Google Kubernetes Engine (GKE) is a managed, production-ready environment for deploying, managing, and scaling containerized applications using Kubernetes. It automates the management and scaling of Kubernetes clusters, allowing you to focus on your applications rather than the underlying infrastructure.

Important topics, commands, and questions to cover while explaining Google Kubernetes Engine include:

1. Kubernetes: Kubernetes is an open-source container orchestration platform that automates deploying, scaling, and operating application containers. GKE builds on Kubernetes to provide a fully managed, scalable, and secure container management solution.
2. Clusters: GKE clusters are groups of nodes that run containerized applications. A cluster consists of at least one control plane node that manages the cluster’s overall state and multiple worker nodes that run the actual applications.

• Command: gcloud container clusters create [CLUSTER_NAME] –zone [ZONE]

3. Nodes and Node Pools: Nodes are the worker machines that run containers in a GKE cluster. Nodes are organized into node pools, which are groups of nodes with the same configuration, such as machine type, disk size, and operating system.

• Command: gcloud container node-pools create [NODE_POOL_NAME] –cluster [CLUSTER_NAME] –zone [ZONE]

4. Pods: Pods are the smallest deployable units in a Kubernetes cluster and are used to group one or more containers together. Containers within a pod share the same network namespace and can communicate with each other using localhost.

Command: kubectl create -f [POD_MANIFEST_FILE]

5. Services: Services define how to access pods in a cluster. They can expose internal cluster IPs, external IPs, or load balancers to enable communication with other services or external clients.

Command: kubectl create -f [SERVICE_MANIFEST_FILE]

6. Load Balancing: GKE supports various types of load balancing, such as internal and external load balancing, network load balancing, and HTTP(S) load balancing. Load balancing distributes traffic across multiple pods to ensure high availability and fault tolerance.
7. Ingress: Ingress is a Kubernetes object that manages external access to services in a cluster. Ingress can provide load balancing, SSL termination, and name-based virtual hosting.

Command: kubectl create -f [INGRESS_MANIFEST_FILE]

8. Autoscaling: GKE supports autoscaling at both the cluster level and the application level. Cluster autoscaling adjusts the number of nodes in a cluster based on resource utilization, while application-level autoscaling adjusts the number of pod replicas based on application demand.

• Command: kubectl autoscale deployment [DEPLOYMENT_NAME] –min=[MIN_REPLICAS] –max=[MAX_REPLICAS] –cpu-percent=[TARGET_CPU_UTILIZATION]

9. Rolling Updates and Rollbacks: GKE provides rolling updates and rollbacks to minimize downtime during application deployments. Rolling updates gradually replace old versions of a deployment with a new version, while rollbacks revert to a previous version if issues arise.

Command: kubectl rollout history deployment/[DEPLOYMENT_NAME]

10. Stateful and Stateless Applications: GKE supports both stateful and stateless applications. Stateful applications maintain state across pod restarts, while stateless applications do not. To manage stateful applications, GKE offers StatefulSets.

Command: kubectl create -f [STATEFULSET_MANIFEST_FILE]

11. Persistent Storage: GKE provides various storage options, such as Persistent Volumes (PVs) and Persistent Volume Claims (PVCs), to store application data.

• Persistent Volumes (PVs) and Persistent Volume Claims (PVCs): PVs and PVCs are used to manage the storage resources in a Kubernetes cluster. PVs are used to represent physical storage resources in a cluster, while PVCs are used by applications to request a specific amount of storage from a PV.

12. Command: kubectl create -f [PV_MANIFEST_FILE]
13. Command: kubectl create -f [PVC_MANIFEST_FILE]

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