Architecting with Google Kubernetes Engine

This class introduces participants to deploying and managing containerized applications on Google Kubernetes Engine (GKE) and the other services provided by Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as pods, containers, deployments, and services; as well as networks and application services. This course also covers deploying practical solutions including security and access management, resource management, and resource monitoring.

This course teaches participants the following skills:  

  • Understand how software containers work Understand the architecture of Kubernetes Understand the architecture of Google Cloud Platform
  • Understand how pod networking works in Kubernetes Engine
  • Create and manage Kubernetes Engine clusters using the GCP Console and gcloud/ kubectl commands Launch, roll back and expose jobs in Kubernetes
  • Manage access control using Kubernetes
  • RBAC and Google Cloud IAM Managing pod security policies and network policies Using Secrets and ConfigMaps to isolate security credentials and configuration artifacts
  • Understand GCP choices for managed storage services Monitor applications running in Kubernetes Engine
 

Course Outline
1 - INTRODUCTION TO GOOGLE CLOUD PLATFORM
  • Use the Google Cloud Platform Console
  • Use Cloud Shell
  • Define cloud computing
  • Identify GCPs compute services
  • Understand regions and zones
  • Understand the cloud resource hierarchy
  • Administer your GCP resources
2 - CONTAINERS AND KUBERNETES IN GCP
  • Create a container using Cloud Build
  • Store a container in Container Registry
  • Understand the relationship between Kubernetes and Google Kubernetes Engine (GKE)
  • Understand how to choose among GCP compute platforms
3 - KUBERNETES ARCHITECTURE
  • Understand the architecture of Kubernetes: pods, namespaces
  • Understand the control-plane components of Kubernetes
  • Create container images using Google Cloud Build
  • Store container images in Google Container Registry
  • Create a Kubernetes Engine cluster
4 - KUBERNETES OPERATIONS
  • Work with the kubectl command
  • Inspect the cluster and Pods
  • View a Pods console output
  • Sign in to a Pod interactively
5 - DEPLOYMENTS, JOBS, AND SCALING
  • Create and use Deployments
  • Create and run Jobs and CronJobs
  • Scale clusters manually and automatically
  • Configure Node and Pod affinity
  • Get software into your cluster with Helm charts and Kubernetes Marketplace
6 - GKE NETWORKING
  • Create Services to expose applications that are running within Pods
  • Use load balancers to expose Services to external clients
  • Create Ingress resources for HTTP(S) load balancing
  • Leverage container-native load balancing to improve Pod load balancing
  • Define Kubernetes network policies to allow and block traffic to pods
7 - PERSISTENT DATA AND STORAGE
  • Use Secrets to isolate security credentials
  • Use ConfigMaps to isolate configuration artifacts
  • Push out and roll back updates to Secrets and ConfigMaps
  • Configure Persistent Storage Volumes for Kubernetes Pods
  • Use StatefulSets to ensure that claims on persistent storage volumes persist across restarts
8 - ACCESS CONTROL AND SECURITY IN KUBERNETES AND KUBERNETES ENGINE
  • Understand Kubernetes authentication and authorization
  • Define Kubernetes RBAC roles and role bindings for accessing resources in namespaces
  • Define Kubernetes RBAC cluster roles and cluster role bindings for accessing cluster-scoped resources
  • Define Kubernetes pod security policies
  • Understand the structure of GCP IAM
  • Define IAM roles and policies for Kubernetes Engine cluster administration
9 - LOGGING AND MONITORING
  • Use Stackdriver to monitor and manage availability and performance
  • Locate and inspect Kubernetes logs
  • Create probes for wellness checks on live applications
10 - USING GCP MANAGED STORAGE SERVICES FROM KUBERNETES APPLICATIONS
  • Understand pros and cons for using a managed storage service versus self-managed containerized storage
  • Enable applications running in GKE to access GCP storage services
  • Understand use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and Bigquery from within a Kubernetes application

Actual course outline may vary depending on offering center. Contact your sales representative for more information.

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Course Length: 3 Days

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Description

This course teaches participants the following skills:

 

  • Understand how software containers work Understand the architecture of Kubernetes Understand the architecture of Google Cloud Platform
  • Understand how pod networking works in Kubernetes Engine
  • Create and manage Kubernetes Engine clusters using the GCP Console and gcloud/ kubectl commands Launch, roll back and expose jobs in Kubernetes
  • Manage access control using Kubernetes
  • RBAC and Google Cloud IAM Managing pod security policies and network policies Using Secrets and ConfigMaps to isolate security credentials and configuration artifacts
  • Understand GCP choices for managed storage services Monitor applications running in Kubernetes Engine

 

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