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Home Architecting with Google Kubernetes Engine

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 Platform.

3 day course

Supporting material

Classroom, Virtual, Private

Classroom

Face to face, interactive classroom training run from our global training centres.

Virtual Classroom

A convenient and interactive learning experience, that enables you to attend on of our courses from the comfort of your own home or anywhere you can log on. We offer Virtual Classroom on selected live classroom courses where this will appear as an option under the location drop down if available. These can also be booked as Private Virtual Classrooms for exclusive business sessions.

Private

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.

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 at our training facility in San Francisco. We also offer private training at a location of your choice or via Virtual Classroom.

Course overview

Who should attend:

This course is suitable for Cloud architects, administrators, and those working in SysOps/DevOps. Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform 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 GCP 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 GCP choices for managed storage services
Monitor applications running in Kubernetes Engine

Prerequisites

To get the most of out of this course, you should have:

Completed Google Cloud Platform 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 Platform

The Google Cloud Platform Console
Cloud Shell
Define cloud computing
Identify GCPs compute services
Regions and zones
The cloud resource hierarchy
Administer your GCP resources

Module 2: Containers and Kubernetes in GCP

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 GCP 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 GCP 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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