Kubernetes: Difference between revisions
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* Puppet kubernetes module | * Puppet kubernetes module | ||
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=== kubespray === | |||
Kubespray uses ansible to deploy a Kubernetes cluster. | |||
Get Kubespray from https://github.com/kubernetes-sigs/kubespray | |||
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Revision as of 05:39, 10 June 2019
Kubernetes is an open source container orchestration system originally developed by Google. By late 2017, there has been a widespread adoption of both containers and Kubernetes.
The name originates from the Greek word κυβερνήτης, meaning helmsman or pilot (Hence, their ship's wheel as their logo). The 8 letters in the middle is commonly replaced with '8' with the entire name stylized as 'k8s'.
Kubernetes is well loved by system administrators for making it easy to upgrade, install security patches, configuring networks, and making backups without needing to worry about the application level. Other features such as autoscaling and load balancing are built in to the core Kubernetes ecosystem.
Developers love it for making it extremely easy to deploy their applications as fully redundant deployments that can automatically scale up or down. Seamless upgrades can also be done and controlled by developers without needing to touch the infrastructure level.
There are many commercial products that build on top of the Kubernetes environment such as Red Hat OpenShift, or VMware PKS. If Kubernetes were the Linux kernel, these commercial products would be like the different Linux distros built on top of the kernel.
Eventually, the excitement around Kubernetes will probably fade. Similar to the Linux kernel, it will be part of the IT infrastructure plumbing and used like any other technology that currently exists.
There are certain use cases where Kubernetes isn't a good fit. For instance, database servers where each database node has some unique state and are not inter-changeable is not something that should be running under Kubernetes. Other lighter things that don't require the full Kubernetes stack might be better suited on Functions as a Service (FaaS) platforms. These so-called funtainers provide an even lighter way to run code that may be more convenient than containers. Alternatively, clusterless container services such as Amazon Fargate, or Azure Container Instances allow hosting of containers without necessarily needing to run a full Kubernetes stack.
Cloud Native
Kubernetes is based around the concept of a cloud native system. Things in such a system should be:
- Automatable - applications are deployed and managed by machines
- Ubiquitous and flexible - Decoupling physical resources from the compute node. Containerized microservices can be moved from one node to another
- Resilient and Scalable - No single point of failure, distributed and highly available through redundancy and graceful degradation.
- Dynamic - an orchestrator should be able to schedule containers to take maximum advantage of available resources
- Observability - monitoring, logging, and tracing are all available
Cluster Architecture
Kubernetes connects multiple servers into a cluster. A cluster is a combination of master nodes and worker nodes, each with a distinct set of components.
While there is a distinction between the two types of nodes in terms of where components are placed, tehre is no intrinsic difference between the two. In fact, you can run all the components on a single node such as in Minikube.
Master Nodes
Master nodes form the control plane. It forms the brain of the cluster and runs all the necessary programs to maintain the Kubernetes cluster: Scheduling containers, managing services, serving the Kubernetes API, etc.
The control plane should have the following components:
- kube-apiserver - the frontend server of the control plane
- etcd - the distributed key/value database used by kubernetes
- kube-scheduler - Schedules where new pods are to be placed
- kube-controller-manager - Exists depending on the environment. Interacts with the cloud provider and manages resources such as load balancers, persistent disk volumes, etc.
To make the control plane resilient, multiple master nodes should be deployed so that the necessary services are still available if a node should go down. A failed control plane would result in the inability for the cluster to respond to any commands or be able to react to cluster changes or reschedule any workloads.
Worker Nodes
Each worker node in the cluster runs the actual workload that is deployed on the cluster and should have the following components:
- kubelet - Responsible for driving container runtimes and starting workloads that are scheduled on the node. It also monitors pod statuses.
- kube-proxy - Handles networking between pods on different nodes and the internet
- a container runtime - The application that handles the containers that are running. Typically Docker, or rkt, or CRI-O.
Pods running on the failed node will automatically be rescheduled elsewhere by the control plane. A well designed cloud application that has multiple replicas should not be impacted by the temporary outage of a single pod.
Failure testing should be done to ensure that applications are not affected by node outages. Automatic resilience testing tools such as Netflix's Chaos Monkey can help by randomly killing nodes, Pods, or network connectivity between nodes.
Installation
Installing Kubernetes is easy and there are many options available to help you get it set up.
Keep in mind however the amount of time and resources it will take to maintain a Kubernetes cluster. There are lots of things that can go wrong with a Kubernetes set up and maintaining such a system requires a significant amount of time and energy. Things to keep in mind on a self-hosted solution are:
- HA control plane and worker nodes
- Cluster set up securely? Patched? Container defaults set appropriately?
- Services in the cluster secure?
- Conformant to CNCF standards?
- Node configuration managed, or has it drifted?
- Data backed up? Persistent storage restore/backups?
- Monitoring?
It might be a better solution to go with a managed Kubernetes service such as from AWS or GCE.
If you do wish to go with a self-hosted solution, there are a few Kubernetes installers:
- kops
- kubespray
- TK8
- Kubernetes the hard way
- kubeadm
- tarmak
- Rancher Kubernetes Engine
- Puppet kubernetes module
- kubeformation
kubespray
Kubespray uses ansible to deploy a Kubernetes cluster.
Get Kubespray from https://github.com/kubernetes-sigs/kubespray
Quick Start
To get an application running as a service:
- Create a deployment which defines how many replicas should exist, the container to use, and exposed ports.
- This will create a Pod. Each replica creates an additional Pod (that ideally resides on different nodes).
kubectl get deploymentsto see deploymentskubectl get podsto see pods
- Create a service which defines the name of the service and the port the service is exposed on
kubectl get service
Concepts
See the Kubernetes documentation at https://kubernetes.io/docs/concepts/
In summary:
- A Deployment defines the desired state for pods and ReplicaSets.
- A ReplicaSets creates or destroys pods depending on scaling and the number of pods that are running.
- A Pod is a collection of container(s) all residing on one node.
- A Service is an abstraction that defines the logical set of Pods. The Pods could be turned off or migrated without affecting the overall Service.
- A Kubernetes Master is responsible for maintaining the state of the Kubernetes cluster.
- A Kubernetes (Worker) Node is responsible for running the actual applications managed by Kubernetes.
Each concept will be covered in more detail below.
Pods
A pod is:
- A collection of application containers
- Guaranteed to be deployed on the same Kubernetes cluster node
- Shares the same cgroup, IP address, hostname (hence, all containers in a pod runs in the same execution environment)
A pod should provide one individual component of an application that can:
- Be scaled independently of all other components in the application (eg. Database with respect to the frontend web server)
- Work even if placed (ie. orchestrated) on a different machine
In general, the right question to ask yourself when designing Pods is, “Will these containers work correctly if they land on different machines?” If the answer is “no,” a Pod is the correct grouping for the containers. If the answer is “yes,” multiple Pods is probably the correct solution. In the example at the beginning of this chapter, the two containers interact via a local filesystem. It would be impossible for them to operate correctly if the containers were scheduled on different machines.—Thinking with Pods, Kubernetes: Up and Running
Pods are assigned a unique Pod IP address within the cluster. All containers inside a pod can reference each other via localhost. Containers outside a pod can only reference other containers in other containers using the Pod IP address or via a Service.
Pods are defined in text file as a manifest. The Kubernetes API server processes the manifest, then stores it in persistent storage (etcd). A scheduler then finds pods that need to be scheduled and deploys the pods on the appropriate resource that satisfies any constraints defined in the manifest.
A Pod can be created by invoking a command: kubectl run kuard --image=registry/something/something:tag. However, using a manifest (aka. an object definition in yaml) to define the Pod is more manageable. A manifest looks something like this:
apiVersion: apps/v1 # for versions before 1.9.0 use apps/v1beta2
kind: Pod
metadata:
name: kuard
spec:
containers:
- image: gcr.io/kuar-demo/kuard-amd64:1
name: kuard
ports:
- containerPort: 8080
name: http
protocol: TCP
env:
- value: something
resources:
requests:
cpu: 100m
cpu: 100Mi
A few things to note from the definition above (and this applies to all manifests)
- Kind: Specifies the kind of Kubernetes resource this manifest defines
- Metadata: Helpful data to uniquely identify the object. Eg. name, UID, optionally namespace
- Spec: Object data; for Pods, it should be an array of containers (including container image, name, ports, environment variables, resources, etc).
For more information on the spec, see https://github.com/kubernetes/community/blob/master/contributors/devel/api-conventions.md.
- Create using
kubectl apply -f pod-manifest.yml - See it using
kubectl get pods - Detailed information about it using
kubectl describe pods pod-name - Delete it using
kubectl delete pods/pod-nameorkubectl delete -f pod-manifest.yml
Pods that are set for deletion will cease to have new requests sent to it. After a 30 second termination grace period, the pods are then terminated. This extra time allows for the pod to reliably finish active requests.
Controllers
A controller is a reconciliation loop that drives the actual cluster state to the desired cluster state.
A few types of controllers are controlled by the following 'set' objects.
ReplicaSet
See: https://kubernetes.io/docs/concepts/workloads/controllers/replicaset/
ReplicaSets defines the number of pod replicas that are running at a given time and is enforced by the Replication Controller. Typically, ReplicaSets are used by Deployments as a mechanism to orchestrate pod creation, deletion, and updates.
DaemonSet
See: https://kubernetes.io/docs/concepts/workloads/controllers/daemonset/
DaemonSet defines which Pod will run on some or all Kubernetes Nodes. As nodes are added or removed, Pods will be created or destroyed with it. Some use cases requring DaemonSets include storage services (glusterd, ceph), monitoring, log collection, etc., on each node.
Others
Stateful Sets: https://kubernetes.io/docs/concepts/workloads/controllers/statefulset/ Job Controller: Runs a Pod as a job. TBD.
Deployments
See: https://kubernetes.io/docs/concepts/workloads/controllers/deployment/
Deployments defines the desired state of Pods or ReplicaSets which are enforced by the Deployment Controller. A deployment can be versioned so that Kubernetes can let you rollout a new version with the ability to pause or even rollback the changes at a later time.
The manifest's spec should contain a template that contains the information about a new Pod.
Example Deployment manifest:
No code provided.
- Create using
kubectl apply -f frontend-deployment.yml - See it using
kubectl get deployments - Pods that this deployment creates can be seen using the label selector.
- This example manifest has 2 labels applied: app, and tier
- See it using
kubectl get pods -l app=guestbook -l tier=frontend
You can change the scale of a deployment:
[root@kube guestbook]# kubectl get deployment frontend
NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE
frontend 3 3 3 3 44m
[root@kube guestbook]# kubectl scale deployment frontend --replicas=5
deployment.extensions/frontend scaled
[root@kube guestbook]# kubectl get deployment frontend
NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE
frontend 5 5 5 5 45m
[root@kube guestbook]# kubectl get pods
NAME READY STATUS RESTARTS AGE
frontend-654c699bc8-5ngzj 1/1 Running 0 45m
frontend-654c699bc8-77b58 1/1 Running 0 45m
frontend-654c699bc8-ll7cr 1/1 Running 0 22s
frontend-654c699bc8-pqzvp 1/1 Running 0 22s
frontend-654c699bc8-sq682 1/1 Running 0 45m
Service
A Service provides an abstraction between the user and the underlying Pod or Pods providing the service. Since Pods are ephemeral, their IP addresses may change as they get created and destroyed and individual pods may go down; a Service provides applications with a name and load balancing and routing to maintain the service's availability.
A Service by default provides a single IP address for the set of pods (known as a ClusterIP) and are only accessible within the cluster. This can be changed so that a Service provides a load balanced port (LoadBalancer) or a port which is exposed on the node (NodePort).
An example manifest:
apiVersion: v1
kind: Service
metadata:
name: frontend
labels:
app: guestbook
tier: frontend
spec:
# comment or delete the following line if you want to use a LoadBalancer
type: NodePort
# if your cluster supports it, uncomment the following to automatically create
# an external load-balanced IP for the frontend service.
# type: LoadBalancer
ports:
- port: 80
selector:
app: guestbook
tier: frontend
- Apply the Service using
kubectl apply -f frontend-service.yaml - See Services using
kubectl get services
If you use a NodePort and the service looks like this:
[root@kube guestbook]# kubectl get service frontend
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
frontend NodePort 10.97.195.242 <none> 80:32764/TCP 10m
You can get to your service by accessing the Node on port 32764.
Namespaces
A namespace organizes objects in the cluster. It is analogous to OU containers in Active Directory, folders in a filesystem, or classes in object oriented languages. By default, new objects are placed in the 'default' namespace.
Objects cannot see other objects in different namespaces (this applies even to the default namespace). Secrets in a different namespace will not be visible.
Kubernetes users can be assigned permissions to specific namespaces which can be used to limit a user's access on a shared multi-tenant cluster.
Contexts
Contexts are like a profile. A context can have different default namespace, or user credentials to manage different clusters.
Change the current context using kubectl config use-context my-context
Config File
Located in ~/.kube/config. This file contains credentials to authenticate to the cluster.
It contains the default namespace and context values.
Kubernetes API
The Kubernetes API is a RESTful API, providing access to the Kubernetes backend.
Objects in the Kubernetes API are represented as JSON or Yaml files. Files can be used to create, update, or delete objects from the server.
| Description | Command |
|---|---|
| Create/Update | # kubectl apply -f obj.yaml
|
| Edit | # kubectl edit <resource-name> <object-name>
|
| Delete | # kubectl delete -f obj.yaml
## or
# kubectl delete <resource-name> <object-name>
|
All objects can be annotated or given a label.
| Description | Command |
|---|---|
Label pod 'bar' color=red |
# kubectl label pods bar color=red
## pass --overwrite if it already exists.
|
Remove label color from pod 'bar' |
# kubectl label pods bar -color
|
Kubernetes Master Node
A Kubernetes master node contains containers that provide the API server, scheduler, etc. that manages the cluster.
The master node should have the following components:
controller-manager: Responsible for running controllers that regulate behavior int he cluster. Eg. ensure replicas for a service are available and healthy.scheduler: Places pods into different nodes in the clusteretcd: storage for cluster; stores API objects.
All components deployed by Kubernetes run under the kube-system namespace.
# kubectl describe nodes kube
...
Non-terminated Pods: (8 in total)
Namespace Name CPU Requests CPU Limits Memory Requests Memory Limits
--------- ---- ------------ ---------- --------------- -------------
kube-system coredns-576cbf47c7-6mphw 100m (2%) 0 (0%) 70Mi (0%) 170Mi (2%)
kube-system coredns-576cbf47c7-75n6g 100m (2%) 0 (0%) 70Mi (0%) 170Mi (2%)
kube-system etcd-kube 0 (0%) 0 (0%) 0 (0%) 0 (0%)
kube-system kube-apiserver-kube 250m (6%) 0 (0%) 0 (0%) 0 (0%)
kube-system kube-controller-manager-kube 200m (5%) 0 (0%) 0 (0%) 0 (0%)
kube-system kube-proxy-cmdsn 0 (0%) 0 (0%) 0 (0%) 0 (0%)
kube-system kube-scheduler-kube 100m (2%) 0 (0%) 0 (0%) 0 (0%)
kube-system weave-net-swwgs 20m (0%) 0 (0%) 0 (0%) 0 (0%)
...
The Kubernetes proxy is responsible for routing network traffic to services in the kubernetes cluster. (Question: Does it do the load balancing?). A proxy exists on every node.
# kubectl get daemonsets --namespace=kube-system
NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE NODE SELECTOR AGE
kube-proxy 1 1 1 1 1 <none> 26h
weave-net 1 1 1 1 1 <none> 28m
Question: What is a DaemonSet?
Kubernetes also runs a DNS server that provides naming and discovery for services in the cluster.
# kubectl get deployments --namespace=kube-system
NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE
coredns 2 2 2 2 26h
# kubectl get services --namespace=kube-system
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
kube-dns ClusterIP 10.96.0.10 <none> 53/UDP,53/TCP 26h
The DNS service for the cluster runs on 10.96.0.10. If you log into a container in the cluster, this server will be used as the primary DNS server.
Kubernetes Dashboard UI can be installed. Like the DNS service, it is both a deployment and a service:
# kubectl get deployments --namespace=kube-system kubernetes-dashboard
NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE
kubernetes-dashboard 1 1 1 1 2m26s
[root@kube ~]# kubectl get services --namespace=kube-system kubernetes-dashboard
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
kubernetes-dashboard ClusterIP 10.108.158.128 <none> 443/TCP 2m36s
Run kubectl proxy to proxy the server on localhost:8001 and then access it in a web browser at http://localhost:8001/ui. If this is on a remote server, create a SSH tunnel.
Kubernetes Node
Also known as a Worker or Minion node which has a container runtime such as Docker.
The Kubelet is a daemon on each node that will start/stop/maintain application containers as directed by the Kubernetes Master (the orchestrator/scheduler/control plane).
The scheduler does this by checking a node's taint and will not schedule pods on nodes that contain things like node-role.kubernetes.io/master:NoSchedule. Attempting to do so will result in a FailedScheduling status and a message of 0/1 nodes are available: 1 node(s) had taints that the pod didn't tolerate. when looking at pod events using kubectl describe pods pod-name.
Commands
The kubectl command line tool is the official kubernetes client for interacting with the Kubernetes API.
| Description | Command |
|---|---|
| Get all nodes | # kubectl get nodes
|
| Get all pods | # kubectl get pods --all-namespaces
|
| Get information about a node | # kubectl describe nodes
|
| See components in the cluster | # kubectl get componentstatuses
|
Tips:
When using kubectl get, pass
--no-headersto remove headers for easier parsing-o json|yamlto format output in json/yaml.
| Description | Command |
|---|---|
| Create a pod | # kubectl run kuard --image=gcr.io/kuar-demo/kuard-amd64:1
# kubectl apply -f kuard-pod.yaml
|
| Listing pods | # kubectl get pods
## Filter by label with -l, can supply multiple of these.
# kubectl get pods -l label=something
|
| Delete pod | # kubectl delete deployments/kuard
# kubectl delete -f kuard-pod.yaml
|
| Pod Details | # kubectl describe pods kuard
|
| Pod Logs | # kubectl logs kuard
|
| Enter a container | # kubectl exec kuard cmd
# kubectl exec -it kuard sh
|
| Copy to/from container | # kubectl cp podname:/src ./dst
# kubectl cp ./src podname:/dst
|
A pod manifest looks something like this:
apiVersion: v1
kind: Pod
metadata:
name: kuard
spec:
containers:
- image: gcr.io/kuar-demo/kuard-amd64:1
name: kuard
ports:
- containerPort: 8080
name: http
protocol: TCP
Questions
- What is involved in setting up a cluster on multiple VMs?
- What is the Kubernetes API?
- What is this persistent storage (etcd)?
- What is the WeaveWorks network and how does it work?
See Also
- Command cheat sheet
- Kubernetes: Up & Running
- CouchDB failover demo: https://blog.couchbase.com/databases-on-kubernetes/
- A Kubernetes Guide
- https://kubernetes.io/docs/tutorials/stateless-application/guestbook/ Simple overview on deploying a guestbook application
MySQL on Kubernetes https://www.youtube.com/watch?v=J7h0F34iBx0Not exactly beginner friendly. Goes over the MySQLOperator and Vitess