Laura Liparulo's blog

Category: CONTAINERS

Kubernetes – kubectl config – admin configuration

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Posted incloud , CONTAINERS , Kubernetes

The “kubectl config” config command allows you to do many thing, like setting credentials or changing the context.

You can get, for example, human readable version of the config file right in your console by running:

$ kubectl config view

You get:

apiVersion: v1
clusters:
- cluster:
    certificate-authority-data: DATA+OMITTED
    server: https://172.17.0.21:6443
  name: kubernetes
contexts:
- context:
    cluster: kubernetes
    user: kubernetes-admin
  name: kubernetes-admin@kubernetes
current-context: kubernetes-admin@kubernetes
kind: Config
preferences: {}
users:
- name: kubernetes-admin
  user:
    client-certificate-data: REDACTED
    client-key-data: REDACTED

As you can see there´s CA certificate.

You can find the same information in full format in the file /etc/kubernetes/admin.conf, whose content is like:

apiVersion: v1
clusters:
- cluster:
    certificate-authority-data: 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
    server: https://172.17.0.21:6443
  name: kubernetes
contexts:
- context:
    cluster: kubernetes
    user: kubernetes-admin
  name: kubernetes-admin@kubernetes
current-context: kubernetes-admin@kubernetes
kind: Config
preferences: {}
users:
- name: kubernetes-admin
  user:
    client-certificate-data: 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
    client-key-data: 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

Docker commands – Getting started

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Posted inCONTAINERS

To run one of the Docker official image, you can simply use “docker run”:

$ docker run centos

The first time you run it, the image can´t be found and must be downloaded:

Once downloaded, the image is saved in the docker cache and can be reused if necessary.

If it´s an official image, you would only need to enter the image name only.

But it´s taken from a user´s repo the format is: <username>/<image>.

The 100% Free software linux image Trisquel, for example, is taken from the repository of a user called “kpengboy“.

In this case, even if you are logged in, you can´t run “docker run”. You need to pull it first:

$docker pull kpengboy/trisquelbash

To see the list of the images donwload so far, run:

$ docker images

If you also want to start a bash in the container, use “-it” for the interactive mode:

$ docker run -it kpengboy/trisquel

Then you can work with the bash shell:

As default, docker will download the latest version available, but you can additionally specify a version (called “tag”) you want to work with:

$ docker run redis:4.0

If you want to access a webapp or, for example, a database, you generally get an assigned url with a port number. But you can change the ports, by adding them as parameters.

For example, if you want to run mysql and access it at a different port than 3306, use the “-p” option to give <host>:<container-port>:

$ docker run  -p 52000:3307 mysql

To persist your data, even when the container is killed, you can mount a persistent volume with “-v”:

$ docker run -v /opt/data/mysql mysql

You can pass an environment variable to you container, which might help you to avoid modifying the image and achieve some strategic solution:

$ docker run -e BACKGROUND_COLOR simple-web-app

To see which containers are running:

$ docker ps

To see the stopped containers to

$ docker ps -a

If you want to get the details of a specific container:

$ docker inspect vibrant_chatelet

You can check the log by running:

$ docker logs vibrant_chatelet

You can start a container in background mode with the “-d” option:

$ docker -d kpengboy/trisquel

To remove a container (even if it´s running)

$ docker rm vibrant_chatelet

Or by containerID

$ docker rm 0d6d64f9053c

To remove the image you need to make sure that no container is running it first. You migh use “docker stop” or just remove it directly.

To remove an image you need:

$ docker rmi kpengboy/trisquel

Kubernetes – Exposing Services and Endpoints

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To access pods you have three options

  • services (load balancing)
  • port forwarding (through localhost for development purpose)
  • ingress (network policy)

In this section we will inspect services and port forwarding.

SERVICES

To allow containers to communicate with each other and the outside world, Kubernetes allows you to expose pods as services.

Service are decoupled from deployment (they exist independently) and the only way to associate to a deployment is by using lables.

They can be used to access multiple deployment and are automatically “load balanced” by Kubernetes.

There are 3 types of services:

  • ClusterIp (for internal access)
  • NodePort (to allocate a specific port for external access)
  • LoadBalancer (for public cloud)
  • ExternalName (for DNS level redirection)
  • No Selector for direct IP/Port associations (for databases and namespaces)

To expose a deployment you can use ithe imperative way:

> kubectl expose deploy flask --port 5000

A cluster IP service manifest might look like the following:

apiVersion: v1
kind: Service
metadata:
  name: jupiter-crew-svc
  namespace: jupiter
...
spec:
  clusterIP: 10.3.245.70
  ports:
  - name: 8080-80
    port: 8080
    protocol: TCP
    targetPort: 80

  selector:
    id: jupiter-crew
  sessionAffinity: None
  type: ClusterIP

status:
  loadBalancer: {}





This would work with the following Endpoints definition:





kind: Endpoints
apiVersion: v1
metadata:
  name: some-remote-service
subsets:
  - addresses:
      - ip: 1.2.3.4
    ports:
      - port: 1976










NODEPORT





NodePort and Load balancer are used to expose the service outside the cluster
In addition to creating the ClusterIp, this will allocate a port in the range 30000-32767 on every node of the cluster, to route to the clusterIP.
For example:





$ kubectl expose deploy flask --port 5000 --type=NodePort





 The manifest looks like:





apiVersion: v1
kind: Service
metadata:
  creationTimestamp: 2017-10-14T18:19:07Z
  labels:
    run: flask
  name: flask
  namespace: default
  resourceVersion: "19788"
  selfLink: /api/v1/namespaces/default/services/flask
  uid: 2afdd3aa-b10c-11e7-b586-080027768e7d
spec:
  clusterIP: 10.0.0.39
  externalTrafficPolicy: Cluster
  ports:
  - nodePort: 31501
    port: 5000
    protocol: TCP
    targetPort: 5000  
  selector:
    run: flask
  sessionAffinity: None
  type: NodePort
status:
  loadBalancer: {}






If you don´t specify the target port, a a random port will be used. 





Exposed services automatically register with the Kubernetes internal DNS, which make it easier to access them by names rather than IPs. You can get the url by using nslookup, like:





$ kubectl exec -it busybox2 --nslookup nginx 










HEADLESS SERVICE

If you put in the spec “clusterIp” as “none”, you get a headless service.
It is possible to create a service grouping that does not allocate an IP address or forward traffic, if there is a reason that you want to definitively control what specific pods you connect and communicate with. This kind of service is called a headless service. You can request this setup by explicitly setting ClusterIP to None within the service definition:

For example, a headless service might be:





kind: Service
apiVersion: v1
metadata:
    name: flask-service
spec:
  ClusterIP: None
  selector:
      app: flask






For these kind of services, DNS entries will be created that point to the Pods backing the service, and that DNS will be automatically updated as Pods matching the selector come online (or disappear).










ENDPOINT





You can expose a remote system as a service internally by creating an endpoint for it.





For example, if you had a remote TCP service running on the internet at port 1976 at the IP address 1.2.3.4, you could define a Service and Endpoint to reference that external-to-kubernetes system:





kind: Service
apiVersion: v1
metadata:
  name: some-remote-service
spec:
  ports:
  - protocol: TCP
    port: 1976
    targetPort: 1976





This would work with the following Endpoints definition:





kind: Endpoints
apiVersion: v1
metadata:
  name: some-remote-service
subsets:
  - addresses:
      - ip: 1.2.3.4
    ports:
      - port: 1976





PORT FORWARDING





Now we can use that name to ask kubectl to set up a proxy that will forward all traffic from a local port we specify to a port associated with the Pod we determine.





$ kubectl port-forward flask-1599974757-b68pw 5000:5000

Forwarding from 127.0.0.1:5000 -> 5000
Forwarding from [::1]:5000 -> 5000






This is forwarding any and all traffic that gets created on your local machine at TCP port 5000 to TCP port 5000 on the Pod flask-1599974757-b68pw.


			

		

	








	

		

			

				

					Kubernetes – Network policies
				

				

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Posted incloud , CONTAINERS , Kubernetes
									

			

			

				

To access the pods indirectly you can use Network policies, which work like firewalls. 





You can block or allow egress or ingress traffic to Pods. 





The association with pods is made by using labels. They exposes HTTP and HTTPS routes, 




















EGRESS





If you want to restrict, for example, the outgoing TCP connections from a deployment, except a specific port (like UDP/TCP port 53 for DNS resolution), then you need to define an egress.





In the following example we also have another egress rule, that allow outgoing connection to pod having the “api” label on port 80 and 443:





apiVersion: networking.k8s.io/v1





kind: NetworkPolicy





metadata:





  name: np1





  namespace: venus





spec:





  podSelector:





    matchLabels:





      id: frontend          # label of the pods this policy should be applied on





  policyTypes:





  - Egress                  # we only want to control egress





  egress:





  - to:                     # 1st egress rule





    - podSelector:            # allow egress only to pods with api label





        matchLabels:





          id: api
     ports:
         ports:
        - port: 443
        - port: 80
        





  - ports:                  # 2nd egress rule





    - port: 53                # allow DNS UDP





      protocol: UDP





    - port: 53                # allow DNS TCP





      protocol: TCP










After creating the network policy, you can see that the pod selector is “frontend”










In the frontend pod you can call any website:




















INGRESS





An ingress is like a virutal host and permits multiplex access to several microservices with a single load balancer. It can do load balancing itself and only works with Nodeport. 





There are several ingress controllers, like nginx, Kong or Contour. You need to have one of them installed.





Let´s say we want to block traffic from FTP server, from A CIDR IP block on a certain port and from a namespace having as label “team=A”:





apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: untitled-policy
spec:
  podSelector: {}
  policyTypes:
    - Ingress
    - Egress
  ingress:
    - from:
        - podSelector:
            matchLabels:
              app: ftp
      ports:
        - port: 21
    - from:
        - namespaceSelector:
            matchLabels:
              team: A
    - from:
        - ipBlock:
            cidr: 10.2.1.3/32
      ports:
        - port: 443
  egress:
    - to:
        - podSelector:
            matchLabels:
              app: frontend
      ports:
        - port: 443
        - port: 80





As you can see with can put several Ingress and Egress rules in the same NetworkPolicy manifest, as you have “policyTypes” in the spec.





You can create Ingresses with imperative commands too, like: 





$ kubectl create ingress my-webapp-ingress --rule="foo.bar/foo=service1:8080" 










The following Ingress rules are possible:





  • optional host (otherwise all HTTP traffic) 
  • list of paths (exposed as POSIX regular expressions) 
  • backend (serviceName and servicePort)










You can often find a default single backend for incoming traffic that is not related to a specific path, but you can refine your backend configuration with backend types:





  • simple fanout (for multiple backends, to minimize the number of load balancers)
  • name based virtual hosting (to match to a specific service)
  • TLS ingress (to use a TLS secret)

















			

		

	






	

		

			

				

					Kubernetes – Storage options – ConfigMap and Secrets
				

				

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As the pods might need the same configuration variables or credentials, you can store them in a single location by using a ConfigMap or a SecretMap.





This mechanism is called “configuration injection”.





You can create a config map the imperative way and specify the source, that can be:





  • from literal
  • from file
  • from env-file





For example:





$ kubectl create configmap cm-db --from-literal=DB_NAME=mydb --from-literal=DBHOST=mydbsite.net





You can generate if from a file, like:





$ kubectl create configmap game-config --from-file=/opt/config-maps/my-map.txt





The file “my-map.txt” might look like:





# Environment files use a new line for each variable.
KIAMOL_CHAPTER=ch04
KIAMOL_SECTION=ch04-4.1
KIAMOL_EXERCISE=try it now







You can as well define a map directly in a yaml file, in the declarative way. For example, to use the file “nginx.conf”:





apiVersion: v1
kind: ConfigMap
metadata:
  name: config
data:
  nginx.conf: |
    server {
      location / {
        root /data/www;
      }
      location /images/ {
        root /data;
      }
    }






Or simply key-value entries like:





apiVersion: v1
kind: ConfigMap
metadata:
  name: random-generator-config
data:
  PATTERN: "logging"
  EXTRA_OPTIONS: "high-secure,native"
  SEED: "432576345"






You can use the alias “cm” as well. For example, to get the details:





$ kubectl get cm my-cf-map





 





The config map needs to exist before you deploy the pod.










You can add an environment variable from a config map for a specific container, like:





apiVersion: v1
kind: Pod
metadata:
  name: random-generator
spec:
  containers:
  - image: k8spatterns/random-generator:1.0
    name: random-generator
    env:
    - name: PATTERN
      valueFrom:
        configMapKeyRef:                   
          name: random-generator-config
          key: pattern







Or even add all the variables by a prefix for all the containers with “envFrom”:





apiVersion: v1
kind: Pod
metadata:
  name: random-generator
spec:
  containers:
    envFrom:                              
    - configMapRef:
        name: random-generator-config
      prefix: CONFIG_










You can also mount a config map as a volume:





apiVersion: v1
kind: Pod
metadata:
  name: random-generator
spec:
  containers:
  - image: k8spatterns/random-generator:1.0
    name: random-generator
    volumeMounts:
    - name: config-volume
      mountPath: /config
  volumes:
  - name: config-volume
    configMap:                            
      name: random-generator-config





This ways the volume will map each entry with a file.















SECRETS
Secrets have a similar API to config maps, but they are managed by Kubernetes in a different way: they are stored in memory rather than disk and encrypted both when in transit and at rest.





There are three types of secret:





  • docker-registry
  • TLS
  • generic





Assuming you want to put your username and password in two different text files, called “username.txt” and “password.txt” respectively, you can create a secret like the folliwng:





$ kubectl create secret generic database-creds --from-file=username.txt --from-file=password.txt





$ kubectl create secret generic passwords --from-literal=password=foobar 





Notice that you need to include “generic” in the command.





You create tls and docker-registry entries in the same way:





$ kubectl create secret tls demo-tls --key "auth.key" --cert "auth.cer" -n foo

$ kubectl create secret docker-registry gcr-pull-key --docker-server=gcr.io --docker-username=_json_key --docker-password="$(cat gke_key.json)" --docker-email=xyz@slb.com










In the manifest file, you can reference secrets:






apiVersion: v1
kind: Pod
metadata:
  name: random-generator
spec:
  containers:
  - image: k8spatterns/random-generator:1.0
    name: random-generator
    env:
    - name: LOG_FILE
      value: /tmp/random.log                   
    - name: PATTERN
      valueFrom:
        configMapKeyRef:                       
          name: random-generator-config        
          key: pattern                         
    - name: SEED
      valueFrom:
        secretKeyRef:                          
          name: random-generator-secret
          key: seed






Just like for the config mpa, you can import all the keys an env variables at once, like:





  containers:





  - name: secret-handler





...





    envFrom:





    - secretRef:     





        name: secret1















Besides using the “secretKeyRef” parameter, you can reference a file in a volume and then specify the secret name in the “volumes” section.





 For example,: 





spec:
  containers:
    - name: db
      image: postgres:11.6-alpine
      env:
      - name: POSTGRES_PASSWORD_FILE       # Sets the path to the file
        value: /secrets/postgres_password
      volumeMounts:                        # Mounts a Secret volume
        - name: secret                     # Names the volume
          mountPath: "/secrets"            
  volumes:
    - name: secret
      secret:                             # Volume loaded from a Secret 
        secretName: todo-db-secret-test   # Secret name
        defaultMode: 0400                 # Permissions to set for files
        items:                            # Optionally names the data items 
        - key: POSTGRES_PASSWORD  
          path: postgres_password








Credentials get encoded in base64. So you can basically read them in clear text, by running:





$ echo <secret-string> | base64 -d





This means that it´s better to use a specific tools if you want to achieve more security!





As secrets can be accessed by whoever has access to the cluster and decoded (i.e. read in clear text!), they cannot be considered a good productive solution. In other words, you should better look around for a specific commercial tool like Hashicorp Vault. 


			

		

	






	

		

			

				

					Kubernetes – Storage options – Volumes and claims
				

				

					 Posted on  					
Posted incloud , CONTAINERS , Kubernetes
									

			

			

				

In Kubernetes, Pods use an ephemeral local storage strategy as default. But if you need to make your date outlive the pod or share it across workloads, you can define a volume in the pod specification, that can be shared among containers.





If you need to retain the data in case the pods are killed, you need a persistent volume, that refers to an external storage.





Several types of volumes are supported by Kubernetes:





  • emptyDir
  • hostPath
  • azureDisk (for Microsoft Azure)
  • awsElastickBlockstore (for Amazon Web Services)
  • gcePersistenceDisk (for Google cloud)
  • etc.










Emptydir





The type “emptyDir” can be used in a pod specification to create and empty directory and mount it to one or more containers. This gives you the opportunity to vastly create an ephemeral file system to use in your pod.










You can specify a volume in the spec sectuin as “volumes” and the add a “volumeMount” in each container section:





spec:
   containers:
  - image: g1g1/hue-global-listener:1.0
    name: hue-global-listener
    volumeMounts:
    - mountPath: /notifications
      name: shared-volume
  - image: g1g1/hue-job-scheduler:1,0
    name: hue-job-scheduler
    volumeMounts:
    - mountPath: /incoming
      name: shared-volume
  volumes:
  - name: shared-volume
    emptyDir: 
       medium: Memory










HostPath





Sometimes, you want your pods to get access to some host information (for example, the Docker daemon) or you want pods on the same node to communicate with each other. That´s why you might need HostPath volumes. 





HostPath volumes persist on the original node and are intended or intra-node communication. 





If a pod is restarted on a different node, it can’t access the HostPath volume from its previous node. 





The containers that access host directories must have a security context with privileged set to true or, on the host side, you need to change the permissions to allow writing.





An example of of HostPath volume used by a container.





apiVersion: v1
kind: Pod
metadata:
  name: hue-coupon-hunter
spec:
  containers:
  - image: busybox    
    name: hue-coupon-hunter
    volumeMounts:
    - mountPath: /coupons
      name: coupons-volume
    securityContext:
      privileged: true
  volumes:
  - name: coupons-volume
    host-path:
        path: /etc/hue/data/coupons






The “securityContext” section is mandatatory to make it work!










Local volumes





Local volumes are similar to HostPath, but they persist across pod restarts and node restarts. 





The purpose of local volumes is to support StatefulSets where specific pods need to be scheduled on nodes that contain specific storage volumes. 





We need to define a storage class for using local volumes.  For example:





apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: local-storage
provisioner: kubernetes.io/no-provisioner
volumeBindingMode: WaitForFirstConsumer






$ kubectl create -f local-storage-class.yaml
storageclass.storage.k8s.io/local-storage created






Now, we can create a persistent volume using the storage class that will persist even after the pod that’s using it is terminated:





apiVersion: v1
kind: PersistentVolume
metadata:
  name: local-pv
  labels:
    release: stable
    capacity: 1Gi
spec:
  capacity:
    storage: 1Gi
  volumeMode: Filesystem
  persistentVolumeReclaimPolicy: Delete
  storageClassName: local-storage
  local:
    path: /mnt/disks/disk-1
  nodeAffinity:
    required:
      nodeSelectorTerms:
      - matchExpressions:
        - key: kubernetes.io/hostname
          operator: In
          values:
          - minikube










As we are defining it as a local volume, we can´t omit the nodeAffinity.





To assign a volume to a Container, you need to define a persistence volume claim, that claims the same storage size.





Persistence volume claims represent a request of storage, by specifying the size and the type of volume you need. 





For example:





kind: PersistentVolumeClaim
apiVersion: v1
metadata:
  name: local-pvc
spec:
  storageClassName: local-storage
  volumeName: local-pv
  accessModes:
   - ReadWriteOnce
  resources:
    requests:
      storage: 1Gi










Once the PVC is bound to a volume, the volume is available to the pods.





Run “kubectl get pv,pvc” and make sure that the pvc is bound:










Kubernetes looks for a pv that matches the volume claim requirements.





Once you have a persistence volume claim, you can add the dependency of the persistence volume in your Pod:





apiVersion: v1
kind: Pod
metadata:
  name: random-generator
spec:
  containers:
  - image: k8spatterns/random-generator:1.0
    name: random-generator
    volumeMounts:
    - mountPath: "/logs"
      name: log-volume
  volumes:
  - name: log-volume
    persistentVolumeClaim:                 
      claimName: local-pvc






If storageClassName is not specified in the PVC, the default storage class will be used for provisioning.





For more infos check:





https://kubernetes.io/blog/2017/03/dynamic-provisioning-and-storage-classes-kubernetes/







			

		

	






	

		

			

				

					Kubernetes – Using Helm
				

				

					 Posted on  					
Posted incloud , CONTAINERS , Kubernetes
									

			

			

				

The helm repo command helps you manage the repositories you have access to. After installation, you can see that you do not have access to any repository:





$ helm repo list





Error: no repositories to show










You can add a new repository with the command helm repo add, for example:





$ helm repo add bitnami https://charts.bitnami.com/bitnami





"bitnami" has been added to your repositories





If you check the list again, you can see the repo:





$ helm repo list





NAME     URL





Bitnami  https://charts.bitnami.com/bitnami










Now, you can install a chart from this repository:





$ helm install my-wp-install bitnami/wordpress[...]










Later, when a new version is released, you can upgrade your installation with the helm upgrade command 





$ helm upgrade my-wp-install bitnami/wordpress





Release "my-wp-install" has been upgraded. 





Happy Helming![...]










You can manage the history of the deployed revisions with helm history





$ helm history my-wp-install





If necessary, you can roll back to a previous release:





$ helm rollback my-wp-install 





You can uninstall the package with the helm uninstall command:





$ helm uninstall my-wp-install










GETTING READY FOR THE CKAD EXAM





If you take the CKAD exam, you might be asked to update an existing repo. It means that, before upgrading your installation, you should run:





$ helm repo update





Helm can be used as alternative to kubectl create. You can specify options for your deployments, like the replicaCount:





$ Helm -n mercury install internal-issue-report-apache bitnami/apache –-set replicaCount=2 –-set image.debug=true


			

		

	






	

		

			

				

					Kubernetes – Health checks with liveness and readiness probes
				

				

					 Posted on  					
Posted incloud , CONTAINERS , Kubernetes
									

			

			

				

Container probes allows you to test the health of your pods through a generic mechanism, that you can configure and execute according to your needs.





There are three types of probes:





  • exec – a command executing, expected to return 0 as exit value 
  • httpGet – a request expected to return 200
  • tcpSocket – for successful connectivity





And two categories:





  • liveness probe  – to check the health of the running application
  • readiness probe – to check if the application is ready to start working





Liveness probe





If you define a liveness probe, you basically will add a command to check if the pod is working as expected. If not, a restartPolicy can be defined.





The three types of  liveness probes are:





  • ExecAction: a command within the Pod to get a response. A result of anything other than 0 represents a failure.
  • TCPSocketAction: it consists of trying to open a socket, without doing anything else. If the socket opens, the probe is successful, and if it fails (after a timeout), the probe fails.
  • HTTPGetAction: Similar to the socket option, this makes an HTTP connection to your Pod as a URI specified, and the response code of the HTTP request is what is used to determine the success/failure of the liveness probe.





The restart Policy can have the following values





  • Always (default)
  • OnFailure
  • Never





The restartPolicy can be found under spec.template.spec:





apiVersion: batch/v1
kind: Deployment
metadata:
 name: my-dep
spec:
 template:
   metadata:
     name: my-dep-template
    spec:
     containers:
     - name: my-container
       image: busybox
       command: ["echo", "this is my container!"]
     restartPolicy: OnFailure





Kubernetes keeps track about how often a restart occurs and will slow down the frequency of restarts if they are happening in quick succession, capped at a maximum of five minutes between restart attempts.





The number of restarts can be inspected in the  “restartcount" in the output of kubectl describe, and also in the yaml file in the status section.





If you want to inspect the fields you can configure under “livenessProbe you can run:





$ k explain deployment.spec.template.spec.containers.livenessProbe















If you are using an HTTP-based probe, you have a number of additional variables that can be defined while making the HTTP request:





  • host: Defaults to the Pod IP address.
  • scheme: HTTP or https. Kubernetes 1.8 defaults to HTTP
  • path: Path of the URI request.
  • HttpHeaders: Any custom headers to be included in the request.
  • port: Port on which to make the HTTP request.





So a httpGet liveness probe might loook like





livenessProbe:
        httpGet:
          path: /checkalive
          port: 8888
          httpHeaders:
          - name: X-Custom-Header
            value: ItsAlive
        initialDelaySeconds: 30
        timeoutSeconds: 10





Readiness probe





Readiness probes are generally necessary if your container depends on other things that might be unavailable at the beginning (like a database service not started yet).





When a readiness probe fails for a container, the container’s pod will be removed from any service endpoint it is registered with. 





Here is a sample readiness probe with the “exec” command:





readinessProbe:
  exec:
    command:
        - /usr/local/bin/checkdb
        - --full-check
        - --data-service=my-data-service
  initialDelaySeconds: 60
  timeoutSeconds: 5






PUTTING THE PROBES IN THE MANIFEST





It is fine to have both a readiness probe and a liveness probe on the same container as they serve different purposes.





You can add them under spec.containers: 





apiVersion: apps/v1beta1
kind: Deployment
metadata:
  name: flask
  labels:
  run: flask
spec:
  template:
    metadata:
      labels:
        app: flask
    spec:
      containers:
      - name: flask
        image: quay.io/kubernetes-for-developers/flask:0.3.0
        imagePullPolicy: Always
        ports:
        - containerPort: 5000
        envFrom:
        - configMapRef:
          name: flask-config
        volumeMounts:
        - name: config
          mountPath: /etc/flask-config
          readOnly: true
        livenessProbe:
          httpGet:
            path: /alive
            port: 5000
          initialDelaySeconds: 1
          periodSeconds: 5
        readinessProbe:
          httpGet:
            path: /ready
            port: 5000
          initialDelaySeconds: 5
          periodSeconds: 5
        volumes:
        - name: config
          configMap:
            name: flask-config


			

		

	






	

		

			

				

					Kuberneting – Set, Rollout, apply… update!
				

				

					 Posted on  					
Posted incloud , CONTAINERS , Kubernetes
									

			

			

				

The imperative approach allows you to update things faster. 





In particular, the following commands: 





  • apply
  • scale
  • edit
  • set
  • rollout










APPLY





If you edi the yaml configuration file, you can update your resources by running:





$ kubectl apply -f yourfile.ymal










SCALE 





To change the amount of replicas: 





$ kubectl scale --replicas 3 deployment webapp





Kubernetes will rearrange the pods immediately. You will see pods being terminated and recreated right away,by running such command. 






EDIT





$ kubectl edit deployment/nginx-deployment










SET





The set command is used for frequent little updates.





For example a new imapge version for the pods:





$ kubectl set image deployment <deployment-name> <container-name>=nginx:1.12 --record 










If you omit “–record” the change-cause description will not be filled















To set resources:





$ kubectl set resources deployment nginx --limits=cpu=200m,memory=512Mi --requests=cpu=100m,memory=256Mi





This will apply to all the containers.










Set environmental variables in serval ways: 
$ kubectl set env deployment nginx --env VAR1=value1
$ kubectl set env deployment nginx --from=configmap/vars --keys="var1,var2"
$ kubectl set env deployment nginx --from=secret/passwords --keys="pass1





 





Afterwards, check the pods have the environmental variables:
$ kubectl exec -it <podname> bash -- -c "env | grep <varname>"










This will happen to your live resource. After running this command, the image will be updated  










ROLLOUT





The kubectl rollout command applies to a deployment. For example, to check the status:





check status:
$ kubectl rollout status deployment/test-deploy





To get the history of the deployment:





$ kubectl rollout history deployment flask

deployments "flask"
REVISION  CHANGE-CAUSE
1         initial deployment
2         kubectl set init container log-sidecar
3         deploying image 0.1.1
4         deploying image 0.2.0






If you annotate your deployment you will see the infomarion in the CHANGE-CAUSE column.










To rollback the deployment to the previous version:





$ kubectl rollout undo deployment/flask 










To roll it back to a specific revision: 





$ kubectl rollout undo deployment/flask --to-revision=2










Sometimes you don´t want to wait for the deployment to be recreated and you want to trigger it yourself. you can do it like:





$ kubectl rollout restart deploy my-deploy 







			

		

	







	
	



			
		

		

	

	            

                

                    

                        

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