Kubernetes fundamentals
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These slides were used during a technical session for the Cloud-Native El Salvador community. It covers the basic Kubernetes components, some installers and main Kubernetes resources. For the demo, it was used the capabilites provided by the Horizontal Pod Autoscaler.
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Kubernetes fundamentals
- 2. Victor Morales • +15 yrs as a Software Engineer • .NET, Java, python, Go programmer • OpenStack, OPNFV, ONAP and CNCF contributor. https://about.me/electrocucaracha
- 3. Agenda 1. Kubernetes Architecture • Control Plane components • kubectl • Controller Pattern • Scheduler • Node components 2. Kubernetes Installers • Kubeadm • Kubespray • Kind 3. Kubernetes Resources • Scopes Namespace or Cluster • Pod • Service and Labels • Deployment and ReplicaSets 4. Demo • Autoscaling strategies • Horizontal Pod Autoscaler
- 5. Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications.
- 6. Control Plane components • kube-apiserver: Exposes the Kubernetes API. • etcd: Used as Kubernetes' backing store for all cluster data. • kube-scheduler: Watches for newly created Pods with no assigned node, and selects a node for them to run on. • kube-controller-manager: Runs controller processes. • Node controller: Responsible for noticing and responding when nodes go down. • Replication controller: Responsible for maintaining the correct number of pods for every replication controller object in the system. • Endpoints controller: Populates the Endpoints object (that is, joins Services & Pods). • Service Account & Token controllers: Create default accounts and API access tokens for new namespaces • cloud-controller-manager: Embeds cloud-specific control logic. master kube-apiserver kube-controller-managerkube-scheduler etcd cloud-controller-manager
- 7. kubectl Tool that makes it easy to use kubectl plugins. The Kubernetes command- line tool which allows you to run commands against Kubernetes clusters.
- 8. Controller pattern A controller tracks at least one Kubernetes resource type. These objects have a spec field that represents the desired state. The controller(s) for that resource are responsible for making the current state come closer to that desired state. https://blog.container-solutions.com/kubernetes-operators-explained
- 9. kube-scheduler The scheduler finds feasible Nodes for a Pod and then runs a set of functions to score the feasible Nodes* and picks a Node with the highest score among the feasible ones to run the Pod. The scheduler then notifies the API server about this decision in a process called binding. *Nodes that meet the scheduling requirements for a Pod are called feasible nodes. Feasible nodes worker worker2 worker3 worker4 Feasible nodes worker worker3 Filtering Feasible nodes worker worker3 Scoring Priority 2 Priority 4 https://kubernetes.io/docs/concepts/scheduling-eviction/kube-scheduler/
- 10. Node components • kubelet: Makes sure that containers are running in a Pod. • kube-proxy: Maintains network rules on nodes. These network rules allow network communication to your Pods from network sessions inside or outside of your cluster. • Container Runtime: Responsible for running containers. (docker, containerd, CRI-O) • Add-ons: Extend the functionality of Kubernetes. worker kubelet kube-proxy docker flannel kubernetes-dashboard coredns
- 12. Kubeadm It is a tool built to provide best-practice "fast paths" for creating Kubernetes clusters. It performs the actions necessary to get a minimum viable, secure cluster up and running in a user friendly way. https://kubernetes.io/docs/setup/production-environment/tools/kubeadm/create-cluster-kubeadm/ https://github.com/kubernetes/kubeadm
- 13. KinD It is a tool for running local Kubernetes clusters using Docker container “nodes”. kind was primarily designed for testing Kubernetes itself, but may be used for local development or CI. https://kind.sigs.k8s.io/
- 14. Kubespray It deploys a Production-Ready Kubernetes Cluster on bare metal and most clouds, using Ansible as its substrate for provisioning and orchestration. https://kubespray.io/#/
- 16. Namespaces Help different projects, teams, or customers to share a Kubernetes cluster. control-plane K8s cluster worker worker2 worker3 pod1 deployment-1 pod2 pod1 deployment-1 pod2 namespace-1 namespace-2
- 19. Ingress Manages external access to the services in a cluster, typically HTTP. https://kubernetes.io/docs/concepts/services-networking/ingress/
- 21. Pod A Pod is a Kubernetes abstraction that represents a group of one or more application containers (such as Docker or rkt), and some shared resources for those containers. Pods are the atomic unit on the Kubernetes platform.
- 22. Service and Labels A Service is an abstraction which defines a logical set of Pods and a policy by which to access them. The set of Pods targeted by a Service is usually determined by a LabelSelector. Services match a set of Pods using labels and selectors, a grouping primitive that allows logical operation on objects in Kubernetes. Labels are key/value pairs attached to objects.
- 23. Deployment and ReplicaSets A ReplicaSet’s purpose is to maintain a stable set of replica Pods running at any given time. As such, it is often used to guarantee the availability of a specified number of identical Pods. A Deployment controller provides declarative updates for Pods and ReplicaSets.
- 25. Autoscaling strategies • Horizontal Pod Autoscaler (HPA): adjusts the number of replica Pods of an application. (scale out/in) • Vertical Pod Autoscaler (VPA): adjusts the resource requests and limits of the containers of an application. (scale up/down) • Cluster Autoscaler: adjusts the number of nodes of the cluster. control-plane K8s cluster worker worker2 pod1 deployment-1 pod1 pod2 pod3 pod4 HPA VPA Cluster Autoscalerhttps://d1smfj0g31qzek.cloudfront.net/above_the_clouds.ppt.pdf
- 26. Horizontal Pod Autoscaler • Resource Metrics API serves predefined resource usage metrics. • Custom Metrics API serves user-specified custom metrics that are associated with Kubernetes objects in the cluster. • External Metrics API serves user-defined custom metrics that are not associated with any Kubernetes objects. https://itnext.io/autoscaling-apps-on-kubernetes-with-the-horizontal-pod-autoscaler-798750ab7847
- 27. Controller Manager Metrics APIMetrics Collector cpustats Prometheus Prometheus Adapter Horizontal Pod Autoscaler Scale out/in /metrics processed_requests_total processed_requests_per_second
Editor's Notes
- https://levelup.gitconnected.com/kubernetes-scheduler-101-751f65841fa0
- https://12factor.net/
- https://medium.com/swlh/applications-autoscaling-strategy-in-kubernetes-50535683322f https://cdn2.hubspot.net/hubfs/498921/eBooks/scalability_new.pdf
- https://levelup.gitconnected.com/building-kubernetes-apps-with-custom-scaling-a-gentle-introduction-a332d7ebc795