test has been running for,
• ✔ 20 number of successful iterations,
• ✘ 0 number of failed iterations,
• (20/s) (attempted) rate,
• p(50): 16.899154ms p(95): 19.1134ms p(100): 21.435088ms average time per iteration, for a given percentile.

Design decisions

Why did we decide to write our own load testing tool?

At Form3, we invest a lot of engineering time into load and performance testing of our platform. We initially used k6 to develop and run these tests, but this was problematic for us for a couple of reasons:

1. The tests that k6 executes are written in Javascript - in order to test our platform, we often need to do things not easily done in Javascript (e.g. connect to SQS queues). The tests themselves can get quite complicated, and Javascript is not well suited to testing these sorts of tests.
2. k6 only really supports a single model for applying load - users. This model assumes you have a finite pool of users, repeatedly making requests in sequence. This doesn't really work for us, since the payments industry has a pool of millions of users, each of whom could make a payment at any moment - when they do, they don't wait around for the previous customer to finish!

Enter f1

We started working on f1, because we already had a suite of load test scenarios that we had started writing in Go. k6 interfaced with these by making web requests to a server that actually ran the tests - a bit of a hack.

We wanted to be able to write the tests in Go in a native load testing framework, which also supported our use case of applying load more aggressively (without waiting for requests to finish).

f1 is the result. It supports writing load test scenarios natively in Go, which means you can make your tests as complicated as you like and test them well. It also has a variety of "trigger modes" (see above), which allow load to be applied in the same way as k6, but also in other, more aggressive modes. Writing new trigger modes is easy, so we welcome contributations to expand the list.

Contributions

If you'd like to help improve f1, please fork this repo and raise a PR!