Pros of hey

• Written in Go, making it more portable and easier to install across different platforms
• Supports HTTP/2 out of the box
• Provides a simpler command-line interface, making it more user-friendly for beginners

Cons of hey

• Generally slower performance compared to wrk
• Less customizable and extensible than wrk
• Limited reporting options and metrics compared to wrk's Lua scripting capabilities

Code Comparison

hey:

func (b *Work) Run() {
    b.results = make(chan *result, b.N)
    b.stopCh = make(chan struct{}, b.C)
    b.start = time.Now()
    b.startTimer()
    b.runWorkers()
}

wrk:

static void *thread_main(void *arg) {
    thread *t = arg;
    aeEventLoop *loop = aeCreateEventLoop(10 + cfg.connections);
    thread_start(loop, t);
    aeMain(loop);
    aeDeleteEventLoop(loop);
    return NULL;
}

Both repositories are HTTP benchmarking tools, but they differ in implementation and features. hey is more modern and user-friendly, while wrk offers better performance and customization options. The code snippets show the core functionality of running workers/threads in each tool, highlighting the different languages and approaches used.

Pros of Vegeta

• Supports multiple output formats (JSON, CSV, Histogram)
• Offers more detailed metrics and reporting capabilities
• Can be used as a library in Go programs for custom load testing scenarios

Cons of Vegeta

• Generally slower than wrk for high-concurrency scenarios
• Less efficient for testing very high loads on a single machine
• Requires more setup and configuration for complex test cases

Code Comparison

Vegeta:

rate := vegeta.Rate{Freq: 100, Per: time.Second}
duration := 5 * time.Second
targeter := vegeta.NewStaticTargeter(vegeta.Target{
    Method: "GET",
    URL:    "http://example.com",
})
attacker := vegeta.NewAttacker()

for res := range attacker.Attack(targeter, rate, duration, "Big Bang!") {
    // Process results
}

wrk:

wrk.method = "GET"
wrk.path   = "/"
wrk.headers["Host"] = "example.com"

function request()
    return wrk.format()
end

function response(status, headers, body)
    -- Process response
end

Both tools are powerful load testing solutions, but Vegeta offers more flexibility and detailed reporting, while wrk excels in raw performance for high-concurrency scenarios. Vegeta's Go-based approach allows for easier integration into existing Go codebases, while wrk's Lua scripting provides a lightweight and fast option for simpler load testing needs.

Pros of Locust

• Written in Python, making it more accessible and easier to extend for many developers
• Supports distributed load testing out of the box
• Provides a web-based UI for real-time monitoring and control of tests

Cons of Locust

• Generally slower performance compared to wrk due to Python's overhead
• Requires more setup and configuration for complex scenarios
• Less suitable for extremely high concurrency tests

Code Comparison

wrk example:

wrk.method = "POST"
wrk.body   = '{"foo": "bar"}'
wrk.headers["Content-Type"] = "application/json"

Locust example:

@task
def post_request(self):
    self.client.post("/endpoint", json={"foo": "bar"})

Both tools allow customization of requests, but wrk uses Lua scripting while Locust uses Python. Locust's approach is generally more intuitive for those familiar with Python, while wrk's Lua scripting can be more efficient for high-performance scenarios.

Locust is better suited for complex, distributed load testing scenarios with a user-friendly interface, while wrk excels in raw performance and simplicity for high-concurrency benchmarking.

Pros of wrk2

• Provides accurate latency measurements with coordinated omission compensation
• Offers more detailed statistical output, including percentiles and histograms
• Supports constant throughput load testing, allowing for more precise control over test scenarios

Cons of wrk2

• Generally slower execution compared to wrk due to additional overhead
• May require more system resources for processing and storing detailed statistics
• Less frequently updated and maintained compared to the original wrk project

Code Comparison

wrk:

wrk.method = "POST"
wrk.body   = "foo=bar&baz=quux"
wrk.headers["Content-Type"] = "application/x-www-form-urlencoded"

wrk2:

wrk.method = "POST"
wrk.body   = "foo=bar&baz=quux"
wrk.headers["Content-Type"] = "application/x-www-form-urlencoded"
wrk.headers["X-Custom-Header"] = "wrk2-specific"

The code structure is similar, with wrk2 allowing for additional customization options and headers. Both projects use Lua for scripting, maintaining compatibility in basic usage scenarios.

Pros of Bombardier

• Written in Go, making it more portable and easier to install across different platforms
• Supports HTTP/1.1, TLS, and HTTP/2 protocols
• Provides more detailed statistics and percentiles in the output

Cons of Bombardier

• Generally slower performance compared to wrk, especially for high concurrency scenarios
• Less mature project with fewer contributors and stars on GitHub
• Limited customization options for complex benchmarking scenarios

Code Comparison

wrk:

wrk.method = "POST"
wrk.body   = "foo=bar&baz=quux"
wrk.headers["Content-Type"] = "application/x-www-form-urlencoded"

Bombardier:

bombardier -m POST -b "foo=bar&baz=quux" -H "Content-Type: application/x-www-form-urlencoded" http://example.com

Both tools allow setting HTTP methods, request bodies, and headers. wrk uses a Lua script for configuration, while Bombardier uses command-line flags. wrk's approach offers more flexibility for complex scenarios, but Bombardier's command-line interface is simpler for basic use cases.