Instead of thinking about Kubernetes as something completely new I've found that comparing it to an operating system helps. I'm not an expert in operating systems but we've all used them.
Kubernetes is a layer on top of which we run our applications. It takes the resources that are accessible from the layers below and manages our applications and resources. And it provides services, such as the DNS, for the applications. With this OS mindset we can also try to go the other way: You may have used a cron (or windows' task scheduler) for saving long term backups of some applications. Here's the same thing in Kubernetes with CronJobs.
Now that we'll start talking about the internals we'll learn new insight on Kubernetes and will be able to prevent and solve problems that may result from its nature.
Due to this section being mostly a reiteration of Kubernetes documentation I will include various links the official version of the documentation - we will not setup our own Kubernetes cluster manually. If you want to go hands-on and learn how to setup your own cluster, you should read and complete Kubernetes the Hard Way by Kelsey Hightower. If you have any leftover credits from part 3 this is a great way to spend some of them.
Controllers and Eventual Consistency
Controllers watch the state of your cluster and then tries to move the current state of the cluster closer to the desired state. When you declare X replicas of a Pod in your deployment.yaml, a controller called Replication Controller makes sure that will be true. There are a number of controllers for different responsibilities.
Kubernetes Control Plane
Kubernetes Control Plane consists of
- A key-value storage that Kubernetes uses to save all cluster data.
- Decides on which node a Pod should be run on.
- Is responsible for and runs all of the controllers.
- This exposes the Kubernetes Control Plane through an API
There's also cloud-controller-manager that lets you link your cluster into a cloud provider's API. If you wanted to build your own cluster on Hetzner, for example, you could use hcloud-cloud-controller-manager in your own cluster installed on their VMs.
Every node has a number components that maintain the running pods.
- Makes sure containers are running in a Pod
- network proxy and maintains the network rules. Enables connections outside and inside of the cluster as well as Services to work as we've been using them.
And also the Container Runtime. We've been using Docker for this course.
In addition to all of the previously mentioned, Kubernetes has Addons which use the same Kubernetes resources we've been using and extend Kubernetes. You can view which resources the addons have created in the
$ kubectl -n kube-system get all NAME READY STATUS RESTARTS AGE pod/event-exporter-v0.2.5-599d65f456-vh4st 2/2 Running 0 5h42m pod/fluentd-gcp-scaler-bfd6cf8dd-kmk2x 1/1 Running 0 5h42m pod/fluentd-gcp-v3.1.1-9sl8g 2/2 Running 0 5h41m pod/fluentd-gcp-v3.1.1-9wpqh 2/2 Running 0 5h41m pod/fluentd-gcp-v3.1.1-fr48m 2/2 Running 0 5h41m pod/heapster-gke-9588c9855-pc4wr 3/3 Running 0 5h41m pod/kube-dns-5995c95f64-m7k4j 4/4 Running 0 5h41m pod/kube-dns-5995c95f64-rrjpx 4/4 Running 0 5h42m pod/kube-dns-autoscaler-8687c64fc-xv6p6 1/1 Running 0 5h41m pod/kube-proxy-gke-dwk-cluster-default-pool-700eba89-j735 1/1 Running 0 5h41m pod/kube-proxy-gke-dwk-cluster-default-pool-700eba89-mlht 1/1 Running 0 5h41m pod/kube-proxy-gke-dwk-cluster-default-pool-700eba89-xss7 1/1 Running 0 5h41m pod/l7-default-backend-8f479dd9-jbv9l 1/1 Running 0 5h42m pod/metrics-server-v0.3.1-5c6fbf777-lz2zh 2/2 Running 0 5h41m pod/prometheus-to-sd-jw9rs 2/2 Running 0 5h41m pod/prometheus-to-sd-qkxvd 2/2 Running 0 5h41m pod/prometheus-to-sd-z4ssv 2/2 Running 0 5h41m pod/stackdriver-metadata-agent-cluster-level-5d8cd7b6bf-rfd8d 2/2 Running 0 5h41m NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE service/default-http-backend NodePort 10.31.251.116 <none> 80:31581/TCP 5h42m service/heapster ClusterIP 10.31.247.145 <none> 80/TCP 5h42m service/kube-dns ClusterIP 10.31.240.10 <none> 53/UDP,53/TCP 5h42m service/metrics-server ClusterIP 10.31.249.74 <none> 443/TCP 5h42m NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE NODE SELECTOR AGE daemonset.apps/fluentd-gcp-v3.1.1 3 3 3 3 3 beta.kubernetes.io/fluentd-ds-ready=true,beta.kubernetes.io/os=linux 5h42m daemonset.apps/metadata-proxy-v0.1 0 0 0 0 0 beta.kubernetes.io/metadata-proxy-ready=true,beta.kubernetes.io/os=linux 5h42m daemonset.apps/nvidia-gpu-device-plugin 0 0 0 0 0 <none> 5h42m daemonset.apps/prometheus-to-sd 3 3 3 3 3 beta.kubernetes.io/os=linux 5h42m NAME READY UP-TO-DATE AVAILABLE AGE deployment.apps/event-exporter-v0.2.5 1/1 1 1 5h42m deployment.apps/fluentd-gcp-scaler 1/1 1 1 5h42m deployment.apps/heapster-gke 1/1 1 1 5h42m deployment.apps/kube-dns 2/2 2 2 5h42m deployment.apps/kube-dns-autoscaler 1/1 1 1 5h42m deployment.apps/l7-default-backend 1/1 1 1 5h42m deployment.apps/metrics-server-v0.3.1 1/1 1 1 5h42m deployment.apps/stackdriver-metadata-agent-cluster-level 1/1 1 1 5h42m NAME DESIRED CURRENT READY AGE replicaset.apps/event-exporter-v0.2.5-599d65f456 1 1 1 5h42m replicaset.apps/fluentd-gcp-scaler-bfd6cf8dd 1 1 1 5h42m replicaset.apps/heapster-gke-58bf4cb5f5 0 0 0 5h42m replicaset.apps/heapster-gke-9588c9855 1 1 1 5h41m replicaset.apps/kube-dns-5995c95f64 2 2 2 5h42m replicaset.apps/kube-dns-autoscaler-8687c64fc 1 1 1 5h42m replicaset.apps/l7-default-backend-8f479dd9 1 1 1 5h42m replicaset.apps/metrics-server-v0.3.1-5c6fbf777 1 1 1 5h41m replicaset.apps/metrics-server-v0.3.1-8559697b9c 0 0 0 5h42m replicaset.apps/stackdriver-metadata-agent-cluster-level-5d8cd7b6bf 1 1 1 5h41m replicaset.apps/stackdriver-metadata-agent-cluster-level-7bd5ddd849 0 0 0 5h42m
To get a complete picture of how each part communicates with each other "what happens when k8s" explores what happens when you do
kubectl run nginx --image=nginx --replicas=3 shedding some more light on the magic that happens behind the scenes.
Back in part 1 we talked a little about the "self-healing" nature of Kubernetes and how pods can be deleted and they're automatically recreated.
Let's see what happens if we delete a node that has a pod in it. Let's first deploy the pod, a web application with ingress from part 1, confirm that it's running and then see which pod has it running.
$ kubectl apply -f https://raw.githubusercontent.com/kubernetes-hy/material-example/master/app2/manifests/deployment.yaml \ -f https://raw.githubusercontent.com/kubernetes-hy/material-example/master/app2/manifests/ingress.yaml \ -f https://raw.githubusercontent.com/kubernetes-hy/material-example/master/app2/manifests/service.yaml deployment.apps/hashresponse-dep created ingress.extensions/dwk-material-ingress created service/hashresponse-svc created $ curl localhost:8081 9eaxf3: 8k2deb $ kubectl describe po hashresponse-dep-57bcc888d7-5gkc9 | grep 'Node:' Node: k3d-k3s-default-agent-1/172.30.0.2
In this case it's in agent-1. Let's make the node go "offline" with pause:
$ docker ps CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES 5c43fe0a936e rancher/k3d-proxy:v3.0.0 "/bin/sh -c nginx-pr…" 10 days ago Up 2 hours 0.0.0.0:8081->80/tcp, 0.0.0.0:50207->6443/tcp k3d-k3s-default-serverlb fea775395132 rancher/k3s:latest "/bin/k3s agent" 10 days ago Up 2 hours k3d-k3s-default-agent-1 70b68b040360 rancher/k3s:latest "/bin/k3s agent" 10 days ago Up 2 hours 0.0.0.0:8082->30080/tcp k3d-k3s-default-agent-0 28cc6cef76ee rancher/k3s:latest "/bin/k3s server --t…" 10 days ago Up 2 hours k3d-k3s-default-server-0 $ docker pause k3d-k3s-default-agent-1 k3d-k3s-default-agent-1
Now wait for a while and this should be the new state:
$ kubectl get po NAME READY STATUS RESTARTS AGE hashresponse-dep-57bcc888d7-5gkc9 1/1 Terminating 0 15m hashresponse-dep-57bcc888d7-4klvg 1/1 Running 0 30s $ curl localhost:8081 6xluh2: ta0ztp
What did just happen? Read this explanation on how kubernetes handles offline nodes
Well then, what happens if you delete the only control-plane node? Nothing good. In our local cluster it's our single point of failure. See Kubernetes documentation for "Options for Highly Available topology" to avoid getting the whole cluster crippled by a single faulty hardware.