Architecting with Google Kubernetes Engine (AGKE)

Course Overview

Module 1 - Workloads: Deployments and Jobs

• Creating deployments.
• Inspecting deployments.
• Updating deployments.
• Adopting other deployment strategies.
• Using Jobs and Cronjobs
• Cluster scaling.
• Controlling Pod placement with labels and affinity rules.
• Controlling Pod placement with taints and tolerations.
• Getting software into your cluster.

Module 2 - Google Kubernetes Engine Networking

• Pod networking
• Kubernetes Services
• Service type and load balancers
• Ingress
• Container-native load balancing
• Network policies

Module 3 - Persistent Data and Storage

• Volumes
• Ephemeral volumes
• Durable volumes
• Statefulsets
• Configmaps
• Secrets

Module 4 - Access Control and Security in Kubernetes and Google Kubernetes Engine

• Explore Kubernetes authentication and authorization.
• Define Kubernetes RBAC and how it works with IAM to secure GKE clusters.
• Configure Workload Identity to access Google Cloud services from within GKE.
• Secure GKE with Pod Security Standards and Pod Security Admission.
• Implement Role-Based Access Control with GKE.

Module 5 - Google Kubernetes Engine Logging and Monitoring

• Cloud Observability
• Cloud Logging
• Cloud Monitoring
• Inspecting logs with the kubectl command
• Inspecting logs with Cloud Logging and logging agents

Module 6 - Using Google Cloud Managed Storage Services with Google Kubernetes Engine

• Using Google Cloud services
• Using Cloud Storage
• Using Google Cloud databases
• Using Cloud SQL and SQL Auth Proxy.
• Comparing storage options.

Module 7 - Using CI/CD with Google Kubernetes Engine

• What is CI/CD?
• CI/CD pipeline construction
• CI/CD tools available in Google Cloud
• Best practices for using CI/CD on Google Cloud

Module 8 - Course Summary

Prerequisites

Complete Getting Started with Google Kubernetes Engine (GCP-GSGKE) or have equivalent experience.