How To Call Kubernetes API using Go - Types and Common Machinery

The official Kubernetes Go client comes loaded with high-level abstractions - Clientset, Informers, Cache, Scheme, Discovery, oh my! When I tried to use it without learning the moving parts first, I ran into an overwhelming amount of new concepts. It was an unpleasant experience, but more importantly, it worsened my ability to make informed decisions in the code.

So, I decided to unravel client-go for myself by taking a thorough look at its components.

But where to start? Before dissecting client-go itself, it's probably a good idea to understand its two main dependencies - k8s.io/api and k8s.io/apimachinery modules. It'll simplify the main task, but that's not the only benefit. These two modules were factored out for a reason - they can be used not only by clients but also on the server-side or by any other piece of software dealing with Kubernetes objects.

How to learn Kubernetes API Go client.

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Multiple Containers, Same Port, no Reverse Proxy

Disclaimer: In 2021, there is still a place for simple setups with just one machine serving all traffic. So, no Kubernetes and no cloud load balancers in this post. Just good old Docker and Podman.

Even when you have just one physical or virtual server, it's often a good idea to run multiple instances of your application on it. Luckily, when the application is containerized, it's actually relatively simple. With multiple application containers, you get horizontal scaling and a much-needed redundancy for a very little price. Thus, if there is a sudden need for handling more requests, you can adjust the number of containers accordingly. And if one of the containers dies, there are others to handle its traffic share, so your app isn't a SPOF anymore.

The tricky part here is how to expose such a multi-container application to the clients. Multiple containers mean multiple listening sockets. But most of the time, clients just want to have a single point of entry.

Benefits of exposing multiple Docker containers on the same port

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Exploring Go net/http Package - On How Not To Set Socket Options

Go standard library makes it super easy to start an HTTP server:

package main

import "net/http"

func main() {
    http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
        w.Write([]byte("Hello there!\n"))
    })

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

...or send an HTTP request:

package main

import "net/http"

func main() {
    resp, err := http.Get("http://example.com/")
    body, err := io.ReadAll(resp.Body)
}

In just ~10 lines of code, I can get a server up and running or fetch a real web page! In contrast, creating a basic HTTP server in C would take hundreds of lines, and anything beyond basics would require third-party libraries.

The Go snippets from above are so short because they rely on powerful high-level abstractions of the net and net/http packages. Go pragmatically chooses to optimize for frequently used scenarios, and its standard library hides many internal socket details behind these abstractions, making lots of default choices on the way. And that's very handy, but...

What if I need to fine-tune net/http sockets before initiating the communication? For instance, how can I set some socket options like SO_REUSEPORT or TCP_QUICKACK?

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My Choice of Programming Languages

When I was a kid, I used to spend days tinkering with woodworking tools. I was lucky enough to have a wide set of tools at my disposal. However, there was no one around to give me a hint about what tool to use when. So, I quickly came up with a heuristic: if my fingers and a tool survived an exercise, I've used the right tool; if either the fingers or the tool got damaged, I'd try other tools for the same task until I find the right one. And it worked quite well for me! Since then, I'm an apologist of the idea that every tool is good only for a certain set of tasks.

A programming language is yet another kind of tool. When I became a software developer, I adapted my heuristic to the new reality: if, while solving a task using a certain language, I suffer too much (fingers damage) or I need to hack things more often than not (tool damage), it's a wrong choice of a language.

Since the language is just a tool, my programming toolbox is defined by the tasks I work on the most often. Since 2010, I've worked in many domains, starting from web UI development and ending with writing code for infrastructure components. I find pleasure in being a generalist (jack of all trades), but there is always a pitfall of spreading yourself too thin (master of none). So, for the past few years, I've been trying to limit my sphere of expertise with the server-side, distributed systems, and infrastructure. Hence, the following choice of languages.

Language logos

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Go, HTTP handlers, panic, and deadlocks

Maybe the scenario I'm going to describe is just a silly bug no seasoned Go developer would ever make, but it is what it is.

I'm not an expert in Go but I do write code in this language from time to time. My cumulative number of LOC is probably still below 100 000 but it's definitely not just a few hundred lines of code. Go always looked like a simple language to me. But also it looked safe. Apparently, it's not as simple and safe as I've thought...

Here is a synthetic piece of code illustrating the erroneous logic I stumbled upon recently:

// main.go
package main

import (
    "fmt"
    "sync"
)

func main() {
    mutex := &sync.Mutex{}

    f := func() {
        fmt.Println("In f()")

        defer func() {
            if r := recover(); r != nil {
                fmt.Println("Recovered", r)
            }
        }()

        dogs := []string{"Lucky"}

        mutex.Lock()
        fmt.Println("Last dog's name is", dogs[len(dogs)])
        mutex.Unlock()
    }

    f()

    fmt.Println("About to get a deadlock in main()")
    mutex.Lock()
}

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