Elton MinettoIf you develop APIs or microservices, especially in medium to large environments, you probably use Kubernetes.
Kubernetes is a project created by Google in mid-2015 that quickly became the standard for managing container execution. You can host it on your machines or use a solution delivered by one of the big cloud players like AWS, Google, and DigitalOcean.
In this post, I want to talk about another functionality: the possibility of extending it to create new capabilities. Let's start with the essential concepts for understanding this article.
Resources and Controllers
One of the most fundamental concepts is that K8s manage resources. According to official documentation,
A resource is an endpoint in the Kubernetes API that stores a collection of API objects of a specific type; for example, the built-in "pods" resource contains a collection of Pod objects.
K8s manages these resources using another concept: controllers. When we use a k8s feature, we need to define, in a yaml file, what state we expect. For example:
apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx-deployment
spec:
selector:
matchLabels:
app: nginx
replicas: 2 # tells deployment to run 2 pods that match the template
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.14.2
ports:
- containerPort: 80
The information inside the spec key corresponds to the desired state of the resource.
What k8s does is ensure that the current state of the object contained in the cluster is equal to the desired one that was declared. In this case, two Nginx containers, version 1.14.2, are running on port 80. It does this using what is called a control loop:
It checks whether the current state of the resource differs from the desired state, and if so, it executes the Reconcile function of the controller linked to the object. This way, we can define a controller like this:
A controller tracks at least one type of Kubernetes resource. These objects have a spec field that represents the desired state. This resource's controller(s) are responsible for bringing the current state closer to that desired state.
K8s has a series of built-in resources such as Pod, Deployment, Service, and controllers that track the lifecycle of each of them. But in addition to them, we can create our resources through Custom Resource Definitions (CRD). The combination of a CRD and a controller is what we call an operator, and it is what we will explore in this text.
operator-sdk
To illustrate what we can do with an operator, I will create a proof of concept using operator-sdk. According to the official website::
The Operator SDK makes it easy to build Kubernetes-native applications, a process that can require deep, application-specific operational knowledge. This project is a component of the Operator Framework, an open-source toolkit for managing native Kubernetes applications called Operators in a practical, automated, and scalable way.
Creating an operator using Go, Ansible or Helm is possible. In this article, I will use Go.
The first step is to install the SDK CLI on the machine. I used brew, but the other options are in the documentation.
brew install operator-sdk
The next step is to use the CLI to generate the project scaffolding using the commands:
operator-sdk init --domain minetto.dev --repo github.com/eminetto/k8s-operator-talk
operator-sdk create api --version v1alpha1 --kind Application --resource --controller
The first command initializes the project by indicating the domain, information that k8s will use to identify the resource and the repository name used for the Go package name. The second command creates a new Application resource in the alpha1 version and a controller skeleton.
Before we get into the code, it's essential to understand the purpose of the proof of concept. In its native form, getting an application running on K8s requires the developer to understand concepts such as Deployment, Pod, Service, etc. My goal is to reduce this cognitive load to just two resources: a namespace, where the Application will reside within the cluster, and an Application, which will define the desired state of an application. For example, the team only needs to create the following yaml :
apiVersion: v1
kind: Namespace
metadata:
name: application-sample
---
apiVersion: minetto.dev/v1alpha1
kind: Application
metadata:
name: application-sample
namespace: application-sample
spec:
image: nginx:latest
replicas: 2
port: 80
Apply it to the cluster using the command:
kubectl apply -f application.yaml
And the rest will be created by our controller.
The first step is configuring our resource to have fields related to spec. To do this, you must change the api/v1alpha/application_types.go file and add the fields to the struct:
type ApplicationSpec struct {
Image string `json:"image,omitempty"`
Replicas int32 `json:"replicas,omitempty"`
Port int32 `json:"port,omitempty"`
}
Later, we will use this information to generate the files necessary to install the CRD on our cluster. We will also use this structure to create the required resources.
The next step is to create the logic for our controller. operator-sdk made the controllers/application_controller.go file and the ‌Reconcile function signature. This function is called by the control loop each time k8s detects a difference between the current state of the object and the desired state. In the main.go file that the SDK generated, we have the link between the Application resource and our controller, and we don't need to worry about it now. One of the advantages of operator-sdk is that it allows us to focus on the controller logic and abstracts all the massive details necessary for it to work.
The Reconcile function code and auxiliaries are below. I tried to document the most important excerpts:
func (r *ApplicationReconciler) Reconcile(ctx context.Context, req ctrl.Request) (ctrl.Result, error) {
l := log.FromContext(ctx)
var app minettodevv1alpha1.Application
//recupera os detalhes do objeto sendo gerenciado
if err := r.Get(ctx, req.NamespacedName, &app); err != nil {
if apierrors.IsNotFound(err) {
return ctrl.Result{}, nil
}
l.Error(err, "unable to fetch Application")
return ctrl.Result{}, err
}
/*
The finalizer is essential because it tells K8s we need control over object deletion.
After all, how we will create other resources must be excluded together.
Without the finalizer, there is no time for the K8s garbage collector to delete,
and we risk having useless resources in the cluster.
*/
if !controllerutil.ContainsFinalizer(&app, finalizer) {
l.Info("Adding Finalizer")
controllerutil.AddFinalizer(&app, finalizer)
return ctrl.Result{}, r.Update(ctx, &app)
}
if !app.DeletionTimestamp.IsZero() {
l.Info("Application is being deleted")
return r.reconcileDelete(ctx, &app)
}
l.Info("Application is being created")
return r.reconcileCreate(ctx, &app)
}
func (r *ApplicationReconciler) reconcileCreate(ctx context.Context, app *minettodevv1alpha1.Application) (ctrl.Result, error) {
l := log.FromContext(ctx)
l.Info("Creating deployment")
err := r.createOrUpdateDeployment(ctx, app)
if err != nil {
return ctrl.Result{}, err
}
l.Info("Creating service")
err = r.createService(ctx, app)
if err != nil {
return ctrl.Result{}, err
}
return ctrl.Result{}, nil
}
func (r *ApplicationReconciler) createOrUpdateDeployment(ctx context.Context, app *minettodevv1alpha1.Application) error {
var depl appsv1.Deployment
deplName := types.NamespacedName{Name: app.ObjectMeta.Name + "-deployment", Namespace: app.ObjectMeta.Name}
if err := r.Get(ctx, deplName, &depl); err != nil {
if !apierrors.IsNotFound(err) {
return fmt.Errorf("unable to fetch Deployment: %v", err)
}
/*If there is no Deployment, we will create it.
An essential section in the definition is OwnerReferences, as it indicates to k8s that
an Application is creating this resource.
This is how k8s knows that when we remove an Application, it must also remove
all the resources it created.
Another important detail is that we use data from our Application to create the Deployment,
such as image information, port, and replicas.
*/
if apierrors.IsNotFound(err) {
depl = appsv1.Deployment{
ObjectMeta: metav1.ObjectMeta{
Name: app.ObjectMeta.Name + "-deployment",
Namespace: app.ObjectMeta.Name,
Labels: map[string]string{"label": app.ObjectMeta.Name, "app": app.ObjectMeta.Name},
Annotations: map[string]string{"imageregistry": "https://hub.docker.com/"},
OwnerReferences: []metav1.OwnerReference{
{
APIVersion: app.APIVersion,
Kind: app.Kind,
Name: app.Name,
UID: app.UID,
},
},
},
Spec: appsv1.DeploymentSpec{
Replicas: &app.Spec.Replicas,
Selector: &metav1.LabelSelector{
MatchLabels: map[string]string{"label": app.ObjectMeta.Name},
},
Template: v1.PodTemplateSpec{
ObjectMeta: metav1.ObjectMeta{
Labels: map[string]string{"label": app.ObjectMeta.Name, "app": app.ObjectMeta.Name},
},
Spec: v1.PodSpec{
Containers: []v1.Container{
{
Name: app.ObjectMeta.Name + "-container",
Image: app.Spec.Image,
Ports: []v1.ContainerPort{
{
ContainerPort: app.Spec.Port,
},
},
},
},
},
},
},
}
err = r.Create(ctx, &depl)
if err != nil {
return fmt.Errorf("unable to create Deployment: %v", err)
}
return nil
}
}
/*The controller also needs to manage the update because if the dev changes any information
in an existing Application, this must impact other resources.*/
depl.Spec.Replicas = &app.Spec.Replicas
depl.Spec.Template.Spec.Containers[0].Image = app.Spec.Image
depl.Spec.Template.Spec.Containers[0].Ports[0].ContainerPort = app.Spec.Port
err := r.Update(ctx, &depl)
if err != nil {
return fmt.Errorf("unable to update Deployment: %v", err)
}
return nil
}
func (r *ApplicationReconciler) createService(ctx context.Context, app *minettodevv1alpha1.Application) error {
srv := v1.Service{
ObjectMeta: metav1.ObjectMeta{
Name: app.ObjectMeta.Name + "-service",
Namespace: app.ObjectMeta.Name,
Labels: map[string]string{"app": app.ObjectMeta.Name},
OwnerReferences: []metav1.OwnerReference{
{
APIVersion: app.APIVersion,
Kind: app.Kind,
Name: app.Name,
UID: app.UID,
},
},
},
Spec: v1.ServiceSpec{
Type: v1.ServiceTypeNodePort,
ExternalTrafficPolicy: v1.ServiceExternalTrafficPolicyTypeLocal,
Selector: map[string]string{"app": app.ObjectMeta.Name},
Ports: []v1.ServicePort{
{
Name: "http",
Port: app.Spec.Port,
Protocol: v1.ProtocolTCP,
TargetPort: intstr.FromInt(int(app.Spec.Port)),
},
},
},
Status: v1.ServiceStatus{},
}
_, err := controllerutil.CreateOrUpdate(ctx, r.Client, &srv, func() error {
return nil
})
if err != nil {
return fmt.Errorf("unable to create Service: %v", err)
}
return nil
}
func (r *ApplicationReconciler) reconcileDelete(ctx context.Context, app *minettodevv1alpha1.Application) (ctrl.Result, error) {
l := log.FromContext(ctx)
l.Info("removing application")
controllerutil.RemoveFinalizer(app, finalizer)
err := r.Update(ctx, app)
if err != nil {
return ctrl.Result{}, fmt.Errorf("Error removing finalizer %v", err)
}
return ctrl.Result{}, nil
}
To deploy our customized resource and its controller, the SDK provides commands in its Makefile :
make manifests
make docker-build docker-push IMG=registry.hub.docker.com/eminetto/k8s-operator-talk:latest
make deploy IMG=registry.hub.docker.com/eminetto/k8s-operator-talk:latest
The first command generates all the files necessary to create the CRD. The second generates a docker container and pushes it to the indicated repository. The last command installs the generated container on the cluster. Tip: You can automate controller generation and installation in your development environment using Tilt. This project's repository has a Tiltfile that does all this work. To learn more about Tilt, check out my post about the tool.
Now, apply the yaml with the Application definition to the cluster, and the controller will generate the Deployment and Service necessary for the Application to run.
We can check that the controller created the resources with the following commands.
kubectl -n application-sample get applications
NAME AGE
application-sample 18s
kubectl -n application-sample get deployments
NAME READY UP-TO-DATE AVAILABLE AGE
application-sample-deployment 2/2 2 2 41s
kubectl -n application-sample get pods
NAME READY STATUS RESTARTS AGE
application-sample-deployment-65b96554f8-8vv64 1/1 Running 0 56s
application-sample-deployment-65b96554f8-v54gp 1/1 Running 0 56s
kubectl -n application-sample get services
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
application-sample-service NodePort 10.43.63.164 <none> 80:32591/TCP 66s
This post ended up being quite long, so there are other topics that I will leave for a future text, such as the testing part. But I hope I was able to spark interest in this subject. I'm very excited about it and believe it has incredible potential to help create automation that makes the lives of development and operations teams much more effortless.
Originally published at https://eltonminetto.dev on September 8, 2023
