Kubernetes - introduction
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Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It coordinates activities across a cluster of machines by defining basic building blocks like pods (which contain containers), replication controllers (which ensure a specified number of pods are running), and services (which define logical groups of pods). Kubernetes provides tools for running applications locally on a single node as well as managing resources in the cluster, including creating, deleting, viewing, and updating resources from configuration files.
![Debugging cluster resources
Execute command on the container
• kubectl exec [-it] pod_name process_to_run
Get container logs
• kubectl logs pod_name [-c container_name]
Forward port from a pod
• kubectl port-forward pod_name local_port:remote_port
Print detailed description of a resource
• kubectl describe resource_type resource_name](https://image.slidesharecdn.com/kubernetes-190226130900/85/Kubernetes-introduction-8-320.jpg)
Kubernetes - introduction
- 2. Kubernetes (k8s): is an open-source system for automating deployment, scaling, and management of containerized applications
- 3. Why would you care? The pitch: “Kuberentes makes it easier to organize and schedule your application across a fleet of machines” Specifically by: • Horizontal scaling • Load distribution • Service discovery • Health monitoring • Deploying new versions, rollbacks • Handling hardware failure
- 4. High level architecture Master - coordinates all activities in the cluster Nodes: • virtual or physical machines • actual workers • runs processes: • kubelet • container runtime
- 5. Basic building blocks Containers • Define single running process* • Eg docker container Pods • the way of running containers in kubernetes • basic deployable and scaling unit • defines one or more containers • containers are co-located on a node • flat network structure Nodes: • physical worker machines • can run multiple pods • pods running within single node don’t know about each other
- 6. Running things locally Minikube: • single node cluster • running in a VM • supports linux, windows and macOS • mature project https://kubernetes.io/docs/setup/minikube/ https://kubernetes.io/docs/tasks/tools/install-minikube/ https://docs.docker.com/docker-for-windows/kubernetes/ https://docs.docker.com/docker-for-mac/kubernetes/ Docker with built-in kubernetes: • single node cluster • running in a VM • windows and macOS • drag & drop installation • bound to specific kubernetes version • relatively new More options listed in https://kubernetes.io
- 7. Managing cluster resources Create resource from file • kubectl create -f resource_file.yml Change existing (or create) resource based on file • kubectl apply -f resource_file.yml Delete existing resource • kubectl delete resource_type resource_name List resources of type • kubectl get resource_type Edit resource on the server • kubectl edit resource_type resource_name
- 8. Debugging cluster resources Execute command on the container • kubectl exec [-it] pod_name process_to_run Get container logs • kubectl logs pod_name [-c container_name] Forward port from a pod • kubectl port-forward pod_name local_port:remote_port Print detailed description of a resource • kubectl describe resource_type resource_name
- 9. Defining a pod Main definition components • api • resource type • metadata • spec
- 10. Grouping pods - labels • Each pod can have multiple labels • Labels can be changed on a live pod • Basic mechanism to execute commands on multiple pods
- 11. Pod health - liveness probe Out of the box (before the probe) • Pod defines a restart policy • Crashing process can be restarted by kubelet Process can be alive but unhealthy eg: • deadlocked • stuck in a loop Liveness probe is a way of telling kubelet that a process in no longer healthy and needs restarting 3 ways of querying: • http • tcp • exec Limitations of liveness probe
- 12. Replica Sets Replication Controller Ensures desired number of pods exist by: • scaling up or down • running new pods when nodes fail Definition consists of: • label selector • replica count • pod template
- 13. Demo
- 14. Service Define logical groups of pods - label selectors Types: • ClusterIP (default) • LoadBalancer • NodePort • ExternalName Service is constant: • IP doesn’t change (except headless) • each service gets a dns entry
- 15. Pod health - readiness probe Similar to liveness probe: • Defined in a pod • 3 types supported • similar parameters When probe fails pod is marked as not ready Not ready pods are removed from services
- 16. Service - LoadBalancer • Allows automatic provisioning of load balancers • Needs to be supported by cloud provider • Exposes external IP to the cluster
- 17. DEMO
- 18. Deployments • Higher level resource • Deals with updating the application • Allows graceful rollback • Can pause or abort a bad release • Manages internally multiple replica sets • Changing pod template triggers update
- 19. Deployments Revision history: • rolling back release • switching between releases • number of revisions can be specified Update strategy: • RollingUpdate • Recreate Detecting bad releases with minReadySeconds Specifying update process • MaxSurge • MaxUnavailable
- 20. DEMO
- 21. Passing configuration Pod definition can embed: • environment variables • command line parameters This couples pod definition with environment: • separate definitions for prod/test • changing configuration requires changing pod
- 22. ConfigMap • Lives as a separate resource • Supports: • environment variables: • individual • entire environment • configuration files /directories • Live reloading of config if supported by pod • Missing ConfigMap prevents container from starting
- 23. ConfigMap - basic usage Defining and passing single environment variable
- 24. ConfigMap - mounting files
- 25. Secrets • Similar to configMap • Stored in memory on the nodes (includes mounting files) • Ability to store binary data - base64 encoded
- 26. Where to go from here Managing persistent storage: • persistent volumes • persistent volume claims • storage class Advanced routing - ingress controllers Multiple replicas with own storage - stateful sets Even more resources - deamon sets, jobs, cronjobs Package management - Helm Managing Kubernetes through API Service mesh - Istio
- 27. Thank you