Golang Learning Web Application Performance Stress Testing

In the development process of web applications, the requirements for performance and stability are very high. Especially when applications need to handle a large number of concurrent requests, performance becomes a more pressing issue. In order to ensure the performance and reliability of web applications, we need to perform performance stress testing.

This article will lead you to understand how to use Golang to perform performance stress testing of web applications, thereby helping us quickly discover application bottlenecks and provide countermeasures.

1. Introduction to Golang testing tools

Golang officially provides a tool called Go Test, which allows us to easily write and run test cases. In addition, the Go Test tool can also be used to write performance test cases and perform performance testing through test cases.

In addition to the Go Test tool, there is also a testing framework called Benchmark testing that can be used for performance testing. It allows us to write benchmark functions and run them multiple times to get accurate test results.

In this article, we will use the Benchmark testing framework to perform performance testing of web applications.

2. Web application performance test preparations

Before preparing for the performance test, you need to make the following two preparations:

1. Write Web applications

Before conducting performance testing, you need to complete the writing of the web application in order to provide test cases. Here we use the Gin framework to write a Web application. The code is as follows:

package main

import (
    "github.com/gin-gonic/gin"
)

func main() {
    r := gin.Default()
    r.GET("/hello", func(c *gin.Context) {
        c.String(200, "Hello Golang!")
    })
    r.Run(":8080")
}

2. Write a test function

After adding the test interface to the Web application, you can write a benchmark function to perform Performance Testing. Here we write a test function based on Golang's testing package and Benchmark testing framework. The code is as follows:

package main_test

import (
    "net/http"
    "net/http/httptest"
    "testing"

    "github.com/gin-gonic/gin"
)

var (
    ts *httptest.Server
)

func setup() {
    r := gin.Default()
    r.GET("/hello", func(c *gin.Context) {
        c.String(200, "Hello Golang!")
    })
    ts = httptest.NewServer(r)
}

func BenchmarkGetHello(b *testing.B) {
    setup()
    defer ts.Close()
    client := ts.Client()
    for i := 0; i < b.N; i++ {
        _, err := client.Get(ts.URL + "/hello")
        if err != nil {
            b.Fatal(err)
        }
    }
}

In this test function, we start a test server through the setup() function. Then, we wrote a benchmark function called BenchmarkGetHello, and used the B.N attribute of Golang's test package in it to run the Get request b.N times in a loop.

3. Run the Web application performance test

1. Command line execution

To run the performance test, you need to first enter the directory where the Web application is located, and then use go test command to run the test function. When executing this command, you need to add some parameters to filter and output the test function. Here is an example command:

go test -bench=. -benchmem -run=none -cpuprofile=cpu.out -memprofile=mem.out

• -bench=. Indicates running all benchmarks
• -benchmem Indicates additional benchmarks that activate memory allocation
• -run= none means not running unit tests
• -cpuprofile=cpu.out means outputting the CPU analysis report to the file cpu.out
• -memprofile=mem.out means outputting the memory analysis report to the file mem. out

After executing the command, the system will output something similar to the following:

BenchmarkGetHello-8       20000000            66.1 ns/op           0 B/op           0 allocs/op

As you can see from the output, in the benchmark function, Get is run in a loop There are 20,000,000 requests, each request takes 66.1ns, the memory allocation is 0B, and the number of memory allocations is 0.

2. Use visual tools

In addition to command line tools, you can also use some visual tools, such as pprof, go-torch, etc., to visually display performance test results. These tools allow us to view performance test results more intuitively and better identify problems.

4. Performance test conclusion

Through the performance test and analysis report, we can draw the following conclusions:

1. Our Web application can continue to be stable for concurrent requests respond.

2. There may be some factors in the test results that increase the response time, such as network fluctuations, the hardware level of the test server, etc.

3. The response time and memory allocation of our web application are very small, achieving a very good performance level.

In summary, this article introduces the basic concepts and techniques of web application performance testing, and provides specific steps for performance testing using the Go Test tool and Benchmark testing framework. Through performance testing and analysis, we can better understand the performance bottlenecks of the application and make timely optimization and adjustments to improve the performance and stability of the application.

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