Google Kubernetes Engine GKE with DevOps 75 Real-World Demos
Deal Score+2
Google Kubernetes Engine GKE with DevOps 75 Real-World Demos
Google GKE, Kubernetes, IAM, Filestore, Disks, Ingress, Load Balancing, Autoscaling, SQL, DNS, Armor, DevOps, Build, CDN
Created by Kalyan Reddy Daida | DevOps & SRE Architect on AWS, Azure & Google Cloud Platforms | 26 hours on-demand video course
Welcome to this Amazing course on Google Kubernetes Engine GKE with DevOps|75 Real-World Demos.
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
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