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The Apprentice's Guide to Kubernetes

by Antoine VeuillerMay 27th, 2021

Too Long; Didn't Read

Kubernetes is a powerful orchestrator that will ease deployment and automatically manage your applications on a set of machines. The aim of this article is to explain the most basic system administration concepts. Mastering these concepts will ease your onboardinging on other orchestrators, such as Docker Swarm. Use some of these concepts to deploy a simple web server and showcase the interactions between the different resources. This article mainly focuses on the developer side, but I will leave some resources about cluster administration at the end. It is possible to configure your application deployment through the command line.

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You probably already heard of Kubernetes, a powerful orchestrator that will ease deployment and automatically manage your applications on a set of machines, called a Cluster.

With great power comes great complexity, even in the eyes of Google. Thus, learning Kubernetes is oftentimes considered as cumbersome and complex, namely because of the number of new concepts you have to learn. On the other hand, those very same concepts can be found in other orchestrators. As a result, mastering them will ease your onboarding on other orchestrators, such as Docker Swarm.

The aim of this article is to explain the most used concepts of Kubernetes relying on basic system administration concepts, then use some of these to deploy a simple web server and showcase the interactions between the different resources. Lastly, I will lay out the usual CLI interactions while working with Kubernetes.

This article mainly focuses on the developer side of a Kubernetes cluster, but I will leave some resources about cluster administration at the end.

Terminology and concepts

Architecture

The Kubernetes realm is the cluster, everything needed is contained within this cluster. Inside it, you will find two types of nodes: the Control Plane and the Worker Nodes.

The control plane is a centralized set of processes that manages the cluster resources, load balance, health, and more. A Kubernetes cluster usually has multiple controller nodes for availability and load balancing purposes. As a developer, you will most likely interact through the API gateway for interactions.

The worker node is any kind of host running a local Kubernetes agent Kubelet and a communication process Kube-Proxy. The former handles the operations commanded by the control plane on the local container runtime (e.g. docker), while the latter redirects connectivity to the right pods.

Namespaces

After some time, a Kubernetes cluster may become huge and heavily used.
In order to keep things well organized, Kubernetes created the concept of Namespace. A namespace is basically a virtual cluster inside the actual cluster.

Most of the resources will be contained inside a namespace, thus unaware of resources from other namespaces. Only a few kinds of resources are completely agnostic of namespaces, and they define computational power or storage sources (i.e. Nodes and PersistentVolumes). However, access to those can be limited by namespace using Quotas.

Namespace-aware resources will always be contained in a namespace as Kubernetes creates and uses a namespace named default if nothing is specified.

There is no silver bullet on the way to use namespaces, as it widely depends on your organization and needs. However, we can note some usual namespaces usages:

Divide the cluster by team or project, to avoid naming conflict and help repartition of resources.
Divide the cluster by environment (i.e. dev, staging, prod), to keep a consistent architecture.
Deploy with more granularity (e.g. blue/green deployment), to quickly fall back on an untouched working environment in case of issue.

Further reading:
Namespace Documentation
Manage The Cluster Namespaces

Glossary

Kubernetes did a great work of remaining agnostic of any technology in their design. This means two things: they can handle multiple technologies under the hood and there is a whole new terminology to learn.

Fortunately, these concepts are pretty straightforward and can most of the time be compared to a unit element of classic system infrastructure. The table below will summarize the binding of the most basic concepts. The comparison might not be a hundred per cent accurate but rather here to help understand the need behind each concept.

Further reading:
Official Kubernetes Glossary
Official Concepts Documentation

Definition files

The resources in Kubernetes are created in a declarative fashion, and while it is possible to configure your application deployment through the command line, a good practice is to keep track of the resource definitions in a versioned environment. Sometimes named GitOps, this practice is not only applicable for Kubernetes but widely applied for delivery systems, backed up by the DevOps movement.

To this effect, Kubernetes proposes a YAML representation of the resource declaration, and its structure can be summarized as follow:

Watch out: some resources such as StorageClass do no use a single entry point as described above

Further reading:
Guide on apiVersion
Yaml Specifications

Metadata and labels

The metadata entry is critical while creating any resource as it will enable Kubernetes and yourself to easily identify and select the resource.

In this entry, you will define a

name

and a

namespace

(defaults to

default

), thanks to which the control plane will automatically be able to tell if the file is a new addition to the cluster or the revision of a previously loaded file.

On top of those elements, you can define a

labels

section. It is composed of a set of key-value pairs to narrow down the context and content of your resource. Those labels can later be used in almost any CLI commands through Selectors. As those entries are not used in the core behavior of Kubernetes, you can use any name you want, even if Kubernetes defines some best practices recommendations.

Finally, you can also create an

annotations

section, which is almost identical to

labels

but not used by Kubernetes at all. Those can be used on the applicative side to trigger behaviors or simply add data to ease debugging.

# <metadata> narrows down selection and identify the resource
metadata:
  # The <name> entry is required and used to identify the resource
  name: my-resource
  namespace: my-namespace-or-default
  # <labels> is optional but often needed for resource selection
  labels:
    app: application-name
    category: back
  # <annotations> is optional and not needed for the configuration of Kubernetes
  annotations:
    version: 4.2

Further reading:
Naming and Identification
Labels and Selectors
Annotations

Data-centric configuration files

Those files define key-value mappings that can be used later in other resources. Usually, those resources (i.e. Secrets and ConfigMap) are loaded before anything else, as it is more likely than not that your infrastructure files are dependent on them.

apiVersion: v1
# <kind> defines the resource described in this file
kind: ConfigMap
metadata:
  name: my-config
data:
  # <data> configures data to load
  configuration_key: "configuration_value"
  properties_entry: |
    # Any multiline content is accepted
    multiline_config=true

Infrastructure centric configuration files

Those files define the infrastructure to deploy on the cluster, potentially using content from the data files.

apiVersion: v1
# <kind> defines the resource described in this file
kind: Pod
metadata:
  name: my-web-server
spec:
  # <spec> is a domain specific description of the resource.
  # The specification entries will be very different from one kind to another

Resources definition

In this section, we will take a closer look at the configuration of the most used resources on a Kubernetes application. This is also the occasion to showcase the interactions between resources.

At the end of the section, we will have a running Nginx server and will be able to contact the server from outside the cluster. The following diagram summarizes the intended state:

ConfigMap

ConfigMap is used to hold properties that can be used later in your resources.

apiVersion: v1
kind: ConfigMap
metadata:
  name: simple-web-config
  namespace: default
data:
  configuration_key: "Configuration value"

The configuration defined above can then be selected from another resource definition with the following snippet:

valueFrom:
  configMapKeyRef:
    name: simple-web-config
    key: configuration_key

Note: ConfigMaps are only available in the namespace in which they are defined.

Further reading:
ConfigMap Documentation

Secret

All sensitive data should be put in Secret files (e.g. API keys, passphrases, …). By default, the data is simply held as base64 encoded values without encryption. However, Kubernetes proposes ways of mitigating leakage risks by integrating a Role-Based Access Control or encrypting secrets.

The Secret file defines a

type

key at its root, which can be used to add validation on the keys declared in the

data

entry. By default, the type is set to

Opaque

which does not validate the entries at all.

apiVersion: v1
kind: Secret
metadata:
  name: simple-web-secrets
# Opaque <type> can hold generic secrets, so no validation will be done.
type: Opaque
data:
  # Secrets should be encoded in base64
  secret_configuration_key: "c2VjcmV0IHZhbHVl"

The secret defined above can then be selected from another resource definition with the following snippet:

valueFrom:
  secretKeyRef:
    name: simple-web-secrets
    key: secret_configuration_key

Note: Secrets are only available in the namespace in which they are defined.

Further reading:
Secrets Documentation
Available Secret Types

Pod

A Pod definition file is pretty straightforward but can become pretty big due to the quantity of configuration available. The

name

and

image

fields are the only mandatory ones, but you might commonly use:

```
ports
```
to define the ports to open on both the container and pod.
```
env
```
to define the environment variables to load on the container.
```
args
```
and
```
entrypoint
```
to customize the container startup sequence.

Pods are usually not created as standalone resources on Kubernetes,
as the best practice indicates to use pod as part of a higher-level definition
(e.g. Deployment). In those cases, the Pod file’s content will simply be embedded in the other resource’s file.

apiVersion: v1
kind: Pod
metadata:
  name: my-web-server
spec:
  # <containers> is a list of container definition to embed in the pod
  containers:
    - name: web
      image: nginx
      ports:
        - name: web
          containerPort: 80
          protocol: TCP
      env:
        - name: SOME_CONFIG
          # Create a line "value: <config_entry>" from the ConfigMap data
          valueFrom:
            configMapKeyRef:
              name: simple-web-config
              key: configuration_key
        - name: SOME_SECRET
          # Create a line "value: <config_entry>" from the Secret data
          valueFrom:
            secretKeyRef:
              name: simple-web-secrets
              key: secret_configuration_key

Note: Pods are only available in the namespace in which they are defined.

Further reading:
Pod Documentation
Advanced Pod Configuration
Fields available in Pod <spec> entry
Fields available in Pod <containers> entry

Deployment

The Deployment is generally used as the atomic working unit since it will automatically:

Create a pod definition based on the
```
template
```
entry.
Create a ReplicaSet on pods selected by the
```
selector
```
entry, with the value of
```
replicas
```
as a count of pods that should be running.

The following file requests 3 instances of an Nginx server running at all times. The file may look a bit heavy, but most of it is the Pod definition copied from above.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-web-server-deployment
  namespace: default
  labels:
    app: webserver
spec:
  # <selector> should retrieve the Pod defined below, and possibly more
  selector:
    matchLabels:
      app: webserver
      instance: nginx-ws-deployment
  # <replicas> asks for 3 pods running in parallel at all time
  replicas: 3
  # The content of <template> is a Pod definition file, without <apiVersion> nor <kind>
  template:
    metadata:
      name: my-web-server
      namespace: default
      labels:
        app: webserver
        instance: nginx-ws-deployment
    spec:
      containers:
        - name: web
          image: nginx
          ports:
            - name: web
              containerPort: 80
              protocol: TCP
          env:
            - name: SOME_CONFIG
              # Create a line "value: <config_entry>" from the ConfigMap data
              valueFrom:
                configMapKeyRef:
                  name: simple-web-config
                  key: configuration_key
            - name: SOME_SECRET
              # Create a line "value: <config_entry>" from the Secret data
              valueFrom:
                secretKeyRef:
                  name: simple-web-secrets
                  key: secret_configuration_key

Note: Deployments are only available in the namespace in which they are defined.

Further reading:
Deployment Documentation

Service

A pod might be deleted and recreated at any time. When it occurs the pod’s IP address will change, which could result in a loss of connection if you are directly contacting it. To solve this issue, a Service provides a stable contact point to a set of Pods, while remaining agnostic of their state and configuration.

Usually, Pods are chosen to be part of a Service through a

selector

entry, thus based on its

labels

. A Pod is selected if and only if all the labels in the selector are worn by the pod.

There are three types of services that are acting quite differently, among which you can select using the type entry.

The ClusterIP service is bound to an internal IP from the cluster, hence only internally reachable. This is the type of service created by default and is suitable for binding different applications inside the same cluster.

A NodePort service will bind a port (by default in range 30000 to 32767) on the nodes hosting the selected pods. This enables you to contact the service directly through the node IP. That also means that your service will be as accessible as the virtual or physical machines hosting those pods.

Note: Using NodePort can pose security risks, as it enables a direct connection from outside the cluster.

A LoadBalancer service will automatically create a load balancer instance from the cloud service provider on which the cluster is running. This load balancer is created outside the cluster but will automatically be bound to the nodes hosting the selected pods.

This is an easy way to expose your service but can end up being costly as each service will be managed by a single load balancer.

If you are setting up your own Ingress as we will do here, you may want to use a

ClusterIp

service, as other services are made for specific use cases.

apiVersion: v1
kind: Service
metadata:
  name: simple-web-service-clusterip
spec:
  # ClusterIP is the default service <type>
  type: ClusterIP
  # Select all pods declaring a <label> entry "app: webserver"
  selector:
    app: webserver
  ports:
    - name: http
      protocol: TCP
      # <port> is the port to bind on the service side
      port: 80
      # <targetPort> is the port to bind on the Pod side
      targetPort: 80

Note: Services are defined in a namespace but can be contacted from other namespaces.

Further reading:
Service Documentation
In Depth Service Comparison
Create an External Load Balancer

Ingress

Ingress enables you to publish internal services without necessarily using a load balancer from cloud service providers. You usually need only one ingress per namespace, where you can bind as many routing

rules

and

backends

as you want. A backend will typically be an internally routed ClusterIP service.

Please note that Kubernetes does not handle ingress resources by itself and relies on third-party implementations. As a result, you will have to choose and install an Ingress Controller before using any ingress resource. On the other hand, it makes the ingress resource customizable depending on the needs of your cluster.

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: simple-web-ingress
  annotations:
    nginx.ingress.kubernetes.io/rewrite-target: /
spec:
  rules:
    # Using <host> redirects all request matching the given DNS name to this rule
    - host: "*.minikube.internal"
      http:
        paths:
          - path: /welcome
            pathType: Prefix
            backend:
              service:
                name: simple-web-service-clusterip
                port:
                  number: 80
    # All other requests will be redirected through this rule
    - http:
        paths:
          - path: /
            pathType: Prefix
            backend:
              service:
                name: simple-web-service-clusterip
                port:
                  number: 80

Note: Ingresses are defined in the namespace but may contact services from other namespaces and are publicly accessible outside the cluster.

Further reading:
Ingress Documentation
Available Ingress Controllers
Enable Ingress on Minikube
Nginx Ingress Annotations

CLI Usage

Create and manage resources

This section showcases the basic CLI commands to manipulate resources. As said before, while it is possible to manually manage resources, a better practice is to use files.

# <kind> is the type of resource to create (e.g. deployment, secret, namespace, quota, ...)
$ kubectl create <kind> <name>
$ kubectl edit   <kind> <name>
$ kubectl delete <kind> <name>

# All those commands can be used through a description file.
$ kubectl create -f <resource>.yaml
$ kubectl edit   -f <resource>.yaml
$ kubectl delete -f <resource>.yaml

To ease resources manipulations through files, you can reduce the interactions to the CLI to the two following commands:

# Create and update any resource
$ kubectl apply   -f <resource>.yaml
# Delete any resource
$ kubectl delete  -f <resource>.yaml

Conclusion

During this article, we saw the fundamentals behind deploying and publishing stateless services using Kubernetes. But you can do a lot more complex things with Kubernetes. If you want to learn more about it, I can recommend you to look at these resources:

Read the Kubernetes reference documentation.
Install a sandbox locally with Minikube, and play with it.
Watch the video .
Manually bootstrap a Kubernetes cluster: Kubernetes The Hard Way.

Incidentally, there are multiple subjects I could not deeply talk about in this article and that may be of interest.

On the developer side:

On the cluster administrator side:

Operators
Access control
Secret encryption
Quotas
Network Plugins (e.g. VPP, Weaveworks)

Furthermore, if you are interested in the ecosystem around Kubernetes,
you may want to take a look at the following technologies:

Openshift is wrapping Kubernetes with production-friendly features
Helm is a charts manager for Kubernetes helping improve the re-usability of configuration files.
ArgoCD is keeping your Kubernetes Cluster up to date with your configurations from Git.

Appendix

Resources’ repository

The resources definitions used in this article are available in the following GitHub repository

CLI equivalents — Docker and Kubernetes

Managing containers with Docker and pods with Kubernetes is very similar, as you can see on the following table describing equivalent operations between both technologies.

Thanks to Sarra Habchi, Dimitri Delabroye, and Alexis Geffroy for the reviews

Also published on: https://aveuiller.github.io/kubernetes_apprentice_cookbook.html