Why Go Is the Language Made for Cloud-Native

Easy to Learn and Use

Go has fewer syntax keywords compared to other languages, making it less difficult to learn and easier to get started with.

Go has only 25 reserved keywords:

break        default      func         interface    select
case         defer        go           map          struct
chan         else         goto         package      switch
const        fallthrough  if           range        type
continue     for          import       return       var

This allows beginners to focus more on how to write more elegant code, rather than focusing on syntactic sugar or writing overly concise or tricky code.

Go was designed to make up for the shortcomings of C++, to eliminate various forms of slowness and bulkiness, and to improve inefficiencies and scalability, making programming more comfortable and convenient. Therefore, Go naturally possesses advantages such as short compilation times, high runtime efficiency, strong stability, powerful compile-time checks, and a complete set of tools for the entire software lifecycle.

The Advantages of Concurrent Programming

Let’s first look at examples of concurrent programming in different languages:

Python

import threading
import time

# Define a simple thread function
def thread_function(name):
    print("Thread {} started".format(name))
    time.sleep(2)
    print("Thread {} ended".format(name))

# Create and start two threads
thread1 = threading.Thread(target=thread_function, args=(1,))
thread2 = threading.Thread(target=thread_function, args=(2,))
thread1.start()
thread2.start()

# Main thread waits for child threads to finish
thread1.join()
thread2.join()

print("Main thread ended")

Java

public class Main {
    // Define a simple thread class
    static class MyThread extends Thread {
        private int id;

        public MyThread(int id) {
            this.id = id;
        }

        @Override
        public void run() {
            System.out.println("Thread " + id + " started");
            try {
                Thread.sleep(2000);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println("Thread " + id + " ended");
        }
    }

    public static void main(String[] args) throws InterruptedException {
        // Create and start two threads
        MyThread thread1 = new MyThread(1);
        MyThread thread2 = new MyThread(2);
        thread1.start();
        thread2.start();

        // Main thread waits for child threads to finish
        thread1.join();
        thread2.join();

        System.out.println("Main thread ended");
    }
}

C++

#include <iostream>
#include <thread>
#include <chrono>

// Define a simple thread function
void thread_function(int id) {
    std::cout << "Thread " << id << " started" << std::endl;
    std::this_thread::sleep_for(std::chrono::seconds(2));
    std::cout << "Thread " << id << " ended" << std::endl;
}

int main() {
    // Create and start two threads
    std::thread thread1(thread_function, 1);
    std::thread thread2(thread_function, 2);

    // Main thread waits for child threads to finish
    thread1.join();
    thread2.join();

    std::cout << "Main thread ended" << std::endl;

    return 0;
}

Compared to Go, concurrent programming in other languages is much more complex. This complexity means it’s easier to make mistakes during programming.

In Go, starting a coroutine only requires the go keyword, and signal passing between different coroutines can be achieved through chan. Writing concurrent code is simple and easy to understand, so naturally, it’s less error-prone.

For example, we can use channels to share data, and use the signal from context.Done to control whether all processes should exit.

func watch(ctx context.Context, event chan string){
     for {
        select {
        case <-ctx.Done():
            return
        case <-event:
            // do something
        }
    }
}

Or, if you need to maintain state regularly using a timer:

func watch(ctx context.Context){
    ticker := time.NewTicker(time.Second * 10)
    for {
        select {
        case <-ctx.Done():
            return
        case <-ticker.C:
            // do something
        }
    }
}

Moreover, in cloud-native scenarios, a lot of processing needs to be done concurrently. For example, when splitting into many microservices, we need to fetch results from different services concurrently. If this were done serially, fast response would be hard to achieve, making concurrent programming particularly important.

Focus on Maintainability

When thousands of developers continuously work for years on massive codebases with tens of millions of lines of code, truly painful problems start to occur.

As the program grows, the compilation time gradually increases, which in turn affects development speed. Therefore, build speed has become one of Go’s major advantages.

A codebase maintained by many people will mix various programming styles.

Over the lifecycle of a codebase, the code is constantly patched, eventually becoming riddled with issues. Technical debt accumulates, and frequent changes to the code can make documentation fall behind, leading to incomplete documentation.

Go has also made efforts in this area. For example, with if-else statements, Go only allows a single style of writing, rather than letting programmers argue about whether to start a new line or not.

In addition, Go provides code formatting tools, so that code written by different people will have a consistent style. Developers only need to focus on understanding the business logic.

The Power of Kubernetes

Kubernetes, the most important container orchestration application in cloud-native, is written in Go. This means that anyone learning cloud-native cannot avoid learning Go. As more people learn Go, naturally more people contribute to its toolchain.

For example, in the microservices framework, go-zero makes starting a new microservice extremely simple. It also provides features such as service registration and discovery, circuit breaking, and log tracing, making it easier for more people to use Go for development.

Widespread Use of Microservices

Due to the surge in Internet users, architectures have shifted from monolithic to distributed microservices. Each microservice communicates with others via protocols to exchange data, and generally, there is little concern over what language is used to implement each individual service. This has laid the foundation for Go’s widespread adoption in cloud-native environments.

There is no need to worry about how complex the existing services are, nor is there a need to rewrite the entire stable service in Go. When adding new features, it’s sufficient to provide APIs in the new service. Others do not care what language is used internally, giving Go fertile ground for growth.

Although Java has become the standard in enterprise development, most microservices do not require such heavy and complex architecture, allowing Go to carve out a place for itself.

Python is irreplaceable in terms of the simplicity of machine learning and algorithm implementation. However, its weak typing makes it unsuitable for multi-person collaboration in enterprise applications, and its concurrency programming is overly complicated, making it difficult to handle scenarios that require large-scale concurrent programming.

Microservices are not dominated by any one language—they consist of many technology stacks. Every language has its own strengths. The key is to implement your ideas with the most suitable technology.

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