As an authorised Google Cloud Training Partner, we’ve been selected by Google to facilitate the delivery of this three-day Kubernetes course.
Through a combination of presentations, demos, and hands-on labs, you’ll explore and deploy solution elements, including infrastructure components such as networks, Pods, containers, and application services.
We’ll also show you how to deploy practical solutions including security and access management, resource management, and resource monitoring.
Our Architecting with Google Kubernetes Engine course is delivered via Virtual Classroom. We also offer it as a private training session that can be delivered virtually or at a location of your choice in the UK.
Course overview
Who should attend:
What you'll learn:
By the end of this course, you will be able to:
- Explain how software containers work, as well as the architecture of Kubernetes and Google Cloud
- 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 artefacts
- Understand Google Cloud 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 the Google Cloud Fundamentals: Core Infrastructure course, or have equivalent experience
- Basic proficiency with command-line tools and Linux operating system environments
Course agenda
- 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
- 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
- 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
- Work with the kubectl command
- Inspect the cluster and Pods
- View a Pod’s console output
- Sign in to a Pod interactively
- 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
- 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
- Use Secrets to isolate security credentials
- Use ConfigMaps to isolate configuration artefacts
- 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
- 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
- Use Cloud Monitoring to monitor and manage availability and performance
- Locate and inspect Kubernetes logs
- Create probes for wellness checks on live 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
- Automate the deployment of Google Cloud services using Deployment Manager or Terraform
- Outline the Google Cloud Marketplace
- Understand pros and cons for using a managed storage service vs. 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