Architecting with Google Kubernetes Engine
This three-day course introduces participants to deploying and managing containerised applications on Google Kubernetes Engine (GKE) and other services provided by Google Cloud Platform.
Through a series of presentations, demonstrations and hands-on activities, participants explore and deploy components such as pods, containers, deployments and services, as well as networks and application services. This course also explores practical cases such as security and access management, organisation and monitoring of resources.
- Duration: 3 days
- Format: Face-to-face or distance learning
- Prerequisites: Completion of the Google Cloud Fundamentals course or equivalent experience, basic skills with command line tools and the Linux environment, experience in system administration, deployment and management of applications in a cloud or on-premises environment
- Audience: Cloud architects, cloud engineers, SysOps/DevOps administrators and engineers, site reliability engineers, IT managers
- Price: Please contact us
- More information in our training catalogue
The course in detail
Module 1: Introduction to Google Cloud Platform
- Use the Google Cloud Platform console.
- Use Cloud Shell.
- Define cloud computing.
- Identify GCP compute services.
- Understand regions and areas.
- Understand the hierarchy of cloud resources.
Administer your GCP resources.
Module 2: Containers and Kubernetes in GCP
- Create a container using Cloud Build.
- Store a container in the container register.
- Understand the relationship between Kubernetes and Google Kubernetes Engine (GKE).
- Understand how to choose among the GCP compute platforms.
Module 3: Kubernetes architecture
- Understand the Kubernetes architecture: pods, namespaces, etc.
- Understand the components of the Kubernetes control plane.
- Create container images using Google Cloud Build.
- Store container images in the Google Container Registry.
- Create a Kubernetes Engine cluster.
Module 4: Kubernetes operations
- Work with the kubectl command.
- Inspect the cluster and pods.
- Analyse pod logs.
- Connect to a pod interactively.
Module 5: Deployments, jobs and scaling up
- Create and use deployments.
- Create and run jobs and CronJobs.
- Scale clusters up manually and automatically.
- Set up node and pod affinity.
- Install software in your cluster with Helm charts and the Kubernetes marketplace.
Module 6: The GKE network
- Create services to expose applications running in pods and use load balancers to expose services to external clients.
- Create Ingress resources for HTTP(S) load balancing.
- Leverage native container load balancing to improve pod load balancing.
- Define Kubernetes network policies to authorise and block traffic to pods.
Module 7: Persistent data and storage
- Use secrets to isolate sensitive information and use ConfigMaps to isolate configurations.
- Publish and undo updates to Secrets and ConfigMaps.
- Configure persistent storage volumes for Kubernetes pods.
- Use StatefulSets to ensure claims on persistent storage volumes persist across reboots.
Module 8: Access control and security in Kubernetes and GKE
- Understand Kubernetes authentication and authorisation.
- Define Kubernetes RBACs for namespace resource access.
- Define Kubernetes RBACs for cluster resource access.
- Define Kubernetes pod security policies.
- Understand the GCP IAM structure and define roles and IAM policies for Kubernetes Engine cluster administration.
Module 9: Logging and monitoring
- Use Stackdriver to monitor and manage availability and performance and locate and inspect Kubernetes logs.
- Create probes to monitor the health of applications.
Module 10: Using GCP managed storage services from Kubernetes applications
- Understand the advantages and disadvantages of using a managed storage service versus standard container storage.
- Connect a GKE application to GCP storage services.
- Understand the use cases for Cloud Storage,
- Cloud SQL, Cloud Spanner, Cloud Bigtable, Cloud Firestore and BigQuery from a Kubernetes application.
