Architecting with Google Kubernetes Engine

Learn how to deploy and manage containerised applications on Google Kubernetes Engine (GKE) and the other services provided by Google Cloud.
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3 day course
Supporting material
Google Cloud Partner of the Year
A private training session for your team. Groups can be of any size, at a location of your choice including our training centres.

As an authorised Google Cloud Training Partner, Jellyfish has been selected by Google to facilitate the delivery of this three-day course.

Jellyfish has recently been named a Google Cloud Specialisation Partner of the Year. This title recognises our commitment to provide world-leading Cloud-based Training solutions that help our clients succeed.

Through a combination of presentations, demos, and hands-on labs, you’ll explore and deploy solution elements, including infrastructure components such as networks, systems, and application services.

This course also covers deploying practical solutions including security and access management, resource management, and resource monitoring.

This Architecting with Google Kubernetes Engine course will run over three consecutive days and is available as a private training session that can be delivered virutally or at a location of your choice.

Course overview
Who should attend:
This course is suitable for Cloud architects, administrators, and those working in SysOps / DevOps. Individuals using Google Cloud to create new solutions or to integrate existing systems, application environments, and infrastructure with Google Cloud will also benefit from this course.
Walk away with the ability to:
  • Explain how software containers work and the architecture of Kubernetes
  • Understand how pod networking works in Kubernetes Engine
  • Create and manage Kubernetes Engine clusters using the Google Cloud Console and gcloud/ kubectl commands
  • Launch, roll back and expose jobs in Kubernetes
  • Manage access control using Kubernetes RBAC and Google Cloud IAM
  • Manage pod security policies and network policies
  • Use Secrets and ConfigMaps to isolate security credentials and configuration artifacts
  • Understand Google Cloud choices for managed storage services
  • Monitor applications running in Kubernetes Engine
To get the most of out of this course, you should have:
  • Completed the Google Cloud Fundamentals: Core Infrastructure course or have equivalent experience
  • Basic proficiency with command-line tools and Linux operating system environments
Course agenda
Module 1: Introduction to Google Cloud
  • The Google Cloud Console
  • Cloud Shell
  • Define cloud computing
  • Identify Google Cloud's compute services
  • Regions and zones
  • The cloud resource hierarchy
  • Administer your Google Cloud resources
Module 2: Containers and Kubernetes in Google Cloud
  • Create a container using Cloud Build
  • Store a container in Container Registry
  • The relationship between Kubernetes and Google Kubernetes Engine (GKE)
  • How to choose among Google Cloud compute platforms
Module 3: Kubernetes Architecture
  • The architecture of Kubernetes: pods, namespaces
  • 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
Module 4: Kubernetes Operations
  • Work with the kubectl command
  • Inspect the cluster and Pods
  • View a Pods console output
  • Sign in to a Pod interactively
Module 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
Module 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
Module 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
Module 8: Access Control and Security in Kubernetes and Kubernetes Engine
  • Kubernetes authentication and authorisation
  • Kubernetes RBAC roles and role bindings for accessing resources in namespaces
  • Kubernetes RBAC cluster roles and cluster role bindings for accessing cluster-scoped resources
  • Define Kubernetes pod security policies
  • The structure of GCP IAM
  • IAM roles and policies for Kubernetes Engine cluster administration
Module 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
Module 10: Using Google Cloud Managed Storage Services from Kubernetes Applications
  • Pros and cons for using a managed storage service versus self-managed containerised storage
  • Enable applications running in GKE to access GCP storage services
  • Use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and BigQuery from within a Kubernetes application
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