Kubernetes Introduction
PanChuan 2018.11.08
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Outline
- Kubernetes Overview
- Kubernetes Objects
- Kubernetes Work Mechanism
Kubernetes Overview
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Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications
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It groups containers that make up an application into logical units for easy management and discovery
Kubernetes Overview
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Kubernetes is Greek for pilot or hemlsman (the person holding the ship's steering wheel)
Kubernetes History
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2003
2013
2014
Kubernetes History
- 2014: Key Players Joined K8s community.
Microsoft/RedHat/IBM/Docker
- 2015: V1.0 release & CNCF
- 2016: The year kubernetes goes mainstream
- 2017: Enterprise Adoption & Support
https://blog.risingstack.com/the-history-of-kubernetes/
K8S Trends
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Kubernetes Needs Backgroud
- Monoliths app -> Microservice app
- Becomes too complex when doing configuration/deployment/management
- Need automation
Kubernetes high-level
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- k8s expose the whole DC as a single deployment platform
- can be thought as an operating system for the cluster
Kubernetes Features
- Service discovery and load balancing
- Automatic binpacking
- Self-healing
- Automated rollouts and rollbacks
- Storage orchestration
- Horizontal scaling
- Batch execution
- Secret and configuration management
Kubernetes Benefits
- Simplify application deployment.
- Achieving better utilization of hardware.
- Better sleeping (self-healing, auto-scaling).
- DevOps to NoOps
Kubernetes Architecture
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Container Runtime: Docker, rkt or else
Kubernetes Objects
- K8S objects are persistent entities in k8s system, these entities represent the state of cluster
- Post your desired state to Kubernetes API
Describe Objects
- Provide the object spec use json/yaml file.
apiVersion: apps/v1 # for versions before 1.9.0 use apps/v1beta2
kind: Deployment
metadata:
name: nginx-deployment
spec:
selector:
matchLabels:
app: nginx
replicas: 2 # tells deployment to run 2 pods matching the template
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.7.9
ports:
- containerPort: 80
Pods
- Pods are the central and most important concept
- encapsulated with one or more container, run and scheduled as smallest unit
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why need Pods
- Containers are designed to run only a single process per container.
- Multiple containers are better than one container running multiple process.
- take the advantage of all the features container provide, meanwhile giving the process the illusion of running together
Pods feature
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- containers in pods are not so isolated by
sharing Linux namespace
- same network interface and hostname
- Flat network between pods (No NAT)
Create a Pod
apiVersion: v1
kind: Pod
metadata:
name: nginx
labels:
env: test
name: nginx
spec:
containers:
- image: docker-registery.itv.qiyi.domain/nginx:latest
name: nginx
ports:
- containerPort: 80
protocol: TCP
kubectl create -f ningx.yaml
Don't Abuse Pods
- Pods are relatively lightweight
- A pod is also the basic unit of scaling
- Typical Multi-container pods: sidecar containers
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Pods Lables
- A label is an arbitrary key-value pair attach to a resource
- Use label-selector to select specific resource
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ReplicaSets
- Don't create pods directly, create ReplicaSets /Deployment instead
- RS keeps Pods running automatically and healthy
- 3 essential parts of a RS: A label selector, A replica count, A pod template
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Container Probe
- liveness probe & readness Probe
- three mechanisms to probe a container:
- HTTP Get probe (check code status)
- TCP socket (check if can connect)
- Exec cmd (check ret status)
Deployments
- A higher-level resource meat for deploying application and updating them declaratively
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Deployments
apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx-demo
spec:
replicas: 3
template:
metadata:
name: nginx-demo
labels:
app: nginx
env: test
spec:
containers:
- image: docker-registry.itv.qiyi.domain/nginx:latest
name: nginx-demo
Service
- Pods are ephemeral, needs a way to provide stable service
- Use label-selector to organize pods
- Each service has an IP:Port that never change while the service exists
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Service
apiVersion: v1
kind: Service
metadata:
name: nginx
spec:
ports:
- port: 80
targetPort: 8080
selector:
app: nginx
kubectl get svc
- cluster IP is virtual and only accessible inside the cluster, can't ping
Service Discovery
- through Environment variables. Pods running order matters
- through DNS
epginfo.product.svc.cluster.lcoal
Expose service to external
- NodePort, each cluster node opens a port on the node and redirect traffic to the underlying service
- LoadBalancer, an extension of the NodePort
- Ingress, operates at the HTTP level, routes different path to different service
NodePort :
=======
apiVersion: v1
kind: Service
metadata:
name: kubia-nodeport
spec:
type: NodePort
ports:
- port: 80
targetPort: 8080
nodePort: 30123
selector:
app: kubia
service Load balancer
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service Ingress
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Ingress controller: Nginx, Traefik, Kong, HAProxy
DaemonSet
- Run exactly one instance of a pod on every worker node
- Example: logCollector, kube-proxy, consul-agent
Job
- Job performs a single completable task
apiVersion: batch/v1
kind: Job
metadata:
name: batch-job
spec:
template:
metadata:
labels:
app: batch-job
spec:
restartPolicy: OnFailure
containers:
- name: main
image: luksa/batch-job
CronJob
- Schedule Jobs to run periodically or sometime in the future
apiVersion: batch/v1beta1
kind: CronJob
metadata:
name: batch-job-every-fifteen-minutes
spec:
schedule: "0,15,30,45 * * * *" // Linux cron table syntax
jobTemplate:
spec:
template:
metadata:
labels:
app: periodic-batch-job
spec:
restartPolicy: OnFailure
containers:
- name: main
image: luksa/batch-job
Namespace
- Kubernetes groups objects into namespace
- Example: prod/staging/dev
- some resource is cluster-level and doesn't belong to any namespace. Node/PersistemVolume ect.
Other Resources
- ConfigureMap
- Secrets
- Persistent Volumes
....
K8S Mechanism
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- Master node and work node components:
- ADD-ON components:
- DNS server
- Dashboard
- CNI net plugin
- Heapster
Etcd
- Kubernetes store all cluster state and metadata in ectd
- API server is the component that talk with etcd
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API Server
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- Api Server is the central component used by all other components
- Api Server clients can request to be notified when a resource is created, modified or deleted (http streaming watch)
Scheduler
- A scheduler waits for newly created pods by watching api server
- Scheduler update the pod definition by api and not talk to kubelet running on work node
- Schedule algorithm is configurable and customized scheduler is support
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Controller manager
- Almost each kind resource has a corresponding controller
- controller make sure the actual state of the system converge toward the desired state
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any possible changes trigger the controller to recheck the desired vs. actual replica count and act accrodingly
Kubelet
- Kubelet is the component responsible for everything running on a worker node
- Kubelet create containers and monitors running containers and reports their status, events, and resource consumption to API server
Cooperate
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Kube-Proxy
- Everything related to service is handled by kube-proxy process running on each node
- Kube-proxy create vIP:port in iptables rules when a new service created (through API Server)
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Proxy-Mode: userspace
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Proxy-Mode: iptables
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Proxy-Mode: ipvs (v1.9 beta)
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- based on ipvs kernel modules hook function
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K8S Control Plane HA
- Run multiple master nodes for HA
- API server can run multiple instance
- Controller Manager and Scheduler run as leader and standing by.
Reference
- https://kubernetes.io
- <Kubernetes In Action>
The End
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Kubernetes Introduction
By panchuan
Kubernetes Introduction
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