How to use Go language for code monitoring and performance evaluation practice

How to use Go language for code monitoring and performance evaluation practice

Introduction:
As the complexity of applications continues to increase, how to monitor and evaluate the performance of the code in real time becomes more and more important. As an efficient and highly concurrency programming language, Go language provides a wealth of tools and libraries to facilitate developers to conduct code monitoring and performance evaluation. This article will introduce the practice of using Go language for code monitoring and performance evaluation, and provide some practical code examples.

1. Code monitoring practice

1. Real-time monitoring of the number of goroutines
   In the Go language, goroutine is a lightweight concurrent execution unit. In order to understand the number of goroutines in the application, you can use the Goroutine function in the runtime package to monitor in real time.

package main

import (
    "fmt"
    "runtime"
    "time"
)

func main() {
    go func() {
        for {
            time.Sleep(time.Second)
        }
    }()

    go func() {
        for {
            time.Sleep(time.Second)
        }
    }()

    go func() {
        for {
            time.Sleep(time.Second)
        }
    }()

    go func() {
        for {
            time.Sleep(time.Second)
        }
    }()

    for {
        fmt.Println("Goroutine num:", runtime.NumGoroutine())
        time.Sleep(time.Second)
    }
}

2. Statistical function execution time
   Understanding the execution time of a function is very important for optimizing code. Using the Now and Since functions in the time package, you can easily count function execution times.

package main

import (
    "fmt"
    "time"
)

func foo() {
    time.Sleep(time.Second)
}

func main() {
    start := time.Now()

    foo()

    elapsed := time.Since(start)

    fmt.Println("Elapsed time:", elapsed)
}

3. Monitor memory usage
   Memory leaks are one of the common causes of program performance problems. Use the memory allocation function in the runtime package to monitor the memory usage of the application.

package main

import (
    "fmt"
    "runtime"
    "time"
)

func main() {
    go func() {
        for {
            _ = make([]byte, 10000)
            time.Sleep(time.Second)
        }
    }()

    for {
        var stats runtime.MemStats
        runtime.ReadMemStats(&stats)
        fmt.Println("Memory usage:", stats.HeapAlloc/1024, "KB")
        time.Sleep(time.Second)
    }
}

2. Performance evaluation practice

1. Use pprof for performance analysis
   Go language has a built-in pprof toolkit, which can easily perform CPU, memory and coroutine analysis performance analysis. Below is an example of using pprof for CPU performance analysis.

package main

import (
    "fmt"
    "log"
    "net/http"
    _ "net/http/pprof"
    "time"
)

func foo() {
    time.Sleep(time.Second)
}

func main() {
    go foo()

    http.ListenAndServe(":8080", nil)
}

Access "http://localhost:8080/debug/pprof/profile" in the browser to get the CPU performance analysis report.

2. Use go test for stress testing
   The testing package of Go language provides a simple and easy-to-use stress testing tool that can test the performance and stability of functions or methods. Below is an example of using go test for stress testing.

package main

import (
    "testing"
    "time"
)

func BenchmarkFoo(b *testing.B) {
    for i := 0; i < b.N; i++ {
        foo()
    }
}

func foo() {
    time.Sleep(time.Second)
}

func main() {}

Enter "go test -bench=." in the command line to get the results of the stress test.

Conclusion:
Through the practice of code monitoring and performance evaluation of the Go language, we can understand the running status of the application in real time and identify potential performance issues. Proper use of these tools and techniques can help us better optimize and tune code and improve application performance and stability.

Reference materials:

• Go language official documentation (https://golang.org/doc/)
• "Go Concurrent Programming Practice" by Wang Yafei

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