Kubernetes basics, Nodes, Pods, Containers, Deployments
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Kubernetes, also known as K8s for short, is an open-source system for automating the deployment, scaling, and management of containerized applications. Open-source: Anyone can use and contribute to it, making it a popular choice for many organizations. Container orchestration: It groups containers (which are essentially miniaturized applications) into logical units for easy management and discovery. Automated: It takes care of tasks like deploying new versions of your application, scaling it up or down based on demand, and restarting crashed containers.
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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 does Kubernetes solve?
- 4. Increased Usage of Containers ● 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 is Special?
- 7. Kubernetes Offers ● Scalability or high performance ● Availability or no downtime ● Disaster recovery or backup, restore
- 8. Kubernetes Popularity ● According to 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 Kubernetes Popularity ● 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.
- 13. Master Node ● API Server: 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 Master Node ● 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 Worker Nodes ● 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.
- 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 deployment is 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
- 21. Horizontal vs Vertical Scaling
- 22. Horizontal Scaling ● Increases or 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 ● Increases or 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.
- 24. Thank you.