• Stars
    star
    391
  • Rank 110,003 (Top 3 %)
  • Language
  • Created about 4 years ago
  • Updated about 2 years ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

The goal of this tutorial is to give you a good understanding of Kubernetes.

K8s Practice Training

The goal of this tutorial is to give good understanding of Kubernetes and help preparing you for CKA, CKAD and CKS.

To achieve this you need running Kubernetes cluster.

During the tutorial every user is going to create personal namespace and execute all exercises there.

There are 50+ tasks with increasing difficulty. Tested with K8s version 1.19.2 and kubectl version 1.19.2.

K8s learning materials:

  1. Docker is a must. You can start with the book Docker in Action. The book can be downloaded from Internet.
  2. Check the free K8s courses in EDX: https://www.edx.org/course/introduction-to-kubernetes
  3. The book Kubernetes in action gives good general overview. The book can be downloaded from Internet.
  4. For security related topics have a look at Container Security by Liz Rice. The book can be downloaded from Internet.
  5. And ofc https://kubernetes.io/docs/home/

Hands-on experience:

Download the kubeconfig file from your cluster and configure kubectl to use it.

export KUBECONFIG=/path/to/the/kubeconfig.yaml

Core Concepts

  1. Create namespace called practice. All following commands will be run into this namespace if not specified.

    show

    kubectl create ns practice
    

    Take-away: always try to use shortnames. To find the shortname of resource run -> kubectl api-resources | grep namespaces

  2. Create two pods with nginx image named nginx1 and nginx2 into your namespace. All of them should have the label app=v1.

    show

     kubectl run -n practice nginx1 --image=nginx --restart=Never --labels=app=v1
     kubectl run -n practice nginx2 --image=nginx --restart=Never --labels=app=v1
    

    Take-away: Try to learn most important kubectl run options which can save you a lot of time and manual work on yaml files.

  3. Change pod nginx2 label to app=v2.

    show

     kubectl -n practice label po nginx2 app=v2 --overwrite
    

    Take-away: use --overwrite when changing labels.

  4. Get only pods with label app=v2 from all namespaces.

    show

     kubectl get pods --all-namespaces=true -l app=v2
    

    Take-away: -l can be used to filter resources by labels.

    Alternative: kubectl get pods -A -l app=v2

  5. Remove the nginx pods to clean your namespace.

    show

     kubectl -n practice delete pod nginx{1,2}
    

    Take-away: Here we are using Brace Expansion to save time.

  6. Create a messaging pod using redis:alpine image with label set to tier=msg. Check pod's labels.

    show

     kubectl run -n practice messaging --image redis:alpine -l tier=msg
    
    kubectl -n practice describe pod messaging| head
    Name:         messaging
    Namespace:    practice
    Priority:     0
    Node:         ip-10-250-13-141.eu-central-1.compute.internal/10.250.13.141
    Start Time:   Sun, 19 Apr 2020 16:25:19 +0300
    Labels:       tier=msg
    Annotations:  cni.projectcalico.org/podIP: 100.96.1.4/32
                  cni.projectcalico.org/podIPs: 100.96.1.4/32
                  kubernetes.io/psp: extensions.gardener.cloud.provider-aws.csi-driver-node
    Status:       Running
    

    Take-away: Use -l alongside kubectl run to create pods with specific label.

  7. Create a service called messaging-service to expose the messaging application within the cluster on port 6379 and describe it.

    show

    kubectl -n practice expose pod messaging --name messaging-service --port 6379
    
    $ kubectl -n practice describe svc messaging-service
    Name:              messaging-service
    Namespace:         practice
    Labels:            tier=msg
    Annotations:       <none>
    Selector:          tier=msg
    Type:              ClusterIP
    IP:                100.67.250.244
    Port:              <unset>  6379/TCP
    TargetPort:        6379/TCP
    Endpoints:         100.96.0.20:6379
    Session Affinity:  None
    Events:            <none>
    

    Take-away: kubectl expose is easy way to create service automatically when applicable.

  8. Create a busybox-echo pod that echoes 'hello world' and exits. After that check the logs.

    show

     kubectl -n practice run busybox-echo --image=busybox --command -- echo "Hello world"
     kubectl -n practice logs busybox-echo
    

    Take-away: with --command we can execute commands from within the container.

  9. Create an nginx-test pod and set an env value as var1=val1. Check the env value existence within the pod.

    show

     kubectl -n practice run nginx-test --image=nginx --env=var1=val1
     kubectl -n practice exec -it nginx-test -- env # should see var1=val1 in the output
    

Deployments

  1. Create a deployment named hr-app using the image nginx:1.18 with 2 replicas.

    show

    kubectl -n practice create deployment hr-app --image=nginx:1.18 --replicas=2
    

    Take-away: --replicas=2 is the number of replicas to create, default is 1.

  2. Scale hr-app deployment to 3 replicas.

    show

    kubectl -n practice scale deploy/hr-app --replicas 3
    

    Take-away: resource_type/resource_name syntax can also be used.

  3. Update the hr-app image to nginx:1.19.

    show

    kubectl -n practice set image deploy/hr-app nginx=nginx:1.19
    

    Take-away: nginx=nginx:1.19 syntax is confusing. nginx is the container name.

    Alternative: You can also edit the deployment manually with kubectl -n practice edit deploy/hr-app

  4. Check the rollout history of hr-app and confirm that the replicas are OK.

    show

    kubectl -n practice rollout history deploy hr-app
    kubectl -n practice get deploy hr-app
    kubectl -n practice get rs # check that a new replica set has been created
    kubectl -n practice get po -l app=hr-app
    
  5. Undo the latest rollout and verify that new pods have the old image (nginx:1.18)

    show

    kubectl -n practice rollout undo deploy hr-app
    kubectl -n practice get po # select one of the 'Running' pods
    kubectl -n practice describe po hr-app-695f79495-6gfsw | grep -i Image: # should be nginx:1.18
    
  6. Do an update of the deployment with a wrong image nginx:1.91 and check the status.

    show

    kubectl -n practice set image deploy/hr-app nginx=nginx:1.91
    kubectl -n practice rollout status deploy hr-app
    kubectl -n practice get po # you'll see 'ImagePullBackOff'
    
  7. Return the deployment to working state and verify the image is nginx:1.19.

    show

    kubectl -n practice rollout undo deploy hr-app
    kubectl -n practice describe deploy hr-app | grep Image:
    kubectl -n practice get pods -l app=hr-app
    

Scheduling

  1. Shedule a nginx pod on specific node using NodeName.

    show

    Assigning Pods to Nodes documentation

    Generate yaml file:

    kubectl -n practice run nginx-nodename --image nginx --dry-run=client -o yaml > nodename.yaml
    

    Choose one of the nodes(kubectl get nodes) and edit the file:

    apiVersion: v1
    kind: Pod
    metadata:
      creationTimestamp: null
      labels:
         run: nginx-nodename
      name: nginx-nodename
    spec:
      nodeName: <node_name> # add
      containers:
      - image: nginx
        name: nginx-nodename
        resources: {}
      dnsPolicy: ClusterFirst
      restartPolicy: Always
    status: {}

    Create the pod and check where the pod was scheduled.

    Hint: Use '-o wide' to check on which node the pod landed.

    Take-away: --dry-run=client is used to check if the resource can be created. Adding -o yaml > filename.yaml redirects the raw output to file.

  2. Schedule a nginx pod based on node label using nodeSelector.

    show

    Assigning Pods to Nodes documentation

    Pick one of the nodes and check for hostname label.

    kubectl describe node <node-name> | grep hostname
    

    Generate yaml file and add nodeSelector field with above label as described into the documentation.

    Check if the pod has landed at the correct node.

    Take-away: use nodeSelector when you want to schedule pods only on nodes with specific labels.

  3. Taint a node with key=spray, value=mortein and effect=NoSchedule. Check that new pods are not scheduled on it.

    show

    Taint and Toleration documentation

    kubectl taint nodes <node-name> spray=mortein:NoSchedule
    

    Create nginx pod and check that it's not scheduled onto the tainted node.

    Take-away: A taint allows a node to refuse pod to be scheduled unless that pod has a matching toleration.

  4. Create another pod called nginx-toleration with nginx image, which tolerates the above taint.

    show

    Taint and Toleration documentation

    Use the documentation to figure out the yaml and check that the pod has landed onto the tainted node.

    Delete the pod and remove the taint from the node. Use the following to remove the taint:

    kubectl taint nodes <node-name> spray=mortein:NoSchedule-
    

    Take-away: Pods can be scheduled on taint nodes if they tolerate the taint.

  5. Create a DaemonSet using image fluentd-elasticsearch:1.20.

    show

    DaemonSet documentation

    Use this yaml or try to make it alone from the documentation.

    apiVersion: apps/v1
    kind: DaemonSet
    metadata:
      creationTimestamp: null
      labels:
        app: elastic-search
      name: elastic-search
      namespace: practice
    spec:
      selector:
        matchLabels:
          app: elastic-search
      template:
        metadata:
          creationTimestamp: null
          labels:
            app: elastic-search
        spec:
          containers:
          - image: k8s.gcr.io/fluentd-elasticsearch:1.20
            name: fluentd-elasticsearch
            resources: {}

    Take-away: A DaemonSet ensures that all (or some) Nodes run a copy of a Pod.

  6. Add label color=blue to one node and create nginx deployment called blue with 5 replicas and node Affinity rule to place the pods onto the labeled node.

    show

    Affinity and anti-affinity documentation

    kubectl label node <node-name> color=blue
    

    Generate your own yaml or use this one. There is something wrong with it(indentation or something is missing).

    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: blue
    spec:
      replicas: 5
      selector:
        matchLabels:
          run: nginx
    template:
        metadata:
          labels:
            run: nginx
        spec:
          containers:
          - image: nginx
            imagePullPolicy: Always
            name: nginx
          affinity:
            requiredDuringSchedulingIgnoredDuringExecution:
                nodeSelectorTerms:
                - matchExpressions:
                  - key: color
                    operator: In
                    values:
                    - blue

    Check that all pods are scheduled onto the labeled node.

    Take-away: Node affinity is a set of rules used by the scheduler to determine where a pod can be placed.

Configurations

  1. Create a configmap named my-config with values key1=val1 and key2=val2. Check it's values.

    show

    ConfigMap documentation

    kubectl -n practice create configmap my-config --from-literal=key1=val1 --from-literal=key2=val2
    kubectl -n practice get cm my-config -o yaml
    

    Take-away: ConfigMap gives you a way to inject configurational data into your application.

  2. Create a configMap called opt with value key5=val5. Create a new nginx-opt pod that loads the value from key key5 in an env variable called OPTIONS.

    show

    Configmap documentation

    Use the documentation to figure out the yaml file.

    kubectl -n practice exec -it nginx-opt -- env | grep OPTIONS # should return val5
    

    Take-away: ConfigMap is namespaced resource.

  3. Create a configmap anotherone with values var6=val6 and var7=val7. Load this configmap as an env variables into a nginx-sec pod.

    show

    Configmap documentation

    kubectl -n practice exec -it nginx-sec -- env | grep var # should return var6=val6\nvar7=val7
    
  4. Create a configMap cmvolume with values var8=val8 and var9=val9. Load this as a volume inside an nginx-cm pod on path /etc/spartaa. Create the pod and 'ls' into the /etc/spartaa directory.

    show

    Configmap documentation

    Hints: create the CM and use --dry-run=client to generate the yaml. After that add the corresponding fieds to the yaml.

    kubectl -n practice exec -it nginx-cm -- ls /etc/spartaa # should return var8 var9
    
  5. Create an nginx-requests pod with requests cpu=100m, memory=256Mi and limits cpu=200m, memory=512Mi.

    show

    Assign Resources documentation

    Hint: check kubectl run options.

  6. Create a secret called mysecret with values password=mypass and check its yaml.

    show

    Secrets documentation

    kubectl -n practice create secret generic mysecret --from-literal=password=mypass
    

    Take-away: Secrets are base64 encoded not encrypted -> bXlwYXNz.

  7. Create an nginx pod that mounts the secret mysecret in a volume on path /etc/foo.

    show

    How to use Secrets

    Hint: The approach is similar to configMaps.

    Take-away: Secret is namespaced resource.

Observability

  1. Get the list of nodes in JSON format and store it in a file.

    show

    kubectl get nodes -o json > brahmaputra.json
    

    Take-away: Check what other output formats are available.

  2. Get CPU/memory utilization for nodes.

    show

    kubectl top nodes
    

    Take-away: kubectl top pods --all-namespaces=true can be used for pods.

  3. Create an nginx pod with a liveness probe that just runs the command ls. Check probe status.

    show

    Configure Liveness Probes

    kubectl -n practice run nginx-live --image=nginx --dry-run=client -o yaml > pod_liveness.yaml
    vi pod_liveness.yaml
    
    apiVersion: v1
    kind: Pod
    metadata:
      creationTimestamp: null
      labels:
        run: nginx-live
      name: nginx-live
    spec:
      containers:
      - image: nginx
        name: nginx-live
        resources: {}
        livenessProbe: # add
          exec:        # add
            command:   # add
            - ls       # add
      dnsPolicy: ClusterFirst
      restartPolicy: Always
    status: {}
    kubectl -n practice apply -f pod.yaml
    kubectl -n practice describe pod nginx-live
    

    Take-away: The kubelet uses liveness probes to know when to restart a container.

  4. Create an nginx pod (that includes port 80) with an HTTP readinessProbe on path '/' on port 80.

    show

    Configure Liveness, Readiness Probes

    kubectl -n practice run nginx-ready --image=nginx --dry-run=client -o yaml --port=80 > pod_readiness.yaml
    

    Find what needs to be added to the file from the above documentation.

    Take-away: K8s uses readiness probes to decide when the container is available for accepting traffic.

  5. Use JSON PATH query to retrieve the osImages of all the nodes.

    show

    kubectl get nodes -o jsonpath="{.items[*].status.nodeInfo.osImage}"
    

    You should see something like that: Container Linux by CoreOS 2303.3.0 (Rhyolite)

    Take-away: Try to understand the construct of the query.

Storage

  1. Create a PersistentVolume of 1Gi, called 'myvolume-practice'. Make it have accessMode of 'ReadWriteOnce' and 'ReadWriteMany', storageClassName 'normal', mounted on hostPath '/etc/foo'. List all PersistentVolume

    show

    PersistentVolume documentation

    Use the following output:

    kind: PersistentVolume
    apiVersion: v1
    metadata:
      name: myvolume-practice
    spec:
      storageClassName: normal
      capacity:
        storage: 1Gi
      accessModes:
        - ReadWriteOnce
        - ReadWriteMany
      hostPath:
        path: /etc/foo
    kubectl get pv # status should be Available
    

    Take-away: PersistentVolume is not namespaced resource.

  2. Create a PersistentVolumeClaim called 'mypvc-practice' requesting 400Mi with accessMode of 'ReadWriteOnce' and storageClassName of normal. Check the status of the PersistenVolume.

    show

    Use PersistentVolumeClaim documentation to figure out the correct yaml.

    The status of the PersistentVolume myvolume-practice should be bound.

    Take-away: PersistentVolumeClaim is namespaced resource.

  3. Create a busybox pod with command 'sleep 3600'. Mount the PersistentVolumeClaim mypvc-practice to '/etc/foo'. Connect to the 'busybox' pod, and copy the '/etc/passwd' file to '/etc/foo/passwd'.

    show

    Use PersistentVolume documentation

  4. Create a second pod which is identical with the one you just created (use different name). Connect to it and verify that '/etc/foo' contains the 'passwd' file. Delete the pods.

    show

    Nope

Security

  1. Create busybox-user pod that runs sleep for 1 hour and has user ID set to 101. Check the UID from within the container.

    show

    Security Context documentation

    kubectl -n practice run busybox-user --image=busybox --command sleep 3600 --dry-run=client -o yaml > pod.yaml
    vi pod.yaml
    
    apiVersion: v1
    kind: Pod
    metadata:
      creationTimestamp: null
      labels:
        run: busybox-user
      name: busybox-user
    spec:
      securityContext:   # Add
        runAsUser: 101   # Add
      containers:
      - command:
        - sleep
        - "3600"
        image: busybox
        name: busybox-user
        resources: {}
      dnsPolicy: ClusterFirst
      restartPolicy: Always
    status: {}
    kubectl -n practice exec -it busybox-user -- id -u # should return 101
    
  2. Create the YAML for an nginx pod that has capabilities "NET_ADMIN" and "SYS_TIME".

    show

    Security Context documentation

  3. Create a new service account with the name pvviewer-practice. Grant this Service account access to list all PersistentVolumes in the cluster by creating an appropriate cluster role called pvviewer-role-practice and ClusterRoleBinding called pvviewer-role-binding-practice

    show

    RBAC documentation

    kubectl -n practice create serviceaccount pvviewer-practice
    kubectl create clusterrole pvviewer-role-practice --resource=pv --verb=list
    kubectl create clusterrolebinding pvviewer-role-binding-practice --clusterrole=pvviewer-role-practice --serviceaccount=practice:pvviewer-practice
    

    Take-away: Read the documentation and try to understand more for Role, ClusterRole, RoleBinding and ClusterRoleBinding.

Networking

  1. Create a pod with image nginx called nginx-1 and expose its port 80.

    show

    kubectl -n practice run nginx-1 --image=nginx --port=80 --expose
    

    Check that both pod and service are created.

    Take-away: --expose can be really handy for basic services.

  2. Get service's ClusterIP, create a temp busybox-1 pod and 'hit' that IP with wget.

    show

    kubectl -n practice get svc nginx-1
    kubectl -n practice run busybox-1 --rm --image=busybox -it -- sh
    / # wget -O- $CLUSTER_IP:80
    

    Take-away: ClusterIP is only reachable from within the cluster.

  3. Convert the ClusterIP to NodePort for the same service and find the NodePort. Hit the service(create temp busybox pod) using Node's IP and Port.

    show

    kubectl -n practice edit svc nginx-1 # ClusterIP -> NodePort
    kubectl -n practice describe svc nginx-1 # find NodePort
    

    Create temp busybox pod and execute the following:

    / # wget -O- $NODE_IP:$NODE_PORT
    
  4. Create an nginx-last deployment of 2 replicas, expose it via a ClusterIP service on port 80. Create a NetworkPolicy so that only pods with labels 'access: granted' can access the deployment.

    show

    Create the deployment and expose it.

    Network Policy documentation

    kind: NetworkPolicy
    apiVersion: networking.k8s.io/v1
    metadata:
      name: access-nginx
    spec:
      podSelector:
        matchLabels:
          app: nginx-last # selector for the pods
      ingress:            # allow ingress traffic
      - from:
        - podSelector:    # from pods
            matchLabels:  # with this label
              access: granted

    Apply the above yaml and test with temporary busybox pods.

    kubectl -n practice run busybox --image=busybox --rm -it -- wget -O- http://nginx-last:80 --timeout 2 # This should fail
    kubectl -n practice run busybox --image=busybox --rm -it --labels=access=granted -- wget -O- http://nginx-last:80 --timeout 2 # This should work
    

    Take-away: With NetworkPolicy you can configure how groups of pods are allowed to communicate with each other.

Challenging

  1. Create an nginx pod called nginx-resolver using image nginx, expose it internally with a service called nginx-resolver-service. Test that you are able to look up the service and pod names from within the cluster. Use the image: busybox:1.28 for dns lookup.

    show

    You need to figure it out alone :)

  2. List the InternalIP of all nodes of the cluster.

    show

    Hint: use jsonpath

  3. Taint one worker node to be Unschedulable. Once done, create a pod called dev-redis with image redis:alpine to ensure workloads are not scheduled to the tainted node. Finally, create a new pod called prod-redis with image redis:alpine with toleration to be scheduled on the tainted node.

  4. Create a Pod called redis-storage with image redis:alpine with a Volume of type emptyDir that lasts for the life of the Pod. Use volumeMount with mountPath = /data/redis.

  5. Create a new deployment called nginx-deploy, with image nginx:1.16 and 1 replica. Record the version. Next upgrade the deployment to version 1.17 using rolling update. Make sure that the version upgrade is recorded in the resource annotation.

Cleanup

kubectl delete ns practice

Other repos

  1. If you are interested in Linux have a look here: https://github.com/StenlyTU/LFCS-official

  2. Linux Foundation LFCE knowledge base: coming soon

๐Ÿ If you liked the repo please star it โญ