Kubernetes manifests

A Deployment example

apiVersion: apps/v1
kind: Deployment
metadata:
  name: website
  namespace: default
  # labels and annotations here are only for the deployment resource type
  labels:
    app: website
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
    resource_type: deployment
spec:
  # remove if HPA is used
  replicas: 1
  # the deployments must wait X seconds after seeing a Pod become healthy before moving on to updating the next Pod
  minReadySeconds: 10
  progressDeadlineSeconds: 60
  # keep the last X deployments history in case of rollback
  revisionHistoryLimit: 5

  # This is the default deployment strategy in Kubernetes. 
  # It replaces the existing version of pods with a new version, updating pods slowly one by one, without cluster downtime.
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0

# This strategy deploys a new version of an application alongside the existing version. 
# Once the new version is deployed and verified, traffic can be switched to the new version. 
# This can help to avoid downtime, but it requires more infrastructure.
#
#  strategy:
#    type: Recreate

  selector:
    matchLabels:
      # label for the deployment used by the Service to connect to the deployment
      app: website

  template:
    metadata:
      name: website
      # labels and annotations here are only for the pods that are created by the deployment -> replicaset -> pods
      labels:
        app: website
      annotations:
        source_url: "git@gitlab.com:kisphp/example.git"
        resource_type: deployment-pod
    spec:
      restartPolicy: Always

      # Optional
      securityContext:
        runAsUser: 33
        runAsGroup: 33
        runAsNonRoot: true

      # configure entries in /etc/hosts file inside the pod.
      # /etc/hosts file will be a shared volume between the containers of the pod
      hostAliases:
        - ip: "127.0.0.1"
          hostnames:
            - "foo.local"
            - "bar.local"
        - ip: "10.1.2.3"
          hostnames:
            - "foo.remote"
            - "bar.remote"

      # target specific nodes
      nodeSelector:
        type: application

      # this can be added into the default service account and will be applied globally
      imagePullSecrets:
        - name: my-registry-secret

      containers:
        - name: website # container name in pod
          image: nginx:latest # docker image used for this container
          imagePullPolicy: Always # always get the docker image from registry

          ports:
            - containerPort: 80

          env:
            - name: APP_TYPE
              value: application
            - name: APP_SECRET
              valueFrom:
                secretKeyRef:
                  key: APP_SECRET
                  name: db-secrets
            - name: K8S_NODE_NAME
              valueFrom:
                fieldRef:
                  fieldPath: spec.nodeName
            - name: K8S_POD_NAME
              valueFrom:
                fieldRef:
                  fieldPath: metadata.name
            - name: K8S_POD_NAMESPACE
              valueFrom:
                fieldRef:
                  fieldPath: metadata.namespace
            - name: K8S_POD_IP
              valueFrom:
                fieldRef:
                  fieldPath: status.podIP
            - name: K8S_POD_SERVICE_ACCOUNT
              valueFrom:
                fieldRef:
                  fieldPath: spec.serviceAccountName

          envFrom:
            # load environment variables from config map
            - configMapRef:
                name: site-configurations
            # load encoded secret from Secrets manifest
            - secretRef:
                name: site-secrets

          # set resources
          resources:
            requests:
              memory: "64Mi"
              cpu: "10m"
            limits:
              memory: "256Mi"
              cpu: "100m"

          livenessProbe:
            httpGet:
              path: /healthz
              port: 8080
              httpHeaders:
                - name: Custom-Header
                  value: Awesome
            initialDelaySeconds: 3
            periodSeconds: 3
            successThreshold: 1 # always 1

#          livenessProbe:
#            exec:
#              command:
#                - cat
#                - /tmp/healthy
#            initialDelaySeconds: 5
#            periodSeconds: 5

          readinessProbe:
            exec:
              command:
                - cat
                - /tmp/healthy
            initialDelaySeconds: 5
            periodSeconds: 30 # default 10, >= 1
            successThreshold: 1 # defualt 1, can be higher number

#           TCP liveness probe
#          readinessProbe:
#            tcpSocket:
#              port: 8080
#            initialDelaySeconds: 5
#            periodSeconds: 10
#          livenessProbe:
#            tcpSocket:
#              port: 8080
#            initialDelaySeconds: 15
#            periodSeconds: 20

          # Protect slow starting containers with startup probes
          startupProbe:
            httpGet:
              path: /healthz
              port: liveness-port
            failureThreshold: 30
            periodSeconds: 10
            successThreshold: 1 # always 1

          # this is a custom application running inside the cluster to post a slack message when a pod is created or terminated
          lifecycle:
            postStart:
              exec:
                command:
                  - "/bin/bash"
                  - "-c"
                  - 'curl -s -X GET --max-time 60 http://${SERVICE_NAME}.notifications.svc.cluster.local/start/${HOSTNAME}/php >&1; exit 0'
            preStop:
              exec:
                command:
                  - "/bin/bash"
                  - "-c"
                  - 'curl -s -X GET --max-time 60 http://${SERVICE_NAME}.notifications.svc.cluster.local/stop/${HOSTNAME}/php >&1; exit 0'

          volumeMounts:
            # thumbnails volume
            - mountPath: /app/public/thumbs
              name: thumbnails

            # file uploads volume
            - mountPath: /app/uploads
              name: uploads

            # from configmap
            - name: config
              mountPath: "/config"
              readOnly: true

      initContainers:
        - name: update-database
          image: php-container
          envFrom:
            - configMapRef:
                name: db-credentials
          command:
            - "bin/console"
            - "setup:install"
          volumeMounts:
            - mountPath: /opt/test
              name: test
          securityContext:
            privileged: true
            runAsUser: 0 # root user
            runAsGroup: 0 # root group
#            runAsNonRoot: true

      # set volumes per deployment that will be used by containers using volumeMounts
      volumes:
        # define thumbnails directory as empty volume every time
        - name: thumbnails
          emptyDir: {}

        # load uploads directory from PersistentVolumeClaim
        - name: uploads
          persistentVolumeClaim:
            claimName: website-uploads

        - name: test
          persistentVolumeClaim:
            claimName: my-test-volume

        # load from AWS EFS
        - name: efs-data
          nfs:
            server: 1a2b3c4d.efs.eu-central-1.amazonaws.com
            path: /

        # load from configmap
        - name: config-volume
          configMap:
            name: special-config
            # optional
            items:
              - key: SPECIAL_LEVEL
                path: keys

        - name: config
          configMap:
            name: my-app-config
            items:
              - key: "game.properties"
                path: "game.properties"
              - key: "user-interface.properties"
                path: "user-interface.properties"

Explanation:

• apiVersion: Specifies the Kubernetes API version to use (apps/v1 for Deployment).
• kind: Specifies the resource type (Deployment in this case).
• metadata: Contains metadata about the deployment, such as the name.
• spec: Defines the desired state of the deployment.
• replicas: Specifies the desired number of replicas (pods).
• selector: Defines how the deployment selects the pods to manage based on labels.
• template: Specifies the pod template.
  • metadata: Contains labels for the pods.
  • spec: Specifies the pod's configuration, including containers.
  • containers: Lists containers in the pod.
    • name: Specifies the container name.
    • image: Specifies the Docker image to use.

Create object

# create resource(s)
kubectl apply -f ./my-manifest.yaml            

# create from multiple files
kubectl apply -f ./my1.yaml -f ./my2.yaml      

# create resource(s) in all manifest files in dir
kubectl apply -f ./dir                         

# create resource(s) from url
kubectl apply -f https://git.io/vPieo          

# create a running pod for quick tests
kubectl run nginx --image=nginx --restart=Never

# start a single instance of nginx as a deployment
kubectl create deployment nginx --image=nginx  

# create a Job which prints "Hello World"
kubectl create job hello --image=busybox -- echo "Hello World" 

# create a CronJob that prints "Hello World" every minute
kubectl create cronjob hello --image=busybox   --schedule="*/1 * * * *" -- echo "Hello World"

Updating resources

# Rolling update "www" containers of "frontend" deployment, updating the image
kubectl set image deployment/frontend www=image:v2               

# Check the history of deployments including the revision 
kubectl rollout history deployment/frontend                      

# Rollback to the previous deployment
kubectl rollout undo deployment/frontend                         

# Rollback to a specific revision
kubectl rollout undo deployment/frontend --to-revision=2         

# Watch rolling update status of "frontend" deployment until completion
kubectl rollout status -w deployment/frontend                    

# Rolling restart of the "frontend" deployment
kubectl rollout restart deployment/frontend                      

# Replace a pod based on the JSON passed into std
cat pod.json | kubectl replace -f -                              

# Force replace, delete and then re-create the resource. Will cause a service outage.
kubectl replace --force -f ./pod.json

# Create a service for a replicated nginx, which serves on port 80 and connects to the containers on port 8000
kubectl expose rc nginx --port=80 --target-port=8000

# Update a single-container pod's image version (tag) to v4
kubectl get pod mypod -o yaml | sed 's/\(image: myimage\):.*$/\1:v4/' | kubectl replace -f -

# Add a Label
kubectl label pods my-pod new-label=awesome                      

# Add an annotation
kubectl annotate pods my-pod icon-url=http://goo.gl/XXBTWq       

kubectl autoscale deployment foo --min=2 --max=10

Scaling resources

# Scale a replicaset named 'foo' to 3
kubectl scale --replicas=3 rs/foo                                 

# Scale a resource specified in "foo.yaml" to 3
kubectl scale --replicas=3 -f foo.yaml                            

# If the deployment named mysql's current size is 2, scale mysql to 3
kubectl scale --current-replicas=2 --replicas=3 deployment/mysql  

# Scale multiple replication controllers
kubectl scale --replicas=5 rc/foo rc/bar rc/baz                   

Assuming horizontal Pod autoscaling is enabled in your cluster, you can set up an autoscaler for your Deployment and choose the minimum and maximum number of Pods you want to run based on the CPU utilization of your existing Pods.

kubectl autoscale deployment/nginx-deployment --min=10 --max=15 --cpu-percent=80

Deleting resources

# Delete a pod using the type and name specified in pod.json
kubectl delete -f ./pod.json                                      

# Delete a pod with no grace period
kubectl delete pod unwanted --now                                 

# Delete pods and services with same names "baz" and "foo"
kubectl delete pod,service baz foo                                

# Delete pods and services with label name=myLabel
kubectl delete pods,services -l name=myLabel                      

# Delete all pods and services in namespace my-ns,
kubectl -n my-ns delete pod,svc --all                             

# Delete all pods matching the awk pattern1 or pattern2
kubectl get pods  -n mynamespace --no-headers=true | awk '/pattern1|pattern2/{print $1}' | xargs  kubectl delete -n mynamespace pod

Copy files and directories to and from containers

# Copy /tmp/foo_dir local directory to /tmp/bar_dir in a remote pod in the current namespace
kubectl cp /tmp/foo_dir my-pod:/tmp/bar_dir            

# Copy /tmp/foo local file to /tmp/bar in a remote pod in a specific container
kubectl cp /tmp/foo my-pod:/tmp/bar -c my-container    

# Copy /tmp/foo local file to /tmp/bar in a remote pod in namespace my-namespace
kubectl cp /tmp/foo my-namespace/my-pod:/tmp/bar       

# Copy /tmp/foo from a remote pod to /tmp/bar locally
kubectl cp my-namespace/my-pod:/tmp/foo /tmp/bar       

Note: kubectl cp requires that the 'tar' binary is present in your container image. If 'tar' is not present, kubectl cp will fail. For advanced use cases, such as symlinks, wildcard expansion or file mode preservation consider using kubectl exec.

# Copy /tmp/foo local file to /tmp/bar in a remote pod in namespace my-namespace
tar cf - /tmp/foo | kubectl exec -i -n my-namespace my-pod -- tar xf - -C /tmp/bar     

# Copy /tmp/foo from a remote pod to /tmp/bar locally
kubectl exec -n my-namespace my-pod -- tar cf - /tmp/foo | tar xf - -C /tmp/bar        

ClusterIP

apiVersion: v1
kind: Service
metadata:
  name: my-app-cluster-ip
  namespace: default
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
spec:
  type: ClusterIP
  selector:
    app: my_app
  ports:
    - port: 80
      targetPort: 80

NodePort

apiVersion: v1
kind: Service
metadata:
  name: my-app-node-port
  namespace: default
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
spec:
  type: NodePort
  selector:
    app: my_app
  ports:
    - port: 80
      targetPort: 80

LoadBalancer (will not work on minikube)

apiVersion: v1
kind: Service
metadata:
  name: my-app-load-balancer
  namespace: default
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
spec:
  type: LoadBalancer
  selector:
    app: my-app
  ports:
    - port: 80
      targetPort: 80

Headless service for StatefulSet

apiVersion: v1
kind: Service
metadata:
  name: nginx
  namespace: default
  labels:
    app: nginx
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
spec:
  ports:
    - port: 80
      name: web
  clusterIP: None
  selector:
    app: nginx

AWS LoadBalancer with TLS termination and application listen on port 80

apiVersion: v1
kind: Service
metadata:
  name: classic-lb-k8s
  namespace: demo
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
    service.beta.kubernetes.io/aws-load-balancer-ssl-cert: arn:aws:acm:eu-central-1:000000000000:certificate/11aa22bb-a1s2-1q2w-1234-q1w2e3r4t5t6
    service.beta.kubernetes.io/aws-load-balancer-backend-protocol: http
    service.beta.kubernetes.io/aws-load-balancer-ssl-ports: https
#    service.beta.kubernetes.io/aws-load-balancer-access-log-enabled: "true"
#    # Specifies whether access logs are enabled for the load balancer
#    service.beta.kubernetes.io/aws-load-balancer-access-log-emit-interval: "60"
#    # The interval for publishing the access logs. You can specify an interval of either 5 or 60 (minutes).
#    service.beta.kubernetes.io/aws-load-balancer-access-log-s3-bucket-name: "my-bucket"
#    # The name of the Amazon S3 bucket where the access logs are stored
#    service.beta.kubernetes.io/aws-load-balancer-access-log-s3-bucket-prefix: "my-bucket-prefix/prod"
#    # The logical hierarchy you created for your Amazon S3 bucket, for example `my-bucket-prefix/prod`
  labels:
    app: my-awesome-application
spec:
  selector:
    app: my-awesome-application
  type: LoadBalancer
  ports:
    - name: http
      port: 80
      targetPort: 80
      protocol: TCP
    - name: https
      port: 443
      targetPort: 80
      protocol: TCP

External Name

An ExternalName service is a special type of Kubernetes service that does not have selectors or endpoints. Instead, it serves as an alias for an external service. This can be useful for accessing external services from within your Kubernetes cluster without having to modify your application code.

apiVersion: v1
kind: Service
metadata:
  name: database-host
  namespace: default
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
spec:
  type: ExternalName
  externalName: "__RDS_HOST__"

ExternalName services can be useful for a variety of use cases, such as:

• Accessing a database that is running outside your Kubernetes cluster.
• Accessing a load balancer that is managed by a third-party provider.
• Accessing a caching server that is running on a different cloud provider.

If you need to access an external service from within your Kubernetes cluster, I recommend using an ExternalName service. It is a simple and effective way to provide a consistent interface to your external services.

External IPs

apiVersion: v1
kind: Service
metadata:
  name: my-service
  namespace: default
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
spec:
  ports:
    - name: mysql
      protocol: TCP
      port: 3306
      targetPort: 3306
  externalIPs:
    - 10.10.10.10

CLI commands

# Create a service for a replicated nginx, which serves on port 80 and connects to the containers on port 8000
kubectl expose rc nginx --port=80 --target-port=8000

# Create a service of type LoadBalancer
kubectl expose deployment hello-world --type=LoadBalancer --name=my-service

Explanations

The following are some explanations of the key fields in a Kubernetes service manifest:

• apiVersion: The API version of the service resource.
• kind: The kind of Kubernetes resource. In this case, the kind is Service.
• metadata: The metadata for the service, including the name and labels.
• spec: The specification for the service, including the selector, ports, and type.

The following are some explanations of the key fields in the spec section of a Kubernetes service manifest:

• selector: A label selector that is used to match pods to the service.
• ports: A list of ports that the service exposes. For each port, you must specify the protocol, port number, and target port.
• type: The type of service. The default type is ClusterIP. Other types include NodePort and LoadBalancer.

ConfigMap example

apiVersion: v1
kind: ConfigMap
metadata:
  # config map name, will be used by deployments, cronjobs, etc
  name: my-app-config
  namespace: default
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
#immutable: true
data:
  APP_ENV: prod

  MYSQL_HOST: "127.0.0.1"
  MYSQL_USER: mysql_username_here

  UPLOAD_DIRECTORY: /data/uploads

  # file-like keys
  game.properties: |
    enemy.types=aliens,machines,humans
    player.maximum-lives=5

  user-interface.properties: |
    color.good=purple
    color.bad=yellow
    color.textmode=true

You can then use those environment variables into your Pods using the env field in the Pod spec or envFrom. For example, the following Pod spec would inject the databasehost and databaseport environment variables into the container:

apiVersion: v1
kind: Pod
metadata:
  name: my-pod
spec:
  containers:
  - name: my-container
    image: my-image
    env:
    - name: DATABASE_HOST
      valueFrom:
        configMapKeyRef:
          name: my-app-config
          key: MYSQL_HOST
    - name: DATABASE_USER
      valueFrom:
        configMapKeyRef:
          name: my-app-config
          key: MYSQL_USER
    
    # or load all parameters defined in ConfigMap
    envFrom:
      - configMapRef:
          name: my-app-config

CLI examples

Create a configmap interactively

kubectl create configmap my-config --from-literal=my-key=my-value

This is a simple example of an Ingress manifest. It creates an Ingress resource called my-ingress that listens for traffic on the example.com domain. When traffic arrives at example.com, it is routed to the my-service Service on port 80.

apiVersion: networking.k8s.io/v1beta1
kind: Ingress
metadata:
  name: my-ingress
  namespace: default
  annotations:
    kubernetes.io/ingress.class: nginx
spec:
  rules:
  - host: example.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: my-service
            port:
              number: 80

Ingress with multiple paths

This is an example of an Ingress manifest with multiple paths. It creates an Ingress resource called my-ingress that listens for traffic on the example.com domain. When traffic arrives at example.com, it is routed to the my-service Service on port 80. When traffic arrives at example.com/api, it is routed to the my-api-service Service on port 8080.

apiVersion: networking.k8s.io/v1beta1
kind: Ingress
metadata:
  name: my-ingress
  namespace: default
  annotations:
    kubernetes.io/ingress.class: nginx
spec:
  rules:
  - host: example.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: my-service
            port:
              number: 80
      - path: /api/
        pathType: Prefix
        backend:
          service:
            name: my-api-service
            port:
              number: 8080

Ingress with TLS

This is an example of an Ingress manifest with TLS. It creates an Ingress resource called my-ingress that listens for traffic on the example.com domain and terminates TLS connections using the my-tls-secret Secret. When traffic arrives at example.com, it is routed to the my-service Service on port 80.

apiVersion: networking.k8s.io/v1beta1
kind: Ingress
metadata:
  name: my-ingress
  namespace: default
  annotations:
    kubernetes.io/ingress.class: nginx
spec:
  tls:
  - hosts:
    - example.com
    secretName: my-tls-secret
  rules:
  - host: example.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: my-service
            port:
              number: 80

Ingress with authentication

apiVersion: networking.k8s.io/v1beta1
kind: Ingress
metadata:
  name: my-ingress
  namespace: default
  annotations:
    kubernetes.io/ingress.class: nginx
spec:
  auth:
  - name: my-auth
    type: basic
    secretName: my-auth-secret
  rules:
  - host: example.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: my-service
            port:
              number: 80

Here is an example of a CronJob manifest:

apiVersion: batch/v1
kind: CronJob
metadata:
  name: my-cron-job
  namespace: default
  labels:
    app: my-cron-job
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
spec:
  # run every ten minutes
  schedule: "*/10 * * * *"
  # do not allow concurrent jobs
  concurrencyPolicy: Forbid
  # delete successful pods
  successfulJobsHistoryLimit: 0
  # keep last 2 failed pods for debug
  failedJobsHistoryLimit: 2
  startingDeadlineSeconds: 120
  suspend: false
  jobTemplate:
    spec:
      template:
        metadata:
          labels:
            app: my-cron-job
          annotations:
            source_url: "git@gitlab.com:kisphp/example.git"
        spec:
          restartPolicy: Never
          nodeSelector:
            type: cron
          containers:
            # name of the container in pod
            - name: app-cron
              # docker image to load for this container
              image: my-php-container:tag_name
              # always download image from registry
              imagePullPolicy: Always # IfNotPresent
              # define necessary resources for this container
              resources:
                requests:
                  cpu: "1"
                  memory: "256Mi"
                limits:
                  cpu: "1"
                  memory: "1Gi"
              # load all variables defined in config map
              envFrom:
                - configMapRef:
                    name: my-app-config
              env:
                # set inline variable for container
                - name: CONTAINER_PURPOSE
                  value: cron
                # register a secret (password) to env vars from secrets manifests
                - name: MYSQL_PASSWORD
                  valueFrom:
                    secretKeyRef:
                      name: my-app-secrets
                      # reference to variable name in secrets manifest
                      key: my_db_password
              command:
                - vendor/bin/codecept
              args:
                - run
                - "--dry-run"
              volumeMounts:
                - name: project-data
                  mountPath: /stored_data
          volumes:
            # using aws EFS (you must enable the EFS Driver Addon on EKS cluster)
            - name: project-data
              nfs:
                server: 1a2b3c4d.efs.eu-central-1.amazonaws.com
                path: /
            # using PVC
            - name: uploads
              persistentVolumeClaim:
                claimName: uploaded-files

Cron schedule syntax

# ┌───────────── minute (0 - 59)
# │ ┌───────────── hour (0 - 23)
# │ │ ┌───────────── day of the month (1 - 31)
# │ │ │ ┌───────────── month (1 - 12)
# │ │ │ │ ┌───────────── day of the week (0 - 6) (Sunday to Saturday;
# │ │ │ │ │                                   7 is also Sunday on some systems)
# │ │ │ │ │
# │ │ │ │ │
# * * * * *

Create a job from a cronjob.

kubectl create job --from=cronjob/<cronjob-name> <job-name>

You can also use kubectl to scale, suspend, and resume CronJobs.

Here are some examples of how to use these commands:

Create a new CronJob

kubectl create cronjob hello-world --schedule="*/15 * * * *" --image=busybox --command=["echo", "Hello, world!"]

List all CronJobs in the current namespace

kubectl get cronjobs

Display detailed information about a specific CronJob

kubectl describe cronjob hello-world

Delete a CronJob

kubectl delete cronjob hello-world

Watch for new Jobs created by CronJobs

kubectl get jobs --watch

Display the logs for a specific Pod created by a CronJob

kubectl logs hello-world-job-1234567890

Here is an example of a Job in Kubernetes:

apiVersion: batch/v1
kind: Job
metadata:
  name: thumbs-cleanup
  namespace: default
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
spec:
  ttlSecondsAfterFinished: 120 # deleted the finished pod after 2 minutes
  backoffLimit: 6 # default value
  parallelism: 2
  completions: 3
  template:
    spec:
      restartPolicy: Never
      containers:
        - name: php
          image: my-custom-container
          imagePullPolicy: Always
          command:
            - vendor/bin/console
            - cleanup:thumbs
          envFrom:
            - configMapRef:
                name: my-config
          env:
            - name: CONTAINER_PURPOSE
              value: job
            - name: MY_DB_PASSWORD
              valueFrom:
                secretKeyRef:
                  name: mysql-password
                  key: password
          volumeMounts:
            - name: my-volume
              mountPath: /mnt/my-volume
      volumes:
        - name: my-volume
          persistentVolumeClaim:
            claimName: my-pvc

• parallelism: This parameter specifies how many Pods can run concurrently. In this case, the Job will create two Pods.
• completions: This parameter specifies the minimum number of Pods that must complete successfully before the Job is marked as successful. In this case, the Job will not be marked as successful until all three Pods have completed.
• ttlSecondsAfterFinished: This parameter specifies the number of seconds after a Pod completes before it is deleted. In this case, the Pods created by this Job will be deleted 120 seconds after they complete.

Here is a simple PersistentVolume manifest:

apiVersion: v1
kind: PersistentVolume
metadata:
  name: uploaded-files
  # PVs don't have a namespace
  labels:
    type: local
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
spec:
  storageClassName: manual
  capacity:
    storage: 10Gi
  accessModes:
    - ReadWriteMany
  hostPath:
    path: /mnt/data/uploaded_files

This manifest creates a PersistentVolume with the following properties:

• Name: uploaded-files
• Capacity: 10Gi
• Access modes: ReadWriteMany, can also be ReadWriteOnce
• PersistentVolumeSource: HostPath
• Path: /mnt/data/uploaded_files

Explanations

• A PersistentVolume (PV) is a piece of storage that Kubernetes can provision for your application. PVs can be backed by a variety of storage providers, such as local disks, cloud storage, and network storage.
• A PersistentVolumeClaim (PVC) is a request for storage from an application. PVCs specify the access modes and capacity of the storage that the application needs.
• Kubernetes will bind a PVC to a PV if the PV meets the requirements of the PVC.

When to use PersistentVolumes

You should use PersistentVolumes if your application needs to store data that persists across restarts. For example, you might use Persistence Volumes for a database, a web application that needs to store user files, or a caching layer.

PersistentVolumes are a powerful way to provision storage for your Kubernetes applications. By understanding how PVs work, you can choose the right storage provider for your needs and ensure that your applications have the storage they need to run reliably.

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: my-app-uploads
  namespace: default
  annotations:
    source_url: "git@gitlab.com:kisphp/example.git"
spec:
  storageClassName: manual
  accessModes:
    - ReadWriteMany
    - ReadWriteOnce
  # Optional
  selector:
    matchLabels:
      node-type: storage
  resources:
    requests:
      storage: 10Gi
# if you define PVC for AWS EFS, just set the storage to 1Gi, no matter how big the EFS is

This PVC requests a 1Gi volume with ReadWriteOnce access mode. The Kubernetes controller will try to find a PersistentVolume (PV) that matches these criteria and bind it to the PVC. If no matching PV is found, the controller will provision a new PV based on the storage class specified in the PVC (or the default storage class if none is specified).

Example 1

This HorizontalPodAutoscaler (HPA) will scale the Deployment my-deployment to a minimum of 1 replica and a maximum of 10 replicas based on the average CPU utilization of the pods in the deployment. When the average CPU utilization is above 80%, the HPA will scale up the deployment by one replica. When the average CPU utilization is below 80%, the HPA will scale down the deployment by one replica.

apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
  name: my-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: my-deployment
  minReplicas: 1
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      targetAverageUtilization: 80

Example 2

This HPA will scale the Deployment my-deployment to a minimum of 1 replica and a maximum of 10 replicas based on the number of pods in the deployment. When the number of pods is less than 2, the HPA will scale up the deployment by one replica. When the number of pods is more than 5, the HPA will scale down the deployment by one replica.

apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
  name: my-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: my-deployment
  minReplicas: 1
  maxReplicas: 10
  metrics:
  - type: Pods
    pods:
      minPods: 2
      maxPods: 5

Example 3

This HPA will scale the Deployment my-deployment to a minimum of 1 replica and a maximum of 10 replicas based on the value of the external metric my-metric with the label app: my-app. When the value of the metric is above a certain threshold, the HPA will scale up the deployment. When the value of the metric is below the threshold, the HPA will scale down the deployment.

apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
  name: my-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: my-deployment
  minReplicas: 1
  maxReplicas: 10
  metrics:
  - type: External
    external:
      metricName: my-metric
      metricSelector:
        matchLabels:
          app: my-app

Create HPA from the CLI

kubectl autoscale deployment php-apache --cpu-percent=50 --min=1 --max=10

Explanations:

• apiVersion: The API version of the HorizontalPodAutoscaler resource.
• kind: The kind of Kubernetes resource.
• metadata: The metadata for the HorizontalPodAutoscaler resource.
• spec: The specification for the HorizontalPodAutoscaler resource.
• scaleTargetRef: A reference to the Kubernetes resource that the HorizontalPodAutoscaler will scale.
• minReplicas: The minimum number of replicas that the HorizontalPodAutoscaler will maintain.
• maxReplicas: The maximum number of replicas that the HorizontalPodAutoscaler will maintain.
• metrics: A list of metrics that the HorizontalPodAutoscaler will use to scale the Kubernetes resource.
• type: The type of metric.
• resource: The resource metric.
• name: The name of the resource metric.
• targetAverageUtilization: The target average utilization of the resource metric.
• pods: The pod metric.
• minPods: The minimum number of pods in the deployment.
• maxPods: The maximum number of pods in the deployment.
• external: The external metric.
• metricName: The name of the external metric.
• metricSelector: A selector for the external metric.
• matchLabels: A map of labels that the external metric must match.

HorizontalPodAutoscalers are a powerful tool for managing the scale of your Kubernetes applications. By using HPAs, you can ensure that your applications have the resources they need to handle changes in demand.

Example 1: Simple PDB for a Deployment

This PDB ensures that at most one Pod of the frontend Deployment is disrupted at a time:

apiVersion: policy/v1beta1
kind: PodDisruptionBudget
metadata:
  name: frontend-pdb
spec:
  minAvailable: 2
  selector:
    matchLabels:
      app: frontend

The minAvailable field specifies that at least two Pods must be available at all times. If Kubernetes needs to disrupt a Pod, it will wait until at least two Pods are available before doing so.

Example 2: PDB with MaxUnavailable for a StatefulSet

This PDB ensures that at most 50% of the Pods of the database StatefulSet are disrupted at a time:

apiVersion: policy/v1beta1
kind: PodDisruptionBudget
metadata:
  name: database-pdb
spec:
  maxUnavailable: 50%
  selector:
    matchLabels:
      app: database

The maxUnavailable field specifies that at most 50% of the Pods can be unavailable at any given time. This is useful for StatefulSets, where the order in which Pods are deployed and terminated is important.

Example 3: PDB with MaxSurge for a DaemonSet

This PDB ensures that at most 10% of the Pods of the logging DaemonSet are unavailable at a time:

apiVersion: policy/v1beta1
kind: PodDisruptionBudget
metadata:
  name: logging-pdb
spec:
  maxSurge: 10%
  selector:
    matchLabels:
      app: logging

With the paused field set to true, Kubernetes will not prevent any Pods of the web Deployment from being disrupted. This can be useful if you need to perform maintenance on the application or if you are confident that the application can handle disruptions.

Example 5: PDB with Custom Label Selector

This PDB ensures that at least one Pod of any Deployment with the label environment: production is available at all times:

apiVersion: policy/v1beta1
kind: PodDisruptionBudget
metadata:
  name: production-pdb
spec:
  minAvailable: 1
  selector:
    matchLabels:
      environment: production

The selector field can be used to select Pods based on any label selector. This allows you to create PDBs for specific applications, environments, or even individual Pods.

Get pod disruption budgets list

kubectl get poddisruptionbudgets

Conclusion

PDBs are a powerful tool for ensuring the availability of your Kubernetes applications. By using PDBs, you can prevent Kubernetes from disrupting your Pods unexpectedly.

This StatefulSet will create three Pods, each running a ZooKeeper server container. The Pods will be named my-zookeeper-cluster-0, my-zookeeper-cluster-1, and my-zookeeper-cluster-2. The volumeMounts section of the spec tells the Pods to mount the PersistentVolumeClaim my-zookeeper-cluster-pvc to the /zookeeper/data directory. This will ensure that the ZooKeeper data is persistent and stored across restarts.

When you update the StatefulSet you are not allowed to change the following parameters: replicas, ordinals, template, updateStrategy, persistentVolumeClaimRetentionPolicy and minReadySeconds

apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: my-zookeeper-cluster
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-zookeeper-cluster
  template:
    metadata:
      labels:
        app: my-zookeeper-cluster
    spec:
      containers:
      - name: my-zookeeper
        image: bitnami/zookeeper:latest
        ports:
        - containerPort: 2181
        volumeMounts:
        - name: zookeeper-data
          mountPath: /zookeeper/data
      volumes:
      - name: zookeeper-data
        persistentVolumeClaim:
          claimName: my-zookeeper-cluster-pvc

Explanations

• replicas: The number of Pods that the StatefulSet will create.
• selector: A label selector that identifies the Pods that the StatefulSet will manage.
• template: A Pod template that is used to create the Pods that the StatefulSet will manage. The template must include a volumeMounts section if the Pods need to access persistent storage.
• volumeMounts: A list of volume mounts that tell the Pods to mount PersistentVolumeClaims to specific directories.
• volumes: A list of volumes that are used by the Pods in the StatefulSet. The volumes must be PersistentVolumeClaims.
• StatefulSets are a powerful tool for managing stateful applications in Kubernetes. By using StatefulSets, you can ensure that your applications are highly available and that their data is persistent.

Using StatefulSets

StatefulSets are valuable for applications that require one or more of the following.

• Stable, unique network identifiers.
• Stable, persistent storage.
• Ordered, graceful deployment and scaling.
• Ordered, automated rolling updates.

In the above, stable is synonymous with persistence across Pod (re)scheduling. If an application doesn't require any stable identifiers or ordered deployment, deletion, or scaling, you should deploy your application using a workload object that provides a set of stateless replicas. Deployment or ReplicaSet may be better suited to your stateless needs.

Limitations

• The storage for a given Pod must either be provisioned by a PersistentVolume Provisioner based on the requested storage class, or pre-provisioned by an admin.
• Deleting and/or scaling a StatefulSet down will not delete the volumes associated with the StatefulSet. This is done to ensure data safety, which is generally more valuable than an automatic purge of all related StatefulSet resources.
• StatefulSets currently require a Headless Service to be responsible for the network identity of the Pods. You are responsible for creating this Service.
• StatefulSets do not provide any guarantees on the termination of pods when a StatefulSet is deleted. To achieve ordered and graceful termination of the pods in the StatefulSet, it is possible to scale the StatefulSet down to 0 prior to deletion.
• When using Rolling Updates with the default Pod Management Policy (OrderedReady), it's possible to get into a broken state that requires manual intervention to repair.

What applications are recommended to run as StatefulSets ?

• Databases (MySQL, PostgreSQL, Oracle, etc.)
• Messaging systems (Kafka, RabbitMQ, etc.)
• Caching systems (Redis, Memcached, etc.)
• Big data platforms (Hadoop, Spark, etc.)
• Distributed systems (ZooKeeper, Kubernetes, etc.)
• Any application that requires persistent storage or a stable, unique network identity

StatefulSets are a good choice for running these applications because they provide the following benefits:

• Guaranteed ordering: StatefulSets ensure that the Pods are created and started in a specific order. This is important for applications that require a specific startup sequence, such as a database cluster.
• Persistent storage: StatefulSets can mount PersistentVolumeClaims to the Pods. This ensures that the application data is persistent and stored across restarts.
• Stable network identities: StatefulSets assign each Pod a unique network identity. This is important for applications that require a stable network identity, such as a load balancer.
• Rolling updates: StatefulSets can perform rolling updates to the Pods. This ensures that the application is always available during updates.

If you are running a stateful application in Kubernetes, I recommend using a StatefulSet to manage it. StatefulSets provide the features and functionality that you need to run stateful applications reliably and efficiently.

apiVersion: v1
kind: ServiceAccount
metadata:
  name: default # this is the default service account
  namespace: default # deployed on default namespace. Must be deployed on all namespaces where you deploy your apps
imagePullSecrets:
  - name: gcp-registry-ro
---
# This manifest creates a service account named `my-service-account`
# with the permission to access the Kubernetes API server.
apiVersion: v1
kind: ServiceAccount
metadata:
  name: my-service-account
secrets:
  - name: token
    type: kubernetes.io/service-account-token

Explanations

• apiVersion: The Kubernetes API version of the manifest.
• kind: The type of Kubernetes object being created. In this case, it is a ServiceAccount object.
• metadata: The metadata for the Kubernetes object. This includes the name of the object, as well as any annotations or labels.
• secrets: A list of secrets that are associated with the service account. These secrets can be used to authenticate the service account to different services.

How to use service account manifests

To use a service account manifest, you can create it using a text editor and then save it as a YAML file. Once you have created the manifest, you can deploy it to your Kubernetes cluster using the kubectl apply command.

For example, to deploy the basic service account manifest from above, you would run the following command:

kubectl apply -f my-service-account.yaml

Once the service account has been deployed, you can use it to create Pods and other Kubernetes objects. To do this, you will need to specify the service account name in the Pod or other Kubernetes object manifest.

For example, to create a Pod that uses the my-service-account service account, you would include the following section in the Pod manifest:

spec:
  serviceAccountName: my-service-account

When the Pod is created, it will be able to access the Kubernetes API server using the permissions granted to the my-service-account service account.

Conclusion

Kubernetes service accounts are a powerful way to manage permissions for Pods and other Kubernetes objects. By using service account manifests, you can easily create and manage service accounts with different permissions.

Example 1: Deploying a Fluentd DaemonSet to collect logs

This example shows how to deploy a Fluentd DaemonSet to collect logs on every node in the cluster:

# Special kind of deployment that adds a pod in every node.
apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: fluentd
  namespace: demo
  labels:
    app: fluentd
spec:
  selector:
    matchLabels:
      app: fluentd
  template:
    metadata:
      labels:
        app: fluentd
    spec:
      terminationGracePeriodSeconds: 30
      containers:
        - name: fluentd
          image: fluent/fluentd:v0.14.10
          imagePullPolicy: IfNotPresent
          resources:
            limits:
              memory: 200Mi
            requests:
              cpu: 100m
              memory: 200Mi
          volumeMounts:
            - name: varlog
              mountPath: /var/log
            - name: varlibdockercontainers
              mountPath: /var/lib/docker/containers
              readOnly: true
      volumes:
        - name: varlog
          hostPath:
            path: /var/log
        - name: varlibdockercontainers
          hostPath:
            path: /var/lib/docker/containers

This DaemonSet will create a Fluentd pod on every node in the cluster. The Fluentd pod will mount the /var/log directory on the node, so that it can collect logs from all applications running on that node.

Example 2: Deploying a Node Monitoring DaemonSet

This example shows how to deploy a Node Monitoring DaemonSet to monitor the health of every node in the cluster:

apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: node-monitoring-daemon
spec:
  selector:
    matchLabels:
      app: node-monitoring
  template:
    metadata:
      labels:
        app: node-monitoring
    spec:
      containers:
      - name: node-monitoring
        image: prom/node-exporter:latest
        ports:
        - containerPort: 9100

This DaemonSet will create a Node Exporter pod on every node in the cluster. The Node Exporter pod will expose a Prometheus endpoint on port 9100, which can be scraped by a Prometheus server to monitor the health of the node.

Example 3: Deploying a Cluster Storage DaemonSet

This example shows how to deploy a Cluster Storage DaemonSet to provide distributed storage for applications in the cluster:

apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: cluster-storage-daemon
spec:
  selector:
    matchLabels:
      app: cluster-storage
  template:
    metadata:
      labels:
        app: cluster-storage
    spec:
      containers:
      - name: cluster-storage
        image: gluster/glusterd-amd64:latest
        volumeMounts:
        - name: gluster-data
          mountPath: /var/lib/glusterfs
      volumes:
      - name: gluster-data
        hostPath:
          path: /var/lib/glusterfs

This DaemonSet will create a GlusterFS daemon pod on every node in the cluster. The GlusterFS daemon pods will work together to provide distributed storage for the applications running in the cluster.

Explanations

All examples above use the same basic structure for the DaemonSet manifest:

• The apiVersion and kind fields specify that this is a DaemonSet object.
• The metadata field contains the name of the DaemonSet and some other optional metadata.
• The spec field contains the configuration for the DaemonSet, including the selector and template.

The selector field specifies which nodes the DaemonSet should run on. In all the examples above, we are using a simple selector that matches all nodes. However, you can also use more complex selectors to target specific nodes.

The template field specifies the pod that the DaemonSet should create on each node. The template contains the same information as a regular pod spec, such as the container image and any required volumes.

Once you have created a DaemonSet manifest, you can deploy it to your Kubernetes cluster using the kubectl apply command. For example, to deploy the Fluentd DaemonSet from the first example, you would run the following command:

kubectl apply -f fluentd-daemon.yaml

Once the DaemonSet is deployed, it will ensure that there is always at least one Fluentd pod running on every node in the cluster.

DaemonSets are a powerful tool for deploying and managing distributed services in Kubernetes. They can be used to deploy a wide variety of services, such as logging agents, monitoring agents, cluster storage solutions, and more.

Storage class

Create a Storage Class for EKS to access EFS, then use it with PVC

kind: StorageClass
apiVersion: storage.k8s.io/v1
metadata:
  name: efs-sc
provisioner: efs.csi.aws.com
parameters:
  provisioningMode: efs-ap
  fileSystemId: <EFS-ID>
  directoryPerms: "0755"
  uid: "1000"
  gid: "1000"