Managing Docker Containers In A Cluster - Introducing Kubernetes
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Managing Docker Containers In A Cluster - Introducing Kubernetes
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Containerising your applications with Docker gets more and more attraction. While managing your Docker containers on your developer machine or on a single server is not a big hassle, it can get uncomfortable very quickly when you want to deploy your containers in a cluster, no matter if in the cloud or on premises. How do you provide high availability, scaling and monitoring? Fortunately there is a rapidly growing ecosystem around docker, and there are tools available which support you with this. In this session I want to introduce you to Kubernetes, the Docker orchestration tool started and open sourced by Google. Based on the experience with their data centers, Google uses some interesting declarative concepts like pods, replication controllers and services in Kubernetes, which I will explain to you. While Kubernetes still is a quite young project, it reached its first stable version this summer, thanks to many contributions by Red Hat, Microsoft, IBM and many more.
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Managing Docker Containers In A Cluster - Introducing Kubernetes
- 1. @slintes#Devoxx #Kubernetes Managing Docker Containers In A Cluster - Introducing Kubernetes Marc Sluiter Luminis Technologies
- 2. @slintes#Devoxx #Kubernetes Who am I? • Marc Sluiter • Software Engineer @ Luminis Technologies • Java developer for 14 years • Working on Amdatu and INAETICS
- 3. @slintes#Devoxx #Kubernetes Motivation • Microservices • decoupled, modular application components • Containers • host os independent packaging • Cloud • virtual or bare metal pool of resources for running the containers
- 4. @slintes#Devoxx #Kubernetes Docker • easy to use on dev machine • how to handle container lifecycle in a cluster?
- 5. @slintes#Devoxx #Kubernetes Kubernetes • Greek for "helmsman" or “pilot" • schedules, runs and manages containers in a cluster of virtual or physical machines • declarative approach: • try permanently to reach the declared cluster state
- 6. @slintes#Devoxx #Kubernetes Kubernetes • started by Google in 2014 • based on over 10 years experience (“Borg”) • first release in Juli 2015 • donated to Cloud Native Computing Foundation • 100% Open Source • Go
- 7. @slintes#Devoxx #Kubernetes Concepts: Pods?! • smallest deployable unit • small group of tightly coupled containers • shared network and data volumes • routable IP address • multiple pods per node
- 8. @slintes#Devoxx #Kubernetes multiple container usecases • sidecar containers • ambassador containers • adapter containers • but often just one container
- 9. @slintes#Devoxx #Kubernetes Pod declaration apiVersion: v1 kind: Pod metadata: name: myAppPod labels: name: myAppPod version: v1.2 spec: containers: - name: master image: myCompany/myImage:v1.2 ports: - containerPort: 1234
- 10. @slintes#Devoxx #Kubernetes Concepts: Replication Controllers • runs x copies of a pods • starts or kill pods if necessary • handle pod failures • health checks • Up- and downscaling
- 11. @slintes#Devoxx #Kubernetes Replication Controller cont. • rolling updates • blue / green or canary deployments
- 12. @slintes#Devoxx #Kubernetes Replication Controller declaration apiVersion: v1 kind: ReplicationController metadata: name: myAppReplicationController labels: name: myApp spec: replicas: 1 selector: name: myAppPod version: v1.2 template: <embedded pod declaration>
- 13. @slintes#Devoxx #Kubernetes Concepts: Services • pods are mortal! • services provide a permanent virtual IP • proxy traffic to selected pods • simple load balancing
- 14. @slintes#Devoxx #Kubernetes Service declaration apiVersion: v1 kind: Service metadata: name: myAppService spec: ports: - port: 8888 targetPort: 1234 selector: name: myApp
- 15. @slintes#Devoxx #Kubernetes kubectl $ kubectl create -f myAppController.yaml $ kubectl get rc CONTROLLER CONTAINER(S) IMAGE(S) SELECTOR REPLICAS myAppRC master myImage name=myAppPod,… 1 $ kubectl get pods NAME READY STATUS RESTARTS AGE myAppRC-dz33o 1/1 Running 0 42s $ kubectl create -f myAppService.yaml $ kubectl get services NAME CLUSTER_IP EXTERNAL_IP PORT(S) SELECTOR AGE myAppService 10.0.136.3 <none> 1234/TCP name=myApp 32s
- 16. @slintes#Devoxx #Kubernetes Kubernetes architecture • Master • API server • Controller • Scheduler • Workers • Kubelet • Proxy • State only in etcd!
- 17. @slintes#Devoxx #Kubernetes More features • Resource limits • Secrets • Monitoring (cAdvisor) • Logging / Debugging • kubectl logs… • kubectl exec… • Authentication • new in V1.1, released this week: • Jobs • DaemonSets • Autoscaling based on CPU Usage • Ingress (HTTP Load Balancing) • Deployments (declarative rolling updates)
- 18. @slintes#Devoxx #Kubernetes K8s in production? • Apache Stratos • Red Hat Openshift & Fabric8 • CoreOS Tectonic • Deis
- 19. @slintes#Devoxx #Kubernetes Kubernetes @ Luminis Amdatu Kubernetes Java Client http://bit.ly/KubeJavaClient
Hinweis der Redaktion
- welcome to my Quickie about…
- amdatu - components for modular java applications based on OSGi inaetics - research project about modular, dynamic, scalable, secure and distributed applications
- why do I want to talk about managing containers in the cloud? everybody talks about micro services nowadays containers provide a nice packaging method for deploying them into the cloud
- Managing containers in a cluster manually is a no go Google came up early with Kubernetes
- declarative approach: not: deploy and start these 2 containers on that node but: I want to have these 2 containers running somewhere in the cluster
- - at Google everything runs in containers, 2 billion starts each week - CNCF belongs to Linux Foundation - open community, open design, open to ideas - KubeCon in SF this week sold out with 500 attendees
- shared network: localhost shared volumes: temporary initially empty directory, host file / directory, GCE persistent disk, Amazon Elastic Block Store, nfs, iSCSI, flocker, glusterfs, RBD, git, and more
- sidecar containers: extend /enhance the main container ambassador container: proxy to the outside world, e.g. to a mongo cluster adapter container: standardize and normalize output, e.g. monitoring/logging -> modular and reusable components
- docker run + metadata, esp. labels
- health checks: check if docker container is running, or sth implementation specific, e.g. via http or in-container command execution scaling during runtime
- metadata + number of replicas + pod selector
- but: - what about SSL, redirects, rewrites? - how can that fixed IP be reached? -> use your own or cloud loadbalancer/proxy for public services, use k8s services for internal communication
- metadata + portmapping + rc selector ip address of service can be fetched via API or through env variables
- command line interface
- API Server: REST / kubectl Controller: what pods should be started Scheduler: where should they be started Kubelet: start the container Proxy: service
- Resource limits: restart when exceeding, helps scheduling Secrets: store and access configuration data in a secure way Authentication: secure API server with certs or username / password Jobs: run containers where you expect termination
- Kubernetes is used already by many other projects, like… -> yes, it’s production ready
- Cloud RTI - commercial offering about kubernetes based application hosting with excellent support by our engineers dashboard with centralised logging also from your frontend