What you’ll learn
This course teaches participants the following skills:
Understand how software containers work.
Understand the architecture of Kubernetes.
Understand the architecture of Google Cloud.
Understand how pod networking works in Google Kubernetes Engine.
Create and manage Google Kubernetes Engine clusters using the Cloud Console and gcloud/ kubectl commands.
Launch, roll back and expose jobs in Kubernetes.
Manage access control using Kubernetes RBAC and 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 Google Kubernetes Engine.
Google Cloud at DDLS
DDLS is Australia's only national Google Cloud Authorised Training Partner. Get the skills needed to build, test and deploy applications on this highly scalable infrastructure. Engineered to handle the most data-intensive work you can throw at it, DDLS can support you through training wherever you are in your Cloud adoption journey.
Stay ahead of the technology curve
Don’t let your tech outpace the skills of your people
Quality instructors and content
Expert instructors with real world experience and the latest vendor- approved in-depth course content.
Chosen and awarded by the world’s leading vendors as preferred training partner.
Ahead of the technology curve
No matter your chosen technologies or platforms, we can help you stay one step ahead.
Who is the course for?
This course is intended for the following participants:
Cloud Architects, Administrators, and SysOps/DevOps Personnel
Individuals using Google Cloud to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud.
Module 1: Introduction to Google Cloud
Use the Google Cloud Console
Use Cloud Shell
Define cloud computing
Identify Google Cloud compute services
Understand regions and zones
Understand 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
Understand the relationship between Kubernetes and Google Kubernetes Engine (GKE)
Understand how to choose among Google Cloud Compute platforms
Module 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
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: Deployment, Jobs, and Scaling
Ways to create deployments
Services and scaling
Jobs and CronJobs
Controlling pod placement
Affinity and Anti-Affinity
Pod placement example
Taints and tolerations
Getting software into your cluster
Module 6: GKE Networking
Module 7: Persistent Data and Storage
Module 8: Access Control and Security in Kubernetes and Kubernetes Engine
Understand Kubernetes authentication and authorisation
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 IAM
Define IAM roles and policies for Kubernetes Engine cluster administration
Module 9: Logging and Monitoring
Use Cloud Monitoring 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
Understand pros and cons for using a managed storage service versus self-managed containerised storage
Enable applications running in GKE to access Google Cloud storage services
Understand use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore, and BigQuery from within a Kubernetes application
To get the most out of this course, participants should have:
Terms & Conditions