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GCP GKE Google Kubernetes Engine DevOps 75 Real-World Demos

Name: GCP GKE Google Kubernetes Engine DevOps 75 Real-World Demos
Rating: 4.9 (839 reviews)

Master GCP GKE Key concepts Kubernetes Clusters, Storage, Ingress, Services, Pods, Deployments, Autoscaling, LB, DevOps

Created byKalyan Reddy Daida | DevOps & SRE Architect on AWS, Azure & Google Cloud Platforms, Anjani M

Last updated 3/2026

English

German [Auto],English [Auto],

What you'll learn

You will learn to master Kubernetes on Google GKE with 75 Real-world demo's on Google Cloud Platform with 20+ Kubernetes and 30+ Google Cloud Services
You will learn Kubernetes Basics for 4.5 hours
You will create GKE Standard and Autopilot clusters with public and private networks
You will learn to implement Kubernetes Storage with Google Persistent Disks and Google File Store
You will also use Google Cloud SQL, Cloud Load Balancing to deploy a sample application outlining LB to DB usecase in GKE Cluster
You will master Kubernetes Ingress concepts in detail on GKE with 22 Real-world Demos
You will implement Ingress Context Path Routing and Name based vhost routing
You will implement Ingress with Google Managed SSL Certificates
You will master Google GKE Workload Identity with a detailed dedicated demo.
You will implement External DNS Controller to automatically add, delete DNS records automatically in Google Cloud DNS Service
You will implement Ingress with Preshared SSL and Self Signed Certificates
You will implement Ingress with Cloud CDN, Cloud Armor, Internal Load Balancer, Cookie Affinity, IP Affinity, HTTP Access Logging.
You will implement Ingress with Google Identity-Aware Proxy
You will learn to use Google Artifact Registry with GKE
You will implement DevOps Continuous Integration (CI) and Continuous Delivery (CD) with Cloud Build and Cloud Source Services
You will learn to master Kubernetes Probes (Readiness, Startup, Liveness)
You will implement Kubernetes Requests, Limits, Namespaces, Resource Quota and Limit Range
You will implement GKE Cluster Autoscaler and Horizontal Pod Autoscaler

Course content

69 sections • 200 lectures • 26h 11m total length

Introduction19:50
Explore 25+ Kubernetes concepts and real-world GKE demos, including pods, deployments, services, storage classes, volumes, config maps, secrets, and autoscaling across 32 Google Cloud services.
Course GitHub Repository Links0:08
Create GCP Account and Budget alerts3:40
Learn how to create a Google Cloud account and navigate the free trial with credit and 20+ free products. Activate a full account and set budget alerts to manage spend.

GKE-02-01-CLUSTER-Introduction-to-GKE-Cluster-Modes-Types5:13
Explore GKE cluster modes and types, compare standard and autopilot architectures, and understand control plane, nodes, and how Cube CTL connects to the API server for workload deployment.
Step-02: Create GKE Cluster10:02
Create a standard regional GKE cluster in Google Cloud, configure node locations and version, enable data plane v2 and workload identity, then deploy a Kubernetes deployment and load balancer service.
Connect with Me !!!0:02
Step-03: Verify GKE Cluster and other GKE Features13:15
Verify your GKE cluster details and features, explore nodes, storage, observability, logs, workloads, services, and ingress, and preview Kubernetes objects to prepare for deploying a sample app.
Step-04: Connect to GKE using Google Cloud Shell6:17
Connect to the GKE cluster from Google Cloud Shell using kubectl and fetch cluster credentials. Verify nodes and system pods in the kube-system namespace to inspect the cluster setup.
Docker Images present on Docker Hub and GitHub Container Registry1:03
Step-05: Deploy Sample Application, Test and CleanUp16:47
Deploy a sample application in a GKE Kubernetes cluster using deployment and load balancer service YAML, run two replicas on port 8080, test via browser, then clean up.

Step-01: Install, Initialize gcloud CLI and Install GKE Auth Plugin10:07
Install the google cloud CLI on macOS, initialize a gcloud config, and configure kubectl with kubeconfig to access a GKE cluster from your terminal, including the GKE auth plugin.
Step-02: Install and Configure kubectl10:14
Remove existing kubectl clients, install kubectl via Google Cloud SDK, and align the client version with your GKE cluster (e.g., 1.26). Configure kubeconfig and verify nodes, with YAML output.

Step-01: WINDOWSOS - Install, Initialize gcloud CLI8:54
Install the Google Cloud CLI on Windows, initialize and authenticate, configure a default project region and zone, and set up kubeconfig for kubectl to access the cluster from your terminal.
Step-02: Install GKE Auth Plugin, kubectl and configure and Test8:42
Install and verify the gcloud auth plugin and kubectl, configure kubectl for your GKE cluster, verify client and server versions, address version skew, and prepare for the next Kubernetes concept.

Step-01: Kubernetes Architecture Introduction10:21
Explore Kubernetes architecture, including master and worker nodes, the API server, etcd backing store, scheduler, controllers, cloud controller manager, and container runtime in GKE.
Step-02: Kubernetes Fundamentals Introduction2:49
Explore core Kubernetes resources—pod, replica set, deployment, and service—along with imperative and declarative workflows using kubectl commands and YAML manifests.
Step-03: Kubernetes Pods Introduction5:07
Learn how a Kubernetes pod encapsulates a container image as the smallest unit, supports 1:1 relationships, enables scaling via replicas, and includes multi-container pods with sidecar and helper containers.
Step-04: Implement Kubernetes Pods Imperative Way13:49
Implement Kubernetes pods imperatively: configure kubectl for your GKE cluster, verify nodes and versions, run a port, inspect events with describe, and prepare for services.
Step-05: Kubernetes Services Introduction3:33
Learn how Kubernetes load balancer services expose pods in GKE, map service ports to container ports, and provision a Google Cloud load balancer with an external IP.
Step-06: Expose Pod with Kubernetes Service6:51
Expose the my first pod as a load balancer service with kubectl on port 80, named my first service. Monitor the external IP and access the app.
Step-07: Connect to Pods, Test and CleanUp9:59
Verify pod logs with kubectl logs, stream with -f, connect to containers via kubectl exec, run commands, fetch YAML, and clean up ports and services.

Step-01: Introduction to Kubernetes ReplicaSets6:17
Use declarative YAML to create Kubernetes replica sets that maintain a stable pod count, ensure high availability, enable scaling, and route traffic via services using labels and selectors.
Step-02: Deploy ReplicaSet and Verify8:06
Learn to create and verify a Kubernetes replica set with declarative YAML and kubectl, deploy three pods, inspect events, and confirm ownership via owner references.
Step-03: Expose ReplicaSet as a Service4:31
Expose the replica set as a load balancer service with service port 80 and container port 88, then test external IP access for the hello world app.
Step-04: Test ReplicaSet Scalability, Reliability and CleanUp5:44
test replica set reliability and high availability by simulating pod deletions and observing automatic pod recreation, then scale from three to six replicas and perform cleanup.

Step-01: Introduction to Kubernetes Deployments2:33
Discover Kubernetes deployments as a superset of replica sets, with imperative workflows and key use cases like rollouts, updates, rollbacks, scaling, pausing, and canary deployments.
Step-02: Create Kubernetes Deployment and Verify10:01
Create a Kubernetes deployment with imperative kubectl commands, verify deployment, replica set, and ports, annotate rollout with change-cause, and expose it as a service.
Step-03: Scale Deployment and Expose Deployment as Service6:44
Scale my first deployment from 1 to 10 replicas with kubectl scale, then expose it as a load balancer service on port 80 to obtain an external IP.

Step-01: Update Kubernetes Deployment with Set Image Option12:44
Update a Kubernetes deployment with set image option, perform a rolling update to 2.0.0, verify rollout status and history, and annotate the change cause as deployment update app version 2.0.0.
Step-02: Update Kubernetes Deployment with Edit Option7:27
update Kubernetes deployment using edit deployment to promote image from 2.0.0 to 3.0.0, verify rollout status, manage replica sets, and annotate change-cause with app version 3.0.0 for clear revision history.

Step-01: Deployment - Rollback to Previous Version7:01
Master deployment rollbacks in GKE by reverting to the previous version or a specific revision. Use kubectl rollout history and undo to verify image tags and change-cause annotations.
Step-02: Deployment - Rollback to Specific Version and Rolling Restarts3:58
Roll back to a specific version using kubectl rollout history and undo to a chosen revision, then perform rolling restarts to update with no downtime.

Requirements

You must have an Google Cloud account to follow with me for hands-on activities.
You don't need to have any basic knowledge of Kubernetes. Course will get started from very very basics of Kubernetes and take you to very advanced levels
Any Cloud Platform basics is required to understand the terminology

Description

Important Note: This course requires you to download Docker Desktop from Docker website . If you are a Udemy Business user, please check with your employer before downloading software.

Course Overview

Welcome to this Amazing course on Google Kubernetes Engine GKE with DevOps|75 Real-World Demos. Below is the list of modules covered in this course.

Course Modules

01. Google Cloud Account Creation

02. Create GKE Standard Public Cluster

03. Install gcloud CLI on mac OS

04. Install gcloud CLI on Windows OS

05. Docker Fundamentals

06. Kubernetes Pods

07. Kubernetes ReplicaSets

08. Kubernetes Deployment - CREATE

09. Kubernetes Deployment - UPDATE

10. Kubernetes Deployment - ROLLBACK

11. Kubernetes Deployments - Pause and Resume

12. Kubernetes ClusterIP and Load Balancer Service

13. YAML Basics

14. Kubernetes Pod & Service using YAML

15. Kubernetes ReplicaSets using YAML

16. Kubernetes Deployment using YAML

17. Kubernetes Services using YAML

18. GKE Kubernetes NodePort Service

19. GKE Kubernetes Headless Service

20. GKE Private Cluster

21. How to use GCP Persistent Disks in GKE ?

22. How to use Balanced Persistent Disk in GKE ?

23. How to use Custom Storage Class in GKE for Persistent Disks ?

24. How to use Pre-existing Persistent Disks in GKE ?

25. How to use Regional Persistent Disks in GKE ?

26. How to perform Persistent Disk Volume Snapshots and Volume Restore ?

28. GKE Workloads and Cloud SQL with Public IP

29. GKE Workloads and Cloud SQL with Private IP

30. GKE Workloads and Cloud SQL with Private IP and No ExternalName Service

31. How to use Google Cloud File Store in GKE ?

32. How to use Custom Storage Class for File Store in GKE ?

33. How to perform File Store Instance Volume Snapshots and Volume Restore ?

34. Ingress Service Basics

35. Ingress Context Path based Routing

36. Ingress Custom Health Checks using Readiness Probes

37. Register a Google Cloud Domain for some advanced Ingress Service Demos

38. Ingress with Static External IP and Cloud DNS

39. Google Managed SSL Certificates for Ingress

40. Ingress HTTP to HTTPS Redirect

41. GKE Workload Identity

42. External DNS Controller Install

43. External DNS - Ingress Service

44. External DNS - Kubernetes Service

45. Ingress Name based Virtual Host Routing

46. Ingress SSL Policy

47. Ingress with Identity-Aware Proxy

48. Ingress with Self Signed SSL Certificates

49. Ingress with Pre-shared SSL Certificates

50. Ingress with Cloud CDN, HTTP Access Logging and Timeouts

51. Ingress with Client IP Affinity

52. Ingress with Cookie Affinity

53. Ingress with Custom Health Checks using BackendConfig CRD

54. Ingress Internal Load Balancer

55. Ingress with Google Cloud Armor

56. Google Artifact Registry

57. GKE Continuous Integration

58. GKE Continuous Delivery

59. Kubernetes Liveness Probes

60. Kubernetes Startup Probes

61. Kubernetes Readiness Probe

62. Kubernetes Requests and Limits

63. GKE Cluster Autoscaling

64. Kubernetes Namespaces

65. Kubernetes Namespaces Resource Quota

66. Kubernetes Namespaces Limit Range

67. Kubernetes Horizontal Pod Autoscaler

68. GKE Autopilot Cluster

69. How to manage Multiple Cluster access in kubeconfig ?

Kubernetes Concepts Covered in the course

01. Kubernetes Deployments (Create, Update, Rollback, Pause, Resume)

02. Kubernetes Pods

03. Kubernetes Service of Type LoadBalancer

04. Kubernetes Service of Type ClusterIP

05. Kubernetes Ingress Service

06. Kubernetes Storage Class

07. Kubernetes Storage Persistent Volume

08. Kubernetes Storage Persistent Volume Claim

09. Kubernetes Cluster Autoscaler

10. Kubernetes Horizontal Pod Autoscaler

11. Kubernetes Namespaces

12. Kubernetes Namespaces Resource Quota

13. Kubernetes Namespaces Limit Range

14. Kubernetes Service Accounts

15. Kubernetes ConfigMaps

16. Kubernetes Requests and Limits

17. Kubernetes Worker Nodes

18. Kubernetes Service of Type NodePort

19. Kubernetes Service of Type Headless

20. Kubernetes ReplicaSets

Google Cloud Platform Services Covered in the course

01. Google GKE Standard Cluster

02. Google GKE Autopilot Cluster

03. Compute Engine - Virtual Machines

04. Compute Engine - Storage Disks

05. Compute Engine - Storage Snapshots

06. Compute Engine - Storage Images

07. Compute Engine - Instance Groups

08. Compute Engine - Health Checks

09. Compute Engine - Network Endpoint Groups

10. VPC Networks - VPC

11. VPC Network - External and Internal IP Addresses

12. VPC Network - Firewall

13. Network Services - Load Balancing

14. Network Services - Cloud DNS

15. Network Services - Cloud CDN

16. Network Services - Cloud NAT

17. Network Services - Cloud Domains

18. Network Services - Private Service Connection

19. Network Security - Cloud Armor

20. Network Security - SSL Policies

21. IAM & Admin - IAM

22. IAM & Admin - Service Accounts

23. IAM & Admin - Roles

24. IAM & Admin - Identity-Aware Proxy

25. DevOps - Cloud Source Repositories

26. DevOps - Cloud Build

27. DevOps - Cloud Storage

28. SQL - Cloud SQL

29. Storage - Filestore

30. Google Artifact Registry

31. Operations Logging

32. GCP Monitoring

Each of my courses comes with

Amazing Hands-on Step By Step Learning Experiences
Real Implementation Experience
Friendly Support in the Q&A section
"30-Day "No Questions Asked" Money Back Guaranteed by Udemy"

Who this course is for:

Infrastructure Architects or Sysadmins or Developers who are planning to master Kubernetes from Real-World perspective on Google Cloud Platform (GCP)
Any beginner who is interested in learning Kubernetes with Google Cloud Platform (GCP)
Any beginner who is planning their career in DevOps

GCP GKE Google Kubernetes Engine DevOps 75 Real-World Demos

What you'll learn

Explore related topics

Course content

Introduction3 lectures • 24min

Section-02: Create GKE Standard Public Cluster7 lectures • 53min

Section-03: Install gcloud CLI on mac OS2 lectures • 20min

Section-04: Install gcloud CLI on Windows OS2 lectures • 18min

Section-06: Kubernetes Pods7 lectures • 52min

Section-07: Kubernetes ReplicaSets4 lectures • 25min

Section-08: Kubernetes Deployment - CREATE3 lectures • 19min

Section-09: Kubernetes Deployment - UPDATE2 lectures • 20min

Section-10: Kubernetes Deployment - ROLLBACK2 lectures • 11min

Section-11: Kubernetes Deployments - Pause and Resume1 lecture • 11min

Requirements

Description

Who this course is for: