Can My Laptop Handle One Million Concurrent HTTP Requests Using Go?

Can Your Laptop Handle a Million Concurrent HTTP Requests?

Imagine sending 1,000,000 simultaneous HTTP requests to a REST API service, pushing your computer's limits to maximize concurrency. While tools exist for this task, let's dive into how to do it in Go using goroutines.

package main

import (
    "fmt"
    "net/http"
    "runtime"
    "time"
)

func main() {
    runtime.GOMAXPROCS(runtime.NumCPU()) // Use all available CPU cores
    transport := &http.Transport{}        // Create an HTTP transport

    for i := 0; i <p><strong>But Wait, There's a Problem!</strong></p><p>Running this script results in errors due to file descriptor limits. The system simply can't handle so many simultaneous connections.</p><p><strong>An Improved Solution</strong></p><p>To overcome these limitations, we need to use a more sophisticated approach.</p><p><strong>Using a Dispatcher and Worker Pool</strong></p><p>This solution involves creating a dispatcher goroutine that pushes requests onto a channel. A worker pool of goroutines pulls requests from the channel, processes them, and sends them to a response channel. A consumer goroutine then processes the responses.</p><pre class="brush:php;toolbar:false">// Dispatcher function
func dispatcher(reqChan chan *http.Request, reqs int) {
    defer close(reqChan)
    for i := 0; i <p><strong>Results</strong></p><p>Running this improved script generates impressive results, such as:</p><p></p><blockquote>
<br><p>Connections:    1000000<br><br>Concurrent:     200<br><br>Total size:     15000000 bytes<br><br>Total time:     38m20.3012317s<br><br>Average time:   2.280131ms</p>
<br>
</blockquote><p><strong>Optimizing for Performance</strong></p><p>However, tweaking the number of concurrent requests and total requests will help you push your system's limits and stress-test its capabilities. Remember, this is an extreme test and can rapidly consume system resources.</p>

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