Kubernetes

Kuerbernetes (k8s) is an open source container cluster manager. Kubernetes' primary goal is to provide a platform for automating deployment, scaling, and operations of application containers across a luster of hosts. Kubernetes was released by Google on July 2015.

1 Design overview
2 Components
3 Setup a Kubernetes cluster
4 Working with our Kubernetes cluster
5 Minikube
6 Volume management
7 ConfigMaps and Secrets
8 Ingress
9 Annotations
10 Jobs
11 Quota Management
12 Daemon Sets
13 Stateful Sets
14 Role Based Access Control (RBAC)
15 Federation
16 Helm
17 Monitoring and logging
18 Bash completion
19 External links

Design overview

Kubernetes is built through the definition of a set of components (building blocks or "primitives") which, when used collectively, provide a method for the deployment, maintenance, and scalability of container-based application clusters.

These "primitives" are designed to be loosely coupled (i.e., where little to no knowledge of the other component definitions is needed to use) as well as easily extensible through an API. Both the internal components of Kubernetes as well as the extensions and containers make use of this API.

Components

The building blocks of Kubernetes are the following (note that these are also referred to as Kubernetes "Objects" or "API Primitives"):

Cluster: A cluster is a set of machines (physical or virtual) on which your applications are managed and run. All machines are managed as a cluster (or set of clusters, depending on the topology used).
Nodes (minions): You can think of these as "container clients". These are the individual hosts (physical or virtual) that Docker is installed on and hosts the various containers within your managed cluster.; Each node will run etcd (a key-pair management and communication service, used by Kubernetes for exchanging messages and reporting on cluster status) as well as the Kubernetes Proxy.
Pods: A pod consists of one or more containers. Those containers are guaranteed (by the cluster controller) to be located on the same host machine (aka "co-located") in order to facilitate sharing of resources. For an example, it makes sense to have database processes and data containers as close as possible. In fact, they really should be in the same pod.; Pods "work together", like in a multi-tiered application configuration. Each set of pods that define and implement a service (like MySQL or Apache) are defined by the label selector.; Pods are assigned unique IPs within each cluster. These allow an application to use ports without having to worry about conflicting port utilization.; Pods can contain definitions of disk volumes or shares, and then provide access from those to all the members (containers) within the pod.; Finally, pod management is done through the API or delegated to a controller.
Labels: Clients can attach "key-value pairs" to any object in the system (like Pods or Nodes). These become the labels that identify them in the configuration and management of them. The key-value pairs can be used to filter, organize, and perform mass operations on a set of resources.
Selectors: Label Selectors represent queries that are made against those labels. They resolve to the corresponding matching objects. A Selector expression matches labels to filter certain resources. For example, you may want to search for all pods that belong to a certain service, or find all containers that have a specific tier Label value as "database". Labels and Selectors are inherently two sides of the same coin. You can use Labels to classify resources and use Selectors to find them and use them for certain actions.; These two items are the primary way that grouping is done in Kubernetes and determine which components that a given operation applies to when indicated.
Controllers: These are used in the management of your cluster. Controllers are the mechanism by which your desired configuration state is enforced.; Controllers manage a set of pods and, depending on the desired configuration state, may engage other controllers to handle replication and scaling (Replication Controller) of X number of containers and pods across the cluster. It is also responsible for replacing any container in a pod that fails (based on the desired state of the cluster).; Replication Controllers (RC) are a subset of Controllers and are an abstraction used to manage pod lifecycles. One of the key uses of RCs is to maintain a certain number of running Pods (e.g., for scaling or ensuring that at least one Pod is running at all times, etc.). It is considered a "best practice" to use RCs to define Pod lifecycles, rather than creating Pods directly.; Other controllers that can be engaged include a DaemonSet Controller (enforces a 1-to-1 ratio of pods to minions) and a Job Controller (that runs pods to "completion", such as in batch jobs).; Each set of pods any controller manages, is determined by the label selectors that are part of its definition.
Replica Sets: These define how many replicas of each Pod will be running. They also monitor and ensure the required number of Pods are running, replacing Pods that die. Replica Sets can act as replacements for Replication Controllers.
Services: A Service is an abstraction on top of Pods, which provides a single IP address and DNS name by which the Pods can be accessed. This load balancing configuration is much easier to manage and helps scale Pods seamlessly.; Kubernetes can then provide service discovery and handle routing with the static IP for each pod as well as load balancing (round robin based) connections to that service among the pods that match the label selector indicated.; By default, although a service is only exposed inside a cluster, it can also be exposed outside a cluster, as needed.
Volumes: A Volume is a directory with data, which is accessible to a container. The volume co-terminates with the Pods that encloses it.
Name: A name by which a resource is identified.
Namespace: A Namespace provides additional qualification to a resource name. This is especially helpful when multiple teams/projects are using the same cluster and there is a potential for name collision. You can think of a Namespace as a virtual wall between multiple clusters.
Annotations: An Annotation is a Label, but with much larger data capacity. Typically, this data is not readable by humans and is not easy to filter through. Annotation is useful only for storing data that may not be searched, but is required by the resource (e.g., storing strong keys, etc.).
Control Pane
API

Pods

A Pod is the smallest and simplest Kubernetes object. It is the unit of deployment in Kubernetes, which represents a single instance of the application. A Pod is a logical collection of one or more containers, which:

Are scheduled together on the same host
Share the same network namespace
Mount the same external storage (Volumes).

Pods are ephemeral in nature, and they do not have the capability to self-heal by themselves. That is why we use them with controllers, which can handle a Pod's replication, fault tolerance, self-heal, etc. Examples of controllers are Deployments, ReplicaSets, ReplicationControllers, etc. We attach the Pod's specification to other objects using Pod Templates (see below).

Labels

Labels are key-value pairs that can be attached to any Kubernetes object (e.g. Pods). Labels are used to organize and select a subset of objects, based on the requirements in place. Many objects can have the same label(s). Labels do not provide uniqueness to objects.

Label Selectors

With Label Selectors, we can select a subset of objects. Kubernetes supports two types of Selectors:

Equality-Based Selectors: Equality-Based Selectors allow filtering of objects based on label keys and values. With this type of Selectors, we can use the =, ==, or != operators. For example, with env==dev, we are selecting the objects where the "env" label is set to "dev".
Set-Based Selectors: Set-Based Selectors allow filtering of objects based on a set of values. With this type of Selectors, we can use the in, notin, and exist operators. For example, with env in (dev,qa), we are selecting objects where the "env" label is set to "dev" or "qa".

Replication Controllers

A ReplicationController (rc) is a controller that is part of the Master Node's Controller Manager. It makes sure the specified number of replicas for a Pod is running at any given point in time. If there are more Pods than the desired count, the ReplicationController would kill the extra Pods, and, if there are less Pods, then the ReplicationController would create more Pods to match the desired count. Generally, we do not deploy a Pod independently, as it would not be able to re-start itself, if something goes wrong. We always use controllers like ReplicationController to create and manage Pods.

Replica Sets

A ReplicaSet (rs) is the next-generation ReplicationController. ReplicaSets support both equality- and set-based Selectors, whereas ReplicationControllers only support equality-based Selectors. As of January 2018, this is the only difference.

As an example, say you create a ReplicaSet where you defined a "desired replicas = 3" (and set "current==desired"), any time "current!=desired" (i.e., one of the Pods dies) the ReplicaSet will detect that the current state is no longer matching the desired state. So, in our given scenario, the ReplicaSet will create one more Pod, thus ensuring that the current state matches the desired state.

ReplicaSets can be used independently, but they are mostly used by Deployments to orchestrate the Pod creation, deletion, and updates. A Deployment automatically creates the ReplicaSets, and we do not have to worry about managing them.

Deployments

Deployment objects provide declarative updates to Pods and ReplicaSets. The DeploymentController is part of the Master Node's Controller Manager, and it makes sure that the current state always matches the desired state.

As an example, let's say we have a Deployment which creates a "ReplicaSet A". ReplicaSet A then creates 3 Pods. In each Pod, one of the containers uses the nginx:1.7.9 image.

Now, in the Deployment, we change the Pod's template and we update the image for the Nginx container from nginx:1.7.9 to nginx:1.9.1. As we have modified the Pod's template, a new "ReplicaSet B" gets created. This process is referred to as a "Deployment rollout". (A rollout is only triggered when we update the Pod's template for a deployment. Operations like scaling the deployment do not trigger the deployment.) Once ReplicaSet B is ready, the Deployment starts pointing to it.

On top of ReplicaSets, Deployments provide features like Deployment recording, with which, if something goes wrong, we can rollback to a previously known state.

Namespaces

If we have numerous users whom we would like to organize into teams/projects, we can partition the Kubernetes cluster into sub-clusters using Namespaces. The names of the resources/objects created inside a Namespace are unique, but not across Namespaces.

To list all the Namespaces, we can run the following command:

$ kubectl get namespaces
NAME          STATUS    AGE
default       Active    2h
kube-public   Active    2h
kube-system   Active    2h

Generally, Kubernetes creates two default namespaces: kube-system and default. The kube-system namespace contains the objects created by the Kubernetes system. The default namespace contains the objects which belong to any other namespace. By default, we connect to the default Namespace. kube-public is a special namespace, which is readable by all users and used for special purposes, like bootstrapping a cluster.

Using Resource Quotas, we can divide the cluster resources within Namespaces.

Component services

The component services running on a standard master/node(s) Kubernetes setup are as follows:

Kubernetes Master
kube-apiserver

Exposes Kubernetes APIs

kube-controller-manager

Runs controllers to handle nodes, endpoints, etc.

kube-scheduler

Watches for new pods and assigns them nodes

etcd

Distributed key-value store

DNS

[optional] DNS for Kubernetes services
Nodes
kubelet

Manages pods on node, volumes, secrets, creating new containers, health checks, etc.

kube-proxy

Maintains network rules, port forwarding, etc.

Setup a Kubernetes cluster

In this section, I will show you how to setup a Kubernetes cluster with etcd and Docker. The cluster will consist of 1 master host and 3 minions (aka nodes).

Setup VMs

For this demo, I will be creating 4 VMs via Vagrant (with VirtualBox).

Create Vagrant demo environment:

$ mkdir $HOME/dev/kubernetes && cd $_

Create Vagrantfile with the following contents:

# -*- mode: ruby -*-
# vi: set ft=ruby :

require 'yaml'
VAGRANTFILE_API_VERSION = "2"

$common_script = <<COMMON_SCRIPT
# Set verbose
set -v
# Set exit on error
set -e
echo -e "$(date) [INFO] Starting modified Vagrant..."
sudo yum update -y
# Timestamp provision
date > /etc/vagrant_provisioned_at
COMMON_SCRIPT

unless defined? CONFIG
  configuration_file = File.join(File.dirname(__FILE__), 'vagrant_config.yml')
  CONFIG = YAML.load(File.open(configuration_file, File::RDONLY).read)
end

CONFIG['box'] = {} unless CONFIG.key?('box')

def modifyvm_network(node)
  node.vm.provider "virtualbox" do |vbox|
    vbox.customize ["modifyvm", :id, "--nicpromisc1", "allow-all"]
    #vbox.customize ["modifyvm", :id, "--natdnshostresolver1", "on"]
    vbox.customize ["modifyvm", :id, "--nicpromisc2", "allow-all"]
  end
end

def modifyvm_resources(node, memory, cpus)
  node.vm.provider "virtualbox" do |vbox|
    vbox.customize ["modifyvm", :id, "--memory", memory]
    vbox.customize ["modifyvm", :id, "--cpus", cpus]
  end
end

## START: Actual Vagrant process
Vagrant.configure(VAGRANTFILE_API_VERSION) do |config|

  config.vm.box = CONFIG['box']['name']

  # Uncomment the following line if you wish to be able to pass files from
  # your local filesystem directly into the vagrant VM:
  #config.vm.synced_folder "data", "/vagrant"

## VM: k8s master #############################################################
  config.vm.define "master" do |node|
    node.vm.hostname = "k8s.master.dev"
    node.vm.provision "shell", inline: $common_script
    #node.vm.network "forwarded_port", guest: 80, host: 8080
    node.vm.network "private_network", ip: CONFIG['host_groups']['master']

    # Uncomment the following if you wish to define CPU/memory:
    #node.vm.provider "virtualbox" do |vbox|
    #  vbox.customize ["modifyvm", :id, "--memory", "4096"]
    #  vbox.customize ["modifyvm", :id, "--cpus", "2"]
    #end
    #modifyvm_resources(node, "4096", "2")
  end
## VM: k8s minion1 ############################################################
  config.vm.define "minion1" do |node|
    node.vm.hostname = "k8s.minion1.dev"
    node.vm.provision "shell", inline: $common_script
    node.vm.network "private_network", ip: CONFIG['host_groups']['minion1']
  end
## VM: k8s minion2 ############################################################
  config.vm.define "minion2" do |node|
    node.vm.hostname = "k8s.minion2.dev"
    node.vm.provision "shell", inline: $common_script
    node.vm.network "private_network", ip: CONFIG['host_groups']['minion2']
  end
## VM: k8s minion3 ############################################################
  config.vm.define "minion3" do |node|
    node.vm.hostname = "k8s.minion3.dev"
    node.vm.provision "shell", inline: $common_script
    node.vm.network "private_network", ip: CONFIG['host_groups']['minion3']
  end
###############################################################################

end

The above Vagrantfile uses the following configuration file:

$ cat vagrant_config.yml

---
box:
  name: centos/7
  storage_controller: 'SATA Controller'
debug: false
development: false
network:
  dns1: 8.8.8.8
  dns2: 8.8.4.4
  internal:
    network: 192.168.200.0/24
  external:
    start: 192.168.100.100
    end: 192.168.100.200
    network: 192.168.100.0/24
    bridge: wlan0
    netmask: 255.255.255.0
    broadcast: 192.168.100.255
host_groups:
  master: 192.168.200.100
  minion1: 192.168.200.101
  minion2: 192.168.200.102
  minion3: 192.168.200.103

In the Vagrant Kubernetes directory (i.e., $HOME/dev/kubernetes), run the following command:

$ vagrant up

Setup hosts

Note: Run the following commands/steps on all hosts (master and minions).

Log into the k8s master host:

$ vagrant ssh master

Kubernetes cluster

$ cat << EOF >> /etc/hosts
192.168.200.100    k8s.master.dev
192.168.200.101    k8s.minion1.dev
192.168.200.102    k8s.minion2.dev
192.168.200.103    k8s.minion3.dev
EOF

Install, enable, and start NTP:

$ yum install -y ntp
$ systemctl enable ntpd && systemctl start ntpd
$ timedatectl

Disable any firewall rules (for now; we will add the rules back later):

$ systemctl stop firewalld && systemctl disable firewalld
$ systemctl stop iptables

Disable SELinux (for now; we will turn it on again later):

$ setenforce 0
$ sed -i 's/^SELINUX=.*/SELINUX=permissive/' /etc/sysconfig/selinux
$ sed -i 's/^SELINUX=.*/SELINUX=permissive/' /etc/selinux/config
$ sestatus

Add the Docker repo and update yum:

$ cat << EOF > /etc/yum.repos.d/virt7-docker-common-release.repo
[virt7-docker-common-release]
name=virr7-docker-common-release
baseurl=http://cbs.centos.org/repos/virt7-docker-common-release/x86_64/os/
gpgcheck=0
EOF
$ yum update

Install Docker, Kubernetes, and etcd:

$ yum install -y --enablerepo=virt7-docker-common-release kubernetes docker etcd

Install and configure master controller

Note: Run the following commands on only the master host.

Edit /etc/kubernetes/config and add (or make changes to) the following lines:

KUBE_MASTER="--master=http://k8s.master.dev:8080"
KUBE_ETCD_SERVERS="--etcd-servers=http://k8s.master.dev:2379"

Edit /etc/etcd/etcd.conf and add (or make changes to) the following lines:

[member]
ETCD_LISTEN_CLIENT_URLS="http://0.0.0.0:2379"
[cluster]
ETCD_ADVERTISE_CLIENT_URLS="http://0.0.0.0:2379"

Edit /etc/kubernetes/apiserver and add (or make changes to) the following lines:

# The address on the local server to listen to.
#KUBE_API_ADDRESS="--insecure-bind-address=127.0.0.1"
KUBE_API_ADDRESS="--address=0.0.0.0"

# The port on the local server to listen on.
KUBE_API_PORT="--port=8080"

# Port minions listen on
KUBELET_PORT="--kubelet-port=10250"

# Comma separated list of nodes in the etcd cluster
KUBE_ETCD_SERVERS="--etcd-servers=http://127.0.0.1:2379"

# Address range to use for services
KUBE_SERVICE_ADDRESSES="--service-cluster-ip-range=10.254.0.0/16"

# default admission control policies
#KUBE_ADMISSION_CONTROL="--admission-control=NamespaceLifecycle,NamespaceExists,LimitRanger,SecurityContextDeny,ServiceAccount,ResourceQuota"

# Add your own!
KUBE_API_ARGS=""

Enable and start the following etcd and Kubernetes services:

$ for SERVICE in etcd kube-apiserver kube-controller-manager kube-scheduler; do
      systemctl restart $SERVICE
      systemctl enable $SERVICE
      systemctl status $SERVICE 
  done

Check on the status of the above services (the following command should report 4 running services):

$ systemctl status etcd kube-apiserver kube-controller-manager kube-scheduler | grep "(running)" | wc -l # => 4

Check on the status of the Kubernetes API server:

$ kubectl cluster-info
Kubernetes master is running at http://localhost:8080
$ curl http://localhost:8080/version
#~OR~
$ curl http://k8s.master.dev:8080/version

{
  "major": "1",
  "minor": "2",
  "gitVersion": "v1.2.0",
  "gitCommit": "ec7364b6e3b155e78086018aa644057edbe196e5",
  "gitTreeState": "clean"
}

Get a list of Kubernetes API paths:

$ curl http://k8s.master.dev:8080/paths

{
  "paths": [
    "/api",
    "/api/v1",
    "/apis",
    "/apis/autoscaling",
    "/apis/autoscaling/v1",
    "/apis/batch",
    "/apis/batch/v1",
    "/apis/extensions",
    "/apis/extensions/v1beta1",
    "/healthz",
    "/healthz/ping",
    "/logs/",
    "/metrics",
    "/resetMetrics",
    "/swagger-ui/",
    "/swaggerapi/",
    "/ui/",
    "/version"
  ]
}

List all available paths (key-value stores) known to ectd:

$ etcdctl ls / --recursive

The master controller in a Kubernetes cluster must have the following services running to function as the master host in the cluster:

ntpd
etcd
kube-controller-manager
kube-apiserver
kube-scheduler

Note: The Docker daemon should not be running on the master host.

Install and configure the minions

Note: Run the following commands/steps on all minion hosts.

Log into the k8s minion hosts:

$ vagrant ssh minion1  # do the same for minion2 and minion3

Edit /etc/kubernetes/config and add (or make changes to) the following lines:

KUBE_MASTER="--master=http://k8s.master.dev:8080"
KUBE_ECTD_SERVERS="--etcd-servers=http://k8s.master.dev:2379"

Edit /etc/kubernetes/kubelet and add (or make changes to) the following lines:

###
# kubernetes kubelet (minion) config

# The address for the info server to serve on (set to 0.0.0.0 or "" for all interfaces)
KUBELET_ADDRESS="--address=0.0.0.0"

# The port for the info server to serve on
KUBELET_PORT="--port=10250"

# You may leave this blank to use the actual hostname
KUBELET_HOSTNAME="--hostname-override=k8s.minion1.dev"  # ***CHANGE TO CORRECT MINION HOSTNAME***

# location of the api-server
KUBELET_API_SERVER="--api-servers=http://k8s.master.dev:8080"

# pod infrastructure container
#KUBELET_POD_INFRA_CONTAINER="--pod-infra-container-image=registry.access.redhat.com/rhel7/pod-infrastructure:latest"

# Add your own!
KUBELET_ARGS=""

Enable and start the following services:

$ for SERVICE in kube-proxy kubelet docker; do
      systemctl restart $SERVICE
      systemctl enable $SERVICE
      systemctl status $SERVICE
  done

Test that Docker is running and can start containers:

$ docker info
$ docker pull hello-world
$ docker run hello-world

Each minion in a Kubernetes cluster must have the following services running to function as a member of the cluster (i.e., a "Ready" node):

ntpd
kubelet
kube-proxy
docker

Kubectl: Exploring our environment

Note: Run all of the following commands on the master host.

Get a list of nodes with kubectl:

$ kubectl get nodes

NAME              STATUS    AGE
k8s.minion1.dev   Ready     20m
k8s.minion2.dev   Ready     12m
k8s.minion3.dev   Ready     12m

Describe nodes with kubectl:

$ kubectl get nodes -o jsonpath='{.items[*].status.addresses[?(@.type=="ExternalIP")].address}'
$ kubectl get nodes -o jsonpath='{range .items[*]}{@.metadata.name}:{range @.status.conditions[*]}{@.type}={@.status};{end}{end}' | tr ';' "\n"

k8s.minion1.dev:OutOfDisk=False
Ready=True
k8s.minion2.dev:OutOfDisk=False
Ready=True
k8s.minion3.dev:OutOfDisk=False
Ready=True

Get the man page for kubectl:

$ man kubectl-get

Working with our Kubernetes cluster

Note: The following section will be working from within the Kubernetes cluster we created above.

Create and deploy pod definitions

Turn off nodes 1 and 2:

minion{1,2}$ systemctl stop kubelet kube-proxy

master$ kubectl get nodes

NAME              STATUS     AGE
k8s.minion1.dev   Ready      1h
k8s.minion2.dev   NotReady   37m
k8s.minion3.dev   NotReady   39m

Check for any k8s Pods (there should be none):

master$ kubectl get pods

Create a builds directory for our Pods:

master$ mkdir builds && cd $_

Create a Pod running Nginx inside a Docker container:

master$ kubectl create -f - <<EOF
---
apiVersion: v1
kind: Pod
metadata:
  name: nginx
spec:
  containers:
  - name: nginx
    image: nginx:1.7.9
    ports:
    - containerPort: 80
EOF

Check on Pod creation status:

master$ kubectl get pods

NAME      READY     STATUS              RESTARTS   AGE
nginx     0/1       ContainerCreating   0          2s

master$ kubectl get pods

NAME      READY     STATUS    RESTARTS   AGE
nginx     1/1       Running   0          3m

minion1$ docker ps

CONTAINER ID        IMAGE        COMMAND                 CREATED        STATUS        PORTS  NAMES
a718c6c0355d        nginx:1.7.9  "nginx -g 'daemon off"  3 minutes ago  Up 3 minutes         k8s_nginx.4580025_nginx_default_699e...

master$ kubectl describe pod nginx

master$ kubectl run busybox --image=busybox --restart=Never --tty -i --generator=run-pod/v1
busybox$ wget -qO- 172.17.0.2
master$ kubectl delete pod busybox
master$ kubectl delete pod nginx

Port forwarding:

master$ kubectl create -f nginx.yml  # see above for YAML
master$ kubectl port-forward nginx :80 &
I1020 23:12:29.478742   23394 portforward.go:213] Forwarding from [::1]:40065 -> 80
master$ curl -I localhost:40065

Tags, labels, and selectors

master$ cat << EOF > nginx-pod-label.yml
---
apiVersion: v1
kind: Pod
metadata:
  name: nginx
  labels:
    app: nginx
spec:
  containers:
  - name: nginx
    image: nginx:1.7.9
    ports:
    - containerPort: 80
EOF

master$ kubectl create -f nginx-pod-label.yml
master$ kubectl get pods -l app=nginx
master$ kubectl describe pods -l app=nginx2

Add labels or overwrite existing ones:

master$ kubectl label pods nginx new-label=mynginx
master$ kubectl describe pods/nginx | awk '/^Labels/{print $2}'
new-label=nginx
master$ kubectl label pods nginx new-label=foo
master$ kubectl describe pods/nginx | awk '/^Labels/{print $2}'
new-label=foo

Deployments

master$ cat << EOF > nginx-deployment-dev.yml
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: nginx-deployment-dev
spec:
  replicas: 1
  template:
    metadata:
      labels:
        app: nginx-deployment-dev
    spec:
      containers:
      - name: nginx-deployment-dev
        image: nginx:1.7.9
        ports:
        - containerPort: 80
EOF

master$ cat << EOF > nginx-deployment-prod.yml
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: nginx-deployment-prod
spec:
  replicas: 1
  template:
    metadata:
      labels:
        app: nginx-deployment-prod
    spec:
      containers:
      - name: nginx-deployment-prod
        image: nginx:1.7.9
        ports:
        - containerPort: 80
EOF

master$ kubectl create --validate -f nginx-deployment-dev.yml
master$ kubectl create --validate -f nginx-deployment-prod.yml

master$ kubectl get pods

NAME                                     READY     STATUS    RESTARTS   AGE
nginx-deployment-dev-104434401-jiiic     1/1       Running   0          5m
nginx-deployment-prod-3051195443-hj9b1   1/1       Running   0          12m

master$ kubectl describe deployments -l app=nginx-deployment-dev

Name:                   nginx-deployment-dev
Namespace:              default
CreationTimestamp:      Thu, 20 Oct 2016 23:48:46 +0000
Labels:                 app=nginx-deployment-dev
Selector:               app=nginx-deployment-dev
Replicas:               1 updated | 1 total | 1 available | 0 unavailable
StrategyType:           RollingUpdate
MinReadySeconds:        0
RollingUpdateStrategy:  1 max unavailable, 1 max surge
OldReplicaSets:         <none>
NewReplicaSet:          nginx-deployment-dev-2568522567 (1/1 replicas created)
...

master$ kubectl get deployments

NAME                    DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
nginx-deployment-prod   1         1         1            1           44s

master$ cat << EOF > nginx-deployment-dev-update.yml
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: nginx-deployment-dev
spec:
  replicas: 1
  template:
    metadata:
      labels:
        app: nginx-deployment-dev
    spec:
      containers:
      - name: nginx-deployment-dev
        image: nginx:1.8  # ***CHANGED***
        ports:
        - containerPort: 80
EOF

master$ kubectl apply -f nginx-deployment-dev-update.yml
master$ kubectl get pods -l app=nginx-deployment-dev

NAME                                   READY     STATUS              RESTARTS   AGE
nginx-deployment-dev-104434401-jiiic   0/1       ContainerCreating   0          27s

master$ kubectl get pods -l app=nginx-deployment-dev

NAME                                   READY     STATUS    RESTARTS   AGE
nginx-deployment-dev-104434401-jiiic   1/1       Running   0          6m

Cleanup:

master$ kubectl delete deployment nginx-deployment-dev
master$ kubectl delete deployment nginx-deployment-prod

Multi-Pod (container) replication controller

Start the other two nodes (the ones we previously stopped):

minion2$ systemctl start kubelet kube-proxy
minion3$ systemctl start kubelet kube-proxy
master$ kubectl get nodes

NAME              STATUS    AGE
k8s.minion1.dev   Ready     2h
k8s.minion2.dev   Ready     2h
k8s.minion3.dev   Ready     2h

master$ cat << EOF > nginx-multi-node.yml
---
apiVersion: v1
kind: ReplicationController
metadata:
  name: nginx-www
spec:
  replicas: 3
  selector:
    app: nginx
  template:
    metadata:
      name: nginx
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: nginx
        ports:
        - containerPort: 80
EOF

master$ kubectl create -f nginx-multi-node.yml

master$ kubectl get pods

NAME              READY     STATUS              RESTARTS   AGE
nginx-www-2evxu   0/1       ContainerCreating   0          10s
nginx-www-416ct   0/1       ContainerCreating   0          10s
nginx-www-ax41w   0/1       ContainerCreating   0          10s

master$ kubectl get pods

NAME              READY     STATUS    RESTARTS   AGE
nginx-www-2evxu   1/1       Running   0          1m
nginx-www-416ct   1/1       Running   0          1m
nginx-www-ax41w   1/1       Running   0          1m

master$ kubectl describe pods | awk '/^Node/{print $2}'

k8s.minion2.dev/192.168.200.102
k8s.minion1.dev/192.168.200.101
k8s.minion3.dev/192.168.200.103

minion1$ docker ps # 1 nginx container running
minion2$ docker ps # 1 nginx container running
minion3$ docker ps # 1 nginx container running
minion3$ docker ps --format "{{.Image}}"

nginx
gcr.io/google_containers/pause:2.0

master$ kubectl describe replicationcontroller

Name:       nginx-www
Namespace:  default
Image(s):   nginx
Selector:   app=nginx
Labels:     app=nginx
Replicas:   3 current / 3 desired
Pods Status:    3 Running / 0 Waiting / 0 Succeeded / 0 Failed
...

Attempt to delete one of the three pods:

master$ kubectl get pods

NAME              READY     STATUS    RESTARTS   AGE
nginx-www-2evxu   1/1       Running   0          11m
nginx-www-416ct   1/1       Running   0          11m
nginx-www-ax41w   1/1       Running   0          11m

master$ kubectl delete pod nginx-www-2evxu
master$ kubectl get pods

NAME              READY     STATUS    RESTARTS   AGE
nginx-www-3cck4   1/1       Running   0          12s
nginx-www-416ct   1/1       Running   0          11m
nginx-www-ax41w   1/1       Running   0          11m

A new pod (nginx-www-3cck4) automatically started up. This is because the expected state, as defined in our YAML file, is for there to be 3 pods running at all times. Thus, if one or more of the pods were to go down, a new pod (or pods) will automatically start up to bring the state back to the expected state.

To force-delete all pods:

master$ kubectl delete replicationcontroller nginx-www
master$ kubectl get pods  # nothing

Create and deploy service definitions

master$ cat << EOF > nginx-service.yml
---
apiVersion: v1
kind: Service
metadata:
  name: nginx-service
spec:
  ports:
  - port: 8000
    targetPort: 80
    protocol: TCP
  selector:
    app: nginx
EOF

master$ kubectl get services

NAME            CLUSTER-IP       EXTERNAL-IP   PORT(S)    AGE
kubernetes      10.254.0.1       <none>        443/TCP    3h

master$ kubectl create -f nginx-service.yml

master$ kubectl get services

NAME            CLUSTER-IP       EXTERNAL-IP   PORT(S)    AGE
kubernetes      10.254.0.1       <none>        443/TCP    3h
nginx-service   10.254.110.127   <none>        8000/TCP   10s

master$ kubectl run busybox --generator=run-pod/v1 --image=busybox --restart=Never --tty -i
busybox$ wget -qO- 10.254.110.127:8000  # works

Cleanup

master$ kubectl delete pod busybox
master$ kubectl delete service nginx-service
master$ kubectl get pods

NAME              READY     STATUS    RESTARTS   AGE
nginx-www-jh2e9   1/1       Running   0          13m
nginx-www-jir2g   1/1       Running   0          13m
nginx-www-w91uw   1/1       Running   0          13m

master$ kubectl delete replicationcontroller nginx-www
master$ kubectl get pods  # nothing

Creating temporary Pods at the CLI

Make sure we have no Pods running:

master$ kubectl get pods

Create temporary deployment pod:

master$ kubectl run mysample --image=foobar/apache
master$ kubectl get pods

NAME                        READY     STATUS              RESTARTS   AGE
mysample-1424711890-fhtxb   0/1       ContainerCreating   0          1s

master$ kubectl get deployment

NAME       DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
mysample   1         1         1            0           7s

Create a temporary deployment pod (where we know it will fail):

master$ kubectl run myexample --image=christophchamp/ubuntu_sysadmin
master$ kubectl -o wide get pods

NAME                         READY     STATUS             RESTARTS   AGE       NODE
myexample-3534121234-mpr35   0/1       CrashLoopBackOff   12         39m       k8s.minion3.dev
mysample-2812764540-74c5h    1/1       Running            0          41m       k8s.minion2.dev

Check on why the "myexample" pod is in status "CrashLoopBackOff":

master$ kubectl describe pods/myexample-3534121234-mpr35
master$ kubectl describe deployments/mysample
master$ kubectl describe pods/mysample-2812764540-74c5h | awk '/^Node/{print $2}'
k8s.minion2.dev/192.168.200.102

master$ kubectl delete deployment mysample

Run multiple replicas of the same pod:

master$ kubectl run myreplicas --image=latest123/apache --replicas=2 --labels=app=myapache,version=1.0.0
master$ kubectl describe deployment myreplicas

Name:           myreplicas
Namespace:      default
CreationTimestamp:  Fri, 21 Oct 2016 19:10:30 +0000
Labels:         app=myapache,version=1.0.0
Selector:       app=myapache,version=1.0.0
Replicas:       2 updated | 2 total | 1 available | 1 unavailable
StrategyType:       RollingUpdate
MinReadySeconds:    0
RollingUpdateStrategy:  1 max unavailable, 1 max surge
OldReplicaSets:     <none>
NewReplicaSet:      myreplicas-2209834598 (2/2 replicas created)
...

master$ kubectl get pods -o wide

NAME                          READY     STATUS             RESTARTS   AGE       NODE
myreplicas-2209834598-5iyer   1/1       Running            0          1m        k8s.minion1.dev
myreplicas-2209834598-cslst   1/1       Running            0          1m        k8s.minion2.dev

master$ kubectl describe pods -l version=1.0.0

Cleanup:

master$ kubectl delete deployment myreplicas

Interacting with Pod containers

Create example Apache pod definition file:

master$ cat << EOF > apache.yml
---
apiVersion: v1
kind: Pod
metadata:
  name: apache
spec:
  containers:
  - name: apache
    image: latest123/apache
    ports:
    - containerPort: 80
EOF

master$ kubectl create -f apache.yml
master$ kubectl get pods -o wide

NAME                          READY     STATUS    RESTARTS   AGE       NODE
apache                        1/1       Running   0          12m       k8s.minion3.dev

Test pod and make some basic configuration changes:

master$ kubectl exec apache date
master$ kubectl exec mypod -i -t -- cat /var/www/html/index.html  # default apache HTML
master$ kubectl exec apache -i -t -- /bin/bash
container$ export TERM=xterm
container$ echo "xtof test" > /var/www/html/index.html
minion3$ curl 172.17.0.2
xtof test
container$ exit

master$ kubectl get pods -o wide

NAME                          READY     STATUS    RESTARTS   AGE       NODE
apache                        1/1       Running   0          12m       k8s.minion3.dev

Pod/container is still running even after we exited (as expected).

Cleanup:

master$ kubectl delete pod apache

Logs

Start our example Apache pod to use for checking Kubernetes logging features:

master$ kubectl create -f apache.yml 
master$ kubectl get pods

NAME      READY     STATUS    RESTARTS   AGE
apache    1/1       Running   0          9s

master$ kubectl logs apache

AH00558: apache2: Could not reliably determine the server's fully qualified domain name, using 172.17.0.2. Set the 'ServerName' directive globally to suppress this message

master$ kubectl logs --tail=10 apache
master$ kubectl logs --since=24h apache  # or 10s, 2m, etc.
master$ kubectl logs -f apache  # follow the logs
master$ kubectl logs -f -c apache apache  # where -c is the container ID

Cleanup:

master$ kubectl delete pod apache

Autoscaling and scaling Pods

master$ kubectl run myautoscale --image=latest123/apache --port=80 --labels=app=myautoscale

master$ kubectl get pods -o wide

NAME                           READY     STATUS    RESTARTS   AGE       NODE
myautoscale-3243017378-kq4z7   1/1       Running   0          47s       k8s.minion3.dev

Create an autoscale definition:

master$ kubectl autoscale deployment myautoscale --min=2 --max=6 --cpu-percent=80

master$ kubectl get deployments

NAME          DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
myautoscale   2         2         2            2           4m

master$ kubectl get pods -o wide

NAME                           READY     STATUS    RESTARTS   AGE       NODE
myautoscale-3243017378-kq4z7   1/1       Running   0          3m        k8s.minion3.dev
myautoscale-3243017378-r2f3d   1/1       Running   0          4s        k8s.minion2.dev

Scale up an already autoscaled deployment:

master$ kubectl scale --current-replicas=2 --replicas=4 deployment/myautoscale

master$ kubectl get deployments

NAME          DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
myautoscale   4         4         4            4           8m

master$ kubectl get pods -o wide

NAME                           READY     STATUS    RESTARTS   AGE       NODE
myautoscale-3243017378-2rxhp   1/1       Running   0          8s        k8s.minion1.dev
myautoscale-3243017378-kq4z7   1/1       Running   0          7m        k8s.minion3.dev
myautoscale-3243017378-ozxs8   1/1       Running   0          8s        k8s.minion3.dev
myautoscale-3243017378-r2f3d   1/1       Running   0          4m        k8s.minion2.dev

Scale down:

master$ kubectl scale --current-replicas=4 --replicas=2 deployment/myautoscale

Note: You can not scale down past the original minimum number of pods/containers specified in the original autoscale deployment (i.e., min=2 in our example).

Cleanup:

master$ kubectl delete deployment myautoscale

Failure and recovery

master$ kubectl run myrecovery --image=latest123/apache --port=80 --replicas=2 --labels=app=myrecovery
master$ kubectl get deployments

NAME         DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
myrecovery   2         2         2            2           6s

master$ kubectl get pods -o wide

NAME                         READY     STATUS    RESTARTS   AGE       NODE
myrecovery-563119102-5xu8f   1/1       Running   0          12s       k8s.minion1.dev
myrecovery-563119102-zw6wp   1/1       Running   0          12s       k8s.minion2.dev

Now stop Kubernetes- and Docker-related services on one of the minions/nodes (so we have a total of 2 nodes online):

minion1$ systemctl stop docker kubelet kube-proxy

master$ kubectl get pods -o wide

NAME                         READY     STATUS    RESTARTS   AGE       NODE
myrecovery-563119102-qyi04   1/1       Running   0          7m        k8s.minion3.dev
myrecovery-563119102-zw6wp   1/1       Running   0          14m       k8s.minion2.dev

Pod switch from minion1 to minion3.

Now stop Kubernetes- and Docker-related services on one of the remaining online minions/nodes (so we have a total of 1 node online):

minion2$ systemctl stop docker kubelet kube-proxy
master$ kubectl get pods -o wide

NAME                         READY     STATUS    RESTARTS   AGE       NODE
myrecovery-563119102-b5tim   1/1       Running   0          2m        k8s.minion3.dev
myrecovery-563119102-qyi04   1/1       Running   0          17m       k8s.minion3.dev

Both Pods are now running on minion3, the only available node.

Start up Kubernetes- and Docker-related services again on minion1 and delete on of the Pods:

minion1$ systemctl start docker kubelet kube-proxy
master$ kubectl delete pod myrecovery-563119102-b5tim
master$ kubectl get pods -o wide

NAME                         READY     STATUS    RESTARTS   AGE       NODE
myrecovery-563119102-8unzg   1/1       Running   0          1m        k8s.minion1.dev
myrecovery-563119102-qyi04   1/1       Running   0          20m       k8s.minion3.dev

Pods are now running on separate nodes.

Cleanup:

master$ kubectl delete deployments/myrecovery

Minikube

Minikube is a tool that makes it easy to run Kubernetes locally. Minikube runs a single-node Kubernetes cluster inside a VM on your laptop for users looking to try out Kubernetes or develop with it day-to-day.

Install Minikube:

$ curl -Lo minikube https://storage.googleapis.com/minikube/releases/latest/minikube-linux-amd64 \
    && chmod +x minikube && sudo mv minikube /usr/local/bin/

Install kubectl

$ curl -Lo kubectl https://storage.googleapis.com/kubernetes-release/release/$(curl -s https://storage.googleapis.com/kubernetes-release/release/stable.txt)/bin/linux/amd64/kubectl \
    && chmod +x kubectl && sudo mv kubectl /usr/local/bin/

Test install

$ minikube start
$ minikube status
$ minikube dashboard
$ kubectl config view
$ kubectl cluster-info

Get the details on the CLI options for kubectl here.

Using the `kubectl proxy` command, kubectl will authenticate with the API Server on the Master Node and would make the dashboard available on http://localhost:8001/ui:

$ kubectl proxy
Starting to serve on 127.0.0.1:8001

After running the above command, we can access the dashboard at http://127.0.0.1:8001/ui.

Once the kubectl proxy is configured, we can send requests to localhost on the proxy port:

$ curl http://localhost:8001/
$ curl http://localhost:8001/version

{
  "major": "1",
  "minor": "8",
  "gitVersion": "v1.8.0",
  "gitCommit": "0b9efaeb34a2fc51ff8e4d34ad9bc6375459c4a4",
  "gitTreeState": "clean",
  "buildDate": "2017-11-29T22:43:34Z",
  "goVersion": "go1.9.1",
  "compiler": "gc",
  "platform": "linux/amd64"
}

Without kubectl proxy configured, we can get the Bearer Token using kubectl, and then send it with the API request. A Bearer Token is an access token which is generated by the authentication server (the API server on the Master Node) and given back to the client. Using that token, the client can connect back to the Kubernetes API server without providing further authentication details, and then, access resources.

Get the k8s token:

$ TOKEN=$(kubectl describe secret $(kubectl get secrets | awk '/^default/{print $1}') | awk '/^token/{print $2}')

Get the k8s API server endpoint:

$ APISERVER=$(kubectl config view | awk '/https/{print $2}')

Access the API Server:

$ curl -k -H "Authorization: Bearer ${TOKEN}" ${APISERVER}

Working with our Minikube-based Kubernetes cluster

Kubernetes Object Model

Kubernetes has a very rich object model, with which it represents different persistent entities in the Kubernetes cluster. Those entities describe:

What containerized applications we are running and on which node
Application resource consumption
Different policies attached to applications, like restart/upgrade policies, fault tolerance, etc.

With each object, we declare our intent or desired state using the spec field. The Kubernetes system manages the status field for objects, in which it records the actual state of the object. At any given point in time, the Kubernetes Control Plane tries to match the object's actual state to the object's desired state.

Examples of Kubernetes objects are Pods, Deployments, ReplicaSets, etc.

To create an object, we need to provide the spec field to the Kubernetes API Server. The spec field describes the desired state, along with some basic information, like the name. The API request to create the object must have the spec field, as well as other details, in a JSON format. Most often, we provide an object's definition in a YAML file, which is converted by kubectl in a JSON payload and sent to the API Server.

Below is an example of a Deployment object:

apiVersion: apps/v1 # for versions before 1.9.0 use apps/v1beta2
kind: Deployment
metadata:
  name: nginx-deployment
  labels:
    app: nginx
spec:
  replicas: 3
  selector:
    matchLabels:
      app: nginx
  template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: nginx:1.7.9
        ports:
        - containerPort: 80

With the apiVersion field in the example above, we mention the API endpoint on the API Server which we want to connect to. Note that you can see what API version to use with the following call to the API server:

$ curl -k -H "Authorization: Bearer ${TOKEN}" ${APISERVER}/apis/apps

Use the preferredVersion for most cases.

With the kind field, we mention the object type — in our case, we have Deployment. With the metadata field, we attach the basic information to objects, like the name. You may have noticed that in above we have two spec fields (spec and spec.template.spec). With spec, we define the desired state of the deployment. In our example, we want to make sure that, at any point in time, at least 3 Pods are running, which are created using the Pod template defined in spec.template. In spec.template.spec, we define the desired state of the Pod (here, our Pod would be created using nginx:1.7.9).

Once the object is created, the Kubernetes system attaches the status field to the object.

Connecting users to Pods

To access the application, a user/client needs to connect to the Pods. As Pods are ephemeral in nature, resources like IP addresses allocated to it cannot be static. Pods could die abruptly or be rescheduled based on existing requirements.

As an example, consider a scenario in which a user/client is connection to a Pod using its IP address. Unexpectedly, the Pot to which the user/client is connected dies, and a new Pod is created by the controller. The new Pod will have a new IP address, which will not be known automatically to the user/client of the earlier Pod. To overcome this situation, Kubernetes provides a higher-level abstraction called Service, which logically groups Pods and a policy to access them. This grouping is achieved via Labels and Selectors (see above).

So, for our example, we would use Selectors (e.g., "app==frontend" and "app==db") to group our Pods into two logical groups. We can assign a name to the logical grouping, referred to as a "service name". In our example, we have created two Services, frontend-svc and db-svc, and they have the "app==frontend" and the "app==db" Selectors, respectively.

The following is an example of a Service object:

kind: Service
apiVersion: v1
metadata:
  name: frontend-svc
spec:
  selector:
    app: frontend
  ports:
    - protocol: TCP
      port: 80
      targetPort: 5000

in which we are creating a frontend-svc Service by selecting all the Pods that have the Label "app" set to the "frontend". By default, each Service also gets an IP address, which is routable only inside the cluster. In our case, we have 172.17.0.4 and 172.17.0.5 IP addresses for our frontend-svc and db-svc Services, respectively. The IP address attached to each Service is also known as the ClusterIP for that Service.

+------------------------------------+
| select: app==frontend              |          container (app:frontend; 10.0.1.3)
|  service=frontend-svc (172.17.0.4) |------>   container (app:frontend; 10.0.1.4)
+------------------------------------+          container (app:frontend; 10.0.1.5)
              ^
             /
            /
user/client
            \
             \
              v
+------------------------------------+
| select: app==db                    |------>   container (app:db; 10.0.1.10)
|  service=db-svc (172.17.0.5)       |
+------------------------------------+

The user/client now connects to a Service via the IP address, which forwards the traffic to one of the Pods attached to it. A Service does the load balancing while selecting the Pods for forwarding the data/traffic.

While forwarding the traffic from the Service, we can select the target port on the Pod. In our example, for frontend-svc, we will receive requests from the user/client on Port 80. We will then forward these requests to one of the attached Pods on Port 5000. If the target port is not defined explicitly, then traffic will be forwarded to Pods on the Port on which the Service receives traffic.

A tuple of Pods, IP addresses, along with the targetPort is referred to as a Service Endpoint. In our case, frontend-svc has 3 Endpoints: 10.0.1.3:5000, 10.0.1.4:5000, and 10.0.1.5:5000.

kube-proxy

All of the Worker Nodes run a daemon called kube-proxy, which watches the API Server on the Master Node for the addition and removal of Services and endpoints. For each new Service, on each node, kube-proxy configures the IPtables rules to capture the traffic for its ClusterIP and forwards it to one of the endpoints. When the Service is removed, kube-proxy removes the IPtables rules on all nodes as well.

Service discovery

As Services are the primary mode of communication in Kubernetes, we need a way to discover them at runtime. Kubernetes supports two methods of discovering a Service:

Environment Variables: As soon as the Pod starts on any Worker Node, the kubelet daemon running on that node adds a set of environment variables in the Pod for all active Services. For example, if we have an active Service called redis-master, which exposes port 6379, and its ClusterIP is 172.17.0.6, then, on a newly created Pod, we can see the following environment variables:

REDIS_MASTER_SERVICE_HOST=172.17.0.6
REDIS_MASTER_SERVICE_PORT=6379
REDIS_MASTER_PORT=tcp://172.17.0.6:6379
REDIS_MASTER_PORT_6379_TCP=tcp://172.17.0.6:6379
REDIS_MASTER_PORT_6379_TCP_PROTO=tcp
REDIS_MASTER_PORT_6379_TCP_PORT=6379
REDIS_MASTER_PORT_6379_TCP_ADDR=172.17.0.6

With this solution, we need to be careful while ordering our Services, as the Pods will not have the environment variables set for Services which are created after the Pods are created.

DNS: Kubernetes has an add-on for DNS, which creates a DNS record for each Service and its format is like my-svc.my-namespace.svc.cluster.local. Services within the same namespace can reach to other services with just their name. For example, if we add a Service redis-master in the my-ns Namespace, then all the Pods in the same Namespace can reach to the redis Service just by using its name, redis-master. Pods from other Namespaces can reach the Service by adding the respective Namespace as a suffix, like redis-master.my-ns.; This is the most common and highly recommended solution. For example, in the previous section's image, we have seen that an internal DNS is configured, which maps our services frontend-svc and db-svc to 172.17.0.4 and 172.17.0.5, respectively.

Service Type

While defining a Service, we can also choose its access scope. We can decide whether the Service:

Is only accessible within the cluster;
Is accessible from within the cluster and the external world; or
Maps to an external entity which resides outside the cluster.

Access scope is decided by ServiceType, which can be mentioned when creating the Service.

ClusterIP: the default ServiceType. A Service gets its Virtual IP address using the ClusterIP. That IP address is used for communicating with the Service and is accessible only within the cluster.

NodePort: With this ServiceType, in addition to creating a ClusterIP, a port from the range 30000-32767 is mapped to the respective service, from all the Worker Nodes. For example, if the mapped NodePort is 32233 for the service frontend-svc, then, if we connect to any Worker Node on port 32233, the node would redirect all the traffic to the assigned ClusterIP (172.17.0.4).; By default, while exposing a NodePort, a random port is automatically selected by the Kubernetes Master from the port range 30000-32767. If we do not want to assign a dynamic port value for NodePort, then, while creating the Service, we can also give a port number from the earlier specific range.; The NodePort ServiceType is useful when we want to make our services accessible from the external world. The end-user connects to the Worker Nodes on the specified port, which forwards the traffic to the applications running inside the cluster. To access the application from the external world, administrators can configure a reverse proxy outside the Kubernetes cluster and map the specific endpoint to the respective port on the Worker Nodes.

LoadBalancer

With this ServiceType, we have the following:

NodePort and ClusterIP Services are automatically created, and the external load balancer will route to them;
The Services are exposed at a static port on each Worker Node; and
The Service is exposed externally using the underlying Cloud provider's load balancer feature.

The LoadBalancer ServiceType will only work if the underlying infrastructure supports the automatic creation of Load Balancers and have the respective support in Kubernetes, as is the case with the Google Cloud Platform and AWS.

ExternalIP: A Service can be mapped to an ExternalIP address if it can route to one or more of the Worker Nodes. Traffic that is ingressed into the cluster with the ExternalIP (as destination IP) on the Service port, gets routed to one of the the Service endpoints. (Note that ExternalIPs are not managed by Kubernetes. The cluster administrators has configured the routing to map the ExternalIP address to one of the nodes.)

ExternalName: a special ServiceType, which has no Selectors and does not define any endpoints. When accessed within the cluster, it returns a CNAME record of an externally configured service.; The primary use case of this ServiceType is to make externally configured services like my-database.example.com available inside the cluster, using just the name, like my-database, to other services inside the same Namespace.

Deploying a application

$ kubectl create -f - <<EOF
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: webserver
spec:
  replicas: 3
  template:
    metadata:
      labels:
        app: webserver
    spec:
      containers:
      - name: webserver
        image: nginx:alpine
        ports:
        - containerPort: 80
EOF

$ kubectl create -f - <<EOF
apiVersion: v1
kind: Service
metadata:
  name: web-service
  labels:
    run: web-service
spec:
  type: NodePort
  ports:
  - port: 80
    protocol: TCP
  selector:
    app: webserver
EOF

$ kubectl get service
NAME          TYPE        CLUSTER-IP       EXTERNAL-IP   PORT(S)        AGE
kubernetes    ClusterIP   10.96.0.1        <none>        443/TCP        6h
web-service   NodePort    10.104.107.132   <none>        80:32610/TCP   7m

Note that "32610" port.

Get the IP address of your Minikube k8s cluster

$ minikube ip
192.168.99.100

Now, check that your web service is serving up a default Nginx website:

$ curl -I http://192.168.99.100:32610
HTTP/1.1 200 OK
Server: nginx/1.13.8
Date: Thu, 11 Jan 2018 00:27:51 GMT
Content-Type: text/html
Content-Length: 612
Last-Modified: Wed, 10 Jan 2018 04:10:03 GMT
Connection: keep-alive
ETag: "5a55921b-264"
Accept-Ranges: bytes

Looks good!

Finally, destroy the webserver deployment:

$ kubectl delete deployments webserver

Volume management

On-disk files in a container are ephemeral, which presents some problems for non-trivial applications when running in containers. First, when a container crashes, kubelet will restart it, but the files will be lost - the container starts with a clean state. Second, when running containers together in a Pod it is often necessary to share files between those containers. The Kubernetes Volumes abstraction solves both of these problems. A Volume is essentially a directory backed by a storage medium. The storage medium and its content are determined by the Volume Type.

In Kubernetes, a Volume is attached to a Pod and shared among the containers of that Pod. The Volume has the same life span as the Pod, and it outlives the containers of the Pod - this allows data to be preserved across container restarts.

Kubernetes resolves the problem of persistent storage with the Persistent Volume subsystem, which provides APIs for users and administrators to manage and consume storage. To manage the Volume, it uses the PersistentVolume (PV) API resource type, and to consume it, it uses the PersistentVolumeClaim (PVC) API resource type.

A Persistent Volume is a network attached storage in the cluster, which is provisioned by the administrator.

Persistent Volumes can be provisioned statically by the administrator, or dynamically, based on the StorageClass resource. A StorageClass contains pre-defined provisioners and parameters to create a Persistent Volume.

A PersistentVolumeClaim (PVC) is a request for storage by a user. Users request Persistent Volume resources based on size, access modes, etc. Once a suitable Persistent Volume is found, it is bound to a Persistent Volume Claim. After a successful bind, the PersistentVolumeClaim resource can be used in a Pod. Once a user finishes its work, the attached Persistent Volumes can be released. The underlying Persistent Volumes can then be reclaimed and recycled for future usage. See Persistent Volumes for details.

As an example of how to use volumes, we can modify our previous "webserver" Deployment (see above) to look like the following:

$ cat webserver.yml

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: webserver
spec:
  replicas: 3
  template:
    metadata:
      labels:
        app: webserver
    spec:
      containers:
      - name: webserver
        image: nginx:alpine
        ports:
        - containerPort: 80
        volumeMounts:
        - name: hostvol
          mountPath: /usr/share/nginx/html
      volumes:
      - name: hostvol
        hostPath:
          path: /home/docker/vol

And use the same Service:

$ cat webserver-svc.yml

apiVersion: v1
kind: Service
metadata:
  name: web-service
  labels:
    run: web-service
spec:
  type: NodePort
  ports:
  - port: 80
    protocol: TCP
  selector:
    app: webserver

Then create the deployment:

$ kubectl create -f webserver.yml
$ kubectl create -f webserver-svc.yml

Then, SSH into the webserver and run the following commands

$ minikube ssh
minikube> mkdir -p /home/docker/vol
minikube> echo "Christoph testing" > /home/docker/vol/index.html
minikube> exit

Get the webserver IP and port:

$ minikube ip
192.168.99.100
$ kubectl get svc/web-service -o json | jq '.spec.ports[].nodePort'
32610
# OR
$ minikube service web-service --url
http://192.168.99.100:32610

$ curl http://192.168.99.100:32610
Christoph testing

ConfigMaps and Secrets

While deploying an application, we may need to pass such runtime parameters like configuration details, passwords, etc. For example, let's assume we need to deploy ten different applications for our customers, and, for each customer, we just need to change the name of the company in the UI. Then, instead of creating ten different Docker images for each customer, we may just use the template image and pass the customers' names as a runtime parameter. In such cases, we can use the ConfigMap API resource. Similarly, when we want to pass sensitive information, we can use the Secret API resource.

ConfigMaps allow you to decouple configuration artifacts from image content to keep containerized applications portable. Using ConfigMaps, we can pass configuration details as key-value pairs, which can be later consumed by Pods, or any other system components, such as controllers. We can create ConfigMaps in two ways:

From literal values; and
From files.

ConfigMaps

Create a ConfigMap:

$ kubectl create configmap my-config --from-literal=key1=value1 --from-literal=key2=value2
configmap "my-config" created
$ kubectl get configmaps my-config -o yaml

apiVersion: v1
data:
  key1: value1
  key2: value2
kind: ConfigMap
metadata:
  creationTimestamp: 2018-01-11T23:57:44Z
  name: my-config
  namespace: default
  resourceVersion: "117110"
  selfLink: /api/v1/namespaces/default/configmaps/my-config
  uid: 37a43e39-f72b-11e7-8370-08002721601f

$ kubectl describe configmap/my-config

Name:         my-config
Namespace:    default
Labels:       <none>
Annotations:  <none>

Data
====
key2:
----
value2
key1:
----
value1
Events:  <none>

Create a ConfigMap from a configuration file

$ cat <<EOF | kubectl create -f -
apiVersion: v1
kind: ConfigMap
metadata:
  name: customer1
data:
  TEXT1: Customer1_Company
  TEXT2: Welcomes You
  COMPANY: Customer1 Company Technology, LLC.
EOF

We can get the values of the given key as environment variables inside a Pod. In the following example, while creating the Deployment, we are assigning values for environment variables from the customer1 ConfigMap:

....
 containers:
      - name: my-app
        image: foobar
        env:
        - name: MONGODB_HOST
          value: mongodb
        - name: TEXT1
          valueFrom:
            configMapKeyRef:
              name: customer1
              key: TEXT1
        - name: TEXT2
          valueFrom:
            configMapKeyRef:
              name: customer1
              key: TEXT2
        - name: COMPANY
          valueFrom:
            configMapKeyRef:
              name: customer1
              key: COMPANY

....

With the above, we will get the TEXT1 environment variable set to Customer1_Company, TEXT2 environment variable set to Welcomes You, and so on.

We can mount a ConfigMap as a Volume inside a Pod. For each key, we will see a file in the mount path and the content of that file become the respective key's value. For details, see here.

Secrets

Objects of type secret are intended to hold sensitive information, such as passwords, OAuth tokens, and ssh keys. Putting this information in a secret is safer and more flexible than putting it verbatim in a pod definition or in a docker image.

As an example, assume that we have a Wordpress blog application, in which our wordpress frontend connects to the MySQL database backend using a password. While creating the Deployment for wordpress, we can put down the MySQL password in the Deployment's YAML file, but the password would not be protected. The password would be available to anyone who has access to the configuration file.

In situations such as the one we just mentioned, the Secret object can help. With Secrets, we can share sensitive information like passwords, tokens, or keys in the form of key-value pairs, similar to ConfigMaps; thus, we can control how the information in a Secret is used, reducing the risk for accidental exposures. In Deployments or other system components, the Secret object is referenced, without exposing its content.

It is important to keep in mind that the Secret data is stored as plain text inside etcd. Administrators must limit the access to the API Server and etcd.

To create a Secret using the kubectl create secret command, we need to first create a file with a password, and then pass it as an argument.

Create a file with your MySQL password:

$ echo mysqlpasswd | tr -d '\n' > password.txt

Create the Secret:

$ kubectl create secret generic mysql-passwd --from-file=password.txt
$ kubectl describe secret/mysql-passwd

Name:         mysql-passwd
Namespace:    default
Labels:       <none>
Annotations:  <none>

Type:  Opaque

Data
====
password.txt:  11 bytes

We can also create a Secret manually, using the YAML configuration file. With Secrets, each object data must be encoded using base64. If we want to have a configuration file for our Secret, we must first get the base64 encoding for our password:

$ cat password.txt | base64
bXlzcWxwYXNzd2Q==

and then use it in the configuration file:

apiVersion: v1
kind: Secret
metadata:
  name: mysql-passwd
type: Opaque
data:
  password: bXlzcWxwYXNzd2Q=

Note that base64 encoding does not do any encryption and anyone can easily decode it:

$ echo "bXlzcWxwYXNzd2Q=" | base64 -d

Therefore, make sure you do not commit a Secret's configuration file in the source code.

We can get Secrets to be used by containers in a Pod by mounting them as data volumes, or by exposing them as environment variables.

We can reference a Secret and assign the value of its key as an environment variable (WORDPRESS_DB_PASSWORD):

.....
    spec:
      containers:
      - image: wordpress:4.7.3-apache
        name: wordpress
        env:
        - name: WORDPRESS_DB_HOST
          value: wordpress-mysql
        - name: WORDPRESS_DB_PASSWORD
          valueFrom:
            secretKeyRef:
              name: my-password
              key: password.txt
.....

Or, we can also mount a Secret as a Volume inside a Pod. A file would be created for each key mentioned in the Secret, whose content would be the respective value. See here for details.

Ingress

Among the ServiceTypes mentioned in that chapter, NodePort and LoadBalancer are the most often used. For the LoadBalancer ServiceType, we need to have the support from the underlying infrastructure. Even after having the support, we may not want to use it for every Service, as LoadBalancer resources are limited and they can increase costs significantly. Managing the NodePort ServiceType can also be tricky at times, as we need to keep updating our proxy settings and keep track of the assigned ports. In this chapter, we will explore the Ingress, which is another method we can use to access our applications from the external world.

An Ingress is a collection of rules that allow inbound connections to reach the cluster Services. With Services, routing rules are attached to a given Service. They exist for as long as the Service exists. If we can somehow decouple the routing rules from the application, we can then update our application without worrying about its external access. This can be done using the Ingress resource.

To allow the inbound connection to reach the cluster Services, Ingress configures a Layer 7 HTTP load balancer for Services and provides the following:

TLS (Transport Layer Security)
Name-based virtual hosting
Path-based routing
Custom rules.

With Ingress, users do not connect directly to a Service. Users reach the Ingress endpoint, and, from there, the request is forwarded to the respective Service. You can see an example of a sample Ingress definition below:

apiVersion: extensions/v1beta1
kind: Ingress
metadata:
  name: web-ingress
spec:
  rules:
  - host: blue.example.com
    http:
      paths:
      - backend: 
          serviceName: blue-service
          servicePort: 80
  - host: green.example.com
    http:
      paths:
      - backend:
          serviceName: green-service
          servicePort: 80

According to the example we provided, users requests to both blue.example.com and green.example.com would go to the same Ingress endpoint, and, from there, they would be forwarded to blue-service, and green-service, respectively. Here, we have seen an example of a Name-Based Virtual Hosting Ingress rule.

We can also have Fan Out Ingress rules, in which we send requests like example.com/blue and example.com/green, which would be forwarded to blue-service and green-service, respectively.

The Ingress resource does not do any request forwarding by itself. All of the magic is done using the Ingress Controller.

Ingress Controller

An Ingress Controller is an application which watches the Master Node's API Server for changes in the Ingress resources and updates the Layer 7 load balancer accordingly. Kubernetes has different Ingress Controllers, and, if needed, we can also build our own. GCE L7 Load Balancer and Nginx Ingress Controller are examples of Ingress Controllers.

Minikube v0.14.0 and above ships the Nginx Ingress Controller setup as an add-on. It can be easily enabled by running the following command:

$ minikube addons enable ingress

Once the Ingress Controller is deployed, we can create an Ingress resource using the kubectl create command. For example, if we create a example-ingress.yml file with the content above, then, we can use the following command to create an Ingress resource:

$ kubectl create -f example-ingress.yml

With the Ingress resource we just created, we should now be able to access the blue-service or green-service services using blue.example.com and green.example.com URLs. As our current setup is on minikube, we will need to update the host configuration file on our workstation to the minikube's IP for those URLs:

$ cat /etc/hosts
127.0.0.1        localhost
::1              localhost
192.168.99.100   blue.example.com green.example.com

Once this is done, we can now open blue.example.com and green.example.com in a browser and access the application.

Annotations

With Annotations, we can attach arbitrary non-identifying metadata to objects, in a key-value format:

"annotations": {
  "key1" : "value1",
  "key2" : "value2"
}

The metadata in an annotation can be small or large, structured or unstructured, and can include characters not permitted by labels.

In contrast to Labels, annotations are not used to identify and select objects. Annotations can be used to:

Store build/release IDs, which git branch, etc.
Phone numbers of persons responsible, or directory entries specifying where such information can be found
Pointers to logging, monitoring, analytics, audit repositories, debugging tools, etc.
Etc.

For example, while creating a Deployment, we can add a description like the one below:

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: webserver
  annotations:
    description: Deployment based PoC dates 12 January 2018
....
....

We can look at annotations while describing an object:

$ kubectl describe deployment webserver
Name:                webserver
Namespace:           default
CreationTimestamp:   Fri, 12 Jan 2018 13:18:23 -0800
Labels:              app=webserver
Annotations:         deployment.kubernetes.io/revision=1
                     description=Deployment based PoC dates 12 January 2018
...
...

Jobs

A job creates one or more pods and ensures that a specified number of them successfully terminate. As pods successfully complete, the job tracks the successful completions. When a specified number of successful completions is reached, the job itself is complete. Deleting a Job will cleanup the pods it created.

A simple case is to create one Job object in order to reliably run one Pod to completion. The Job object will start a new Pod if the first pod fails or is deleted (for example due to a node hardware failure or a node reboot).

A Job can also be used to run multiple pods in parallel.

Example: Here is an example Job config. It computes π to 2000 places and prints it out. It takes around 10s to complete.

apiVersion: batch/v1
kind: Job
metadata:
  name: pi
spec:
  template:
    spec:
      containers:
      - name: pi
        image: perl
        command: ["perl",  "-Mbignum=bpi", "-wle", "print bpi(2000)"]
      restartPolicy: Never
  backoffLimit: 4

$ kubctl create -f ./job-pi.yml
job "pi" created
$ kubectl describe jobs/pi

Name:           pi
Namespace:      default
Selector:       controller-uid=19aa42d0-f7df-11e7-8370-08002721601f
Labels:         controller-uid=19aa42d0-f7df-11e7-8370-08002721601f
                job-name=pi
Annotations:    <none>
Parallelism:    1
Completions:    1
Start Time:     Fri, 12 Jan 2018 13:25:23 -0800
Pods Statuses:  1 Running / 0 Succeeded / 0 Failed
Pod Template:
  Labels:  controller-uid=19aa42d0-f7df-11e7-8370-08002721601f
           job-name=pi
  Containers:
   pi:
    Image:  perl
    Port:   <none>
    Command:
      perl
      -Mbignum=bpi
      -wle
      print bpi(2000)
    Environment:  <none>
    Mounts:       <none>
  Volumes:        <none>
Events:
  Type    Reason            Age   From            Message
  ----    ------            ----  ----            -------
  Normal  SuccessfulCreate  8s    job-controller  Created pod: pi-rfvvw

$ pods=$(kubectl get pods  --show-all --selector=job-name=pi --output=jsonpath={.items..metadata.name})
$ echo $pods
pi-rfvvw
$ kubectl logs $pods
3.1415926535897932384626433832795028841971693...

Cron Jobs

Support for creating Jobs at specified times/dates (i.e. cron) is available in Kubernetes 1.4. See here for details.

$ kubectl create -f cronjob.yml
cronjob "hello" created
$ kubectl get cronjob hello
NAME      SCHEDULE      SUSPEND   ACTIVE    LAST SCHEDULE   AGE
hello     */1 * * * *   False     0         <none>          11s
$ kubectl get jobs --watch
NAME               DESIRED   SUCCESSFUL   AGE
hello-1515793140   1         1            7s
$ kubectl get cronjob hello
NAME      SCHEDULE      SUSPEND   ACTIVE    LAST SCHEDULE   AGE
hello     */1 * * * *   False     0         22s             48s
$ pods=$(kubectl get pods -a --selector=job-name=hello-1515793140 --output=jsonpath={.items..metadata.name})
$ echo $pods
hello-1515793140-plp8g
$ kubectl logs $pods
Fri Jan 12 21:39:07 UTC 2018
Hello from the Kubernetes cluster
$ kubectl delete cronjob hello

Quota Management

When there are many users sharing a given Kubernetes cluster, there is always a concern for fair usage. To address this concern, administrators can use the ResourceQuota] object, which provides constraints that limit aggregate resource consumption per Namespace.

We can have the following types of quotas per Namespace:

Compute Resource Quota: We can limit the total sum of compute resources (CPU, memory, etc.) that can be requested in a given Namespace.
Storage Resource Quota: We can limit the total sum of storage resources (persistentvolumeclaims, requests.storage, etc.) that can be requested.
Object Count Quota: We can restrict the number of objects of a given type (pods, ConfigMaps, persistentvolumeclaims, ReplicationControllers, Services, Secrets, etc.).

Daemon Sets

In some cases, like collecting monitoring data from all nodes, or running a storage daemon on all nodes, etc., we need a specific type of Pod running on all nodes at all times. A DaemonSet is the object that allows us to do just that.

Whenever a node is added to the cluster, a Pod from a given DaemonSet is created on it. When the node dies, the respective Pods are garbage collected. If a DaemonSet is deleted, all Pods it created are deleted as well.

Stateful Sets

The StatefulSet controller is used for applications which require a unique identity, such as name, network identifications, strict ordering, etc. For example, MySQL cluster, etcd cluster.

The StatefulSet controller provides identity and guaranteed ordering of deployment and scaling to Pods.

Note: Before Kubernetes 1.5, the StatefulSet controller was referred to as PetSet.

Role Based Access Control (RBAC)

Role-based access control] (RBAC) is an authorization mechanism for managing permissions around Kubernetes resources.

Using the RBAC API, we define a role which contains a set of additive permissions. Within a Namespace, a role is defined using the Role object. For a cluster-wide role, we need to use the ClusterRole object.

Once the roles are defined, we can bind them to a user or a set of users using RoleBinding and ClusterRoleBinding.

Federation

With the Kubernetes Cluster Federation we can manage multiple Kubernetes clusters from a single control plane. We can sync resources across the clusters, and have cross cluster discovery. This allows us to do Deployments across regions and access them using a global DNS record.

The Federation is very useful when we want to build a hybrid solution, in which we can have one cluster running inside our private datacenter and another one on the public cloud. We can also assign weights for each cluster in the Federation, to distribute the load as per our choice.

Helm

To deploy an application, we use different Kubernetes manifests, such as Deployments, Services, Volume Claims, Ingress, etc. Sometimes, it can be tiresome to deploy them one by one. We can bundle all those manifests after templatizing them into a well-defined format, along with other metadata. Such a bundle is referred to as Chart. These Charts can then be served via repositories, such as those that we have for rpm and deb packages.

Helm is a package manager (analogous to yum and apt) for Kubernetes, which can install/update/delete those Charts in the Kubernetes cluster.

Helm has two components:

A client called helm, which runs on your user's workstation
A server called tiller, which runs inside your Kubernetes cluster.

The client helm connects to the server tiller to manage Charts. Charts submitted for Kubernetes are available here.

Monitoring and logging

In Kubernetes, we have to collect resource usage data by Pods, Services, nodes, etc, to understand the overall resource consumption and to take decisions for scaling a given application. Two popular Kubernetes monitoring solutions are Heapster and Prometheus.

Heapster is a cluster-wide aggregator of monitoring and event data, which is natively supported on Kubernetes.

Prometheus, now part of CNCF (Cloud Native Computing Foundation), can also be used to scrape the resource usage from different Kubernetes components and objects. Using its client libraries, we can also instrument the code of our application.

Another important aspect for troubleshooting and debugging is Logging, in which we collect the logs from different components of a given system. In Kubernetes, we can collect logs from different cluster components, objects, nodes, etc. The most common way to collect the logs is using Elasticsearch, which uses fluentd with custom configuration as an agent on the nodes. fluentd is an open source data collector, which is also part of CNCF.

Bash completion

Note: The following only works on newer versions. I have tested that this works on version 1.9.1.

Add the following line to your ~/.bashrc file:

source <(kubectl completion bash)

External links

Official website
Kubernetes code — via GitHub

Playgrounds

Tools

minikube — Run Kubernetes locally
kops — Kubernetes Operations (kops) - Production Grade K8s Installation, Upgrades, and Management
kube-aws — a command-line tool to create/update/destroy Kubernetes clusters on AWS
kubespray — Deploy a production ready kubernetes cluster

Resources

Training

Kubernetes Fundamentals (LFS258)

Kubernetes

Contents

Design overview

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Replica Sets

Deployments

Namespaces

Component services

Setup a Kubernetes cluster

Setup VMs

Setup hosts

Install and configure master controller

Install and configure the minions

Kubectl: Exploring our environment

Working with our Kubernetes cluster

Create and deploy pod definitions

Tags, labels, and selectors

Deployments

Multi-Pod (container) replication controller

Create and deploy service definitions

Creating temporary Pods at the CLI

Interacting with Pod containers

Logs

Autoscaling and scaling Pods

Failure and recovery

Minikube

Working with our Minikube-based Kubernetes cluster

kube-proxy

Service discovery

Service Type

Deploying a application

Volume management

ConfigMaps and Secrets

Ingress

Annotations

Jobs

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Daemon Sets

Stateful Sets

Role Based Access Control (RBAC)

Federation

Helm

Monitoring and logging

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