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Kubernetes basics, Nodes, Pods, Containers, Deployments
Kubernetes (K8s) is an open-source container orchestration tool developed by Google for managing containerized applications, addressing the challenges of transitioning from monoliths to microservices. Its popularity has surged, with over 69% of organizations using it in production by 2022, and it boasts a significant market share among container orchestration tools. The architecture consists of a master node managing the cluster and worker nodes executing the applications, with pods serving as the fundamental unit for deployment.
Kubernetes basics, Nodes, Pods, Containers, Deployments
- 1. What is Kubernetes(K8s)? ● Open-source container orchestration tool ● Helps us manage containerized applications ● Developed by Google
- 2. What problems doesKubernetes solve?
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- 4. Increased Usage ofContainers ● According to the Annual Flexera State of the Cloud Report from 2021, 53% of companies use Docker containers. ● Gartner's analysts predict that by 2022, more than 75% of global organizations running containerized applications
- 6. Why Kubernetes isSpecial?
- 7. Kubernetes Offers ● Scalabilityor high performance ● Availability or no downtime ● Disaster recovery or backup, restore
- 8. Kubernetes Popularity ● Accordingto the 2022 CNCF Cloud Native Landscape Survey, over 69% of organizations are using Kubernetes in production, ● The number was 58% in 2021 and 30% in 2018.
- 10. Facts about KubernetesPopularity ● World's leading technology companies, such as Amazon, Google, and Microsoft, are using Kubernetes to deploy their applications. ● Over 50% of Fortune 100 companies are using Kubernetes in production. ● Kubernetes has a commanding 92% market share among container orchestration tools ● There are now over 3.9 million developers worldwide who use Kubernetes.
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- 13. Master Node ● APIServer: Entry point for interacting with the cluster. ● Etcd: Stores the cluster's desired state configuration and current state data. ● Scheduler: Selects the most suitable node for each pod based on various factors like resource availability and pod requirements. ● Controller Manager: Maintains the desired state of the cluster by running various controllers that manage deployments, replica sets, nodes, and more.
- 14. Facts about MasterNode ● It can be compared to the control plane or the brain of the cluster. ● It is a single point of control for managing the entire cluster, simplifying administration and configuration. ● It continuously comparing the current state with the desired state ● It automates tasks like scheduling, scaling, and healing, reducing manual intervention and improving efficiency ● It uses less resources than worker nodes ● It recommended to have more than one master node on production
- 15. Worker Nodes ● Kubelet:An agent that runs on each worker node. Manages pod lifecycle events (start, stop, restart) ● Container Runtime: Directly on the worker node's operating system and handles container lifecycles ● kube-proxy: Manages pod networking. Routes traffic to pods based on service definitions.
- 16. Facts about WorkerNodes ● They are the workhorses of the cluster. ● If master node is the brain then worker nodes are the muscles, executing the work. ● The performance of the applications directly depends on the capabilities of the worker nodes.
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- 18. Pods & Containers ●A pod is the fundamental unit for deploying and managing applications ● It's like a little pod of peas, where each pea represents a container ● All the containers in a pod share the same storage and network resources ● Kubernetes treats the entire pod as a single unit ● Pods are ephemeral
- 19. Deployments ● A deploymentis a Kubernetes object that specifies the desired state of your application, including: ○ The container image to use. ○ The number of replicas (instances) to run. ○ Resource requests and limits for each container. ○ Environment variables and other configuration. ● Deployments are commonly used for stateless applications ● Deployments manage ReplicaSets ● Kubernetes ensures that the actual state of your application converges to the desired state you defined
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- 21. Horizontal vs VerticalScaling
- 22. Horizontal Scaling ● Increasesor decreases the number of pod replicas (instances) running your application ● Suitable for stateless applications with predictable resource demands Methods: ● Horizontal Pod Autoscaler (HPA): Automatically scales pods based on CPU, memory, or custom metrics. ● Manual Scaling: You manually adjust the number of pod replicas as needed.
- 23. Vertical Scaling ● Increasesor decreases the resources allocated to individual pods. ● Useful for stateful applications or those with fluctuating resource needs. Methods: ● Vertical Pod Autoscaler (VPA): Automatically adjusts CPU and memory requests/limits for pods based on their usage. ● Manual Scaling: You manually adjust pod resource requests/limits.
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