Google Kubernetes Engine (GKE) Training Course: Deploy and operate Kubernetes on Google Cloud
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Description of the training: Google Kubernetes Engine (GKE) Training Course: Deploy and operate Kubernetes on Google Cloud
The Google Kubernetes Engine training course is for people who know Kubernetes and discover that it does not behave quite the same way at Google. Which stands to reason: Kubernetes came from there, and GKE is its most tightly integrated implementation on the market — with automation the others do not have, and defaults you need to understand before you have to live with them.
Over 3 days, you build a cluster end to end and operate it: the trade-off between Autopilot and Standard mode (the first decision, and the one that shapes everything else), VPC-native networking and pod addressing, identity through Workload Identity, pod and node autoscaling, exposure via Ingress and the Gateway API, observability with Cloud Operations, hardening and cost control. Every building block is stress-tested by a deliberately induced incident.
This course extends our Kubernetes Training Course and our Advanced Kubernetes and CI/CD Training Course by anchoring them in the Google ecosystem. If you are starting from containers, our Docker Training Course and our From Docker to Kubernetes Training Course lay the foundations. On the Google Cloud side, our Google Cloud Associate Cloud Engineer Training Course covers the infrastructure prerequisites, our Google Cloud Professional Cloud DevOps Engineer Training Course goes further into SRE practices, and our Google Cloud Professional Cloud Security Engineer Training Course into hardening. To provision your clusters as code, see our Terraform Fundamentals Training Course. If your estate is multicloud, our AWS EKS Training Course covers the same ground on the Amazon side.
Good to know
Sessions are guaranteed from a single registrant (except in cases of force majeure). A preliminary discussion takes place between the participant and/or a company representative to fully take into account the participant’s profile. Assessment: quizzes, role-play and practical exercises. A certificate of completion is issued at the end of the training. This training covers the container portion of the Google Cloud Professional Cloud DevOps Engineer certification syllabus (exam not included). This training is part of our Cloud Computing Training Courses catalogue. Discover our other cloud training courses to master architectures, services and best practices on AWS, Azure and GCP. To get started on AWS, we recommend our AWS Cloud Practitioner Training Course as a prerequisite, which lays the foundations of the Amazon Cloud.
Objectives of the training: Google Kubernetes Engine (GKE) Training Course: Deploy and operate Kubernetes on Google Cloud
By the end of the training, participants will be able to:
- Choose between GKE Autopilot and GKE Standard with full knowledge of the consequences.
- Deploy a GKE cluster and understand how responsibility is shared with Google.
- Configure cluster networking (VPC-native, pod addressing, network policies).
- Grant Google Cloud permissions to pods without static keys, using Workload Identity.
- Implement pod and node autoscaling.
- Expose applications with Ingress, the Gateway API and Google load balancing.
- Monitor, harden and control the cost of a GKE cluster in production.
Prerequisites of the training: Google Kubernetes Engine (GKE) Training Course: Deploy and operate Kubernetes on Google Cloud
- Prior Kubernetes practice is essential: pods, deployments, services and namespaces should already be familiar, and you should be able to read a YAML manifest. Our Kubernetes Training Course, or equivalent experience, is the expected starting point.
- Some initial Google Cloud experience (projects, IAM, VPC) is also required. The level of the Cloud Digital Leader certification, or the basics of Associate Cloud Engineer, is amply sufficient.
- Because every participant is unique, a personalised discussion with our expert allows us to design a training course perfectly aligned with their objectives.
Target audience of the training: Google Kubernetes Engine (GKE) Training Course: Deploy and operate Kubernetes on Google Cloud
- DevOps and SRE engineers running, or about to run, Kubernetes on Google Cloud.
- Cloud and systems administrators migrating containerised workloads to GKE.
- Architects who must arbitrate between GKE Autopilot, GKE Standard and Cloud Run.
- Developers who want to understand the real runtime environment of their applications.
Detailed programme of the training: Google Kubernetes Engine (GKE) Training Course: Deploy and operate Kubernetes on Google Cloud
GKE: Autopilot or Standard, the decision that shapes everything
Nodes, node pools and capacity
Networking: VPC-native, Ingress and the Gateway API
Identity: Workload Identity
Autoscaling
Storage and stateful workloads
Observability, security and cost
Course highlights
- tackles Kubernetes where it genuinely gets tricky: its integration into Google Cloud (VPC-native, Workload Identity, Autopilot);
- settles the Autopilot / Standard trade-off in the very first module, since it conditions everything else;
- devotes around 60% of the time to hands-on work, with incidents deliberately induced on the cluster;
- runs in a group of 1 to 3 participants, which allows work on your own clusters.
FAQ
Do I need to know Kubernetes already?
Yes — this is the one genuinely blocking prerequisite. The course does not re-explain what a pod or a deployment is: it deals with what Kubernetes becomes once it sits on Google Cloud. If you are starting out, our Kubernetes Training Course is the necessary step first — the preliminary discussion is there to check this.
Autopilot or Standard: does the course help me choose?
That is the subject of the first module, and the decision shapes everything else about the cluster. Autopilot suits most cases and removes node management; Standard makes sense when you need to control the hardware, install privileged agents or tune finely. Both modes are used during the course.
How does this differ from the AWS EKS training course?
The subject is the same — managed Kubernetes — but the integrations differ markedly: Workload Identity versus IRSA, Autopilot (which has no AWS equivalent), VPC-native versus VPC CNI, Google Ingress versus the ALB Controller. If your estate is multicloud, taking both makes sense; otherwise, take the one for your provider.
Does the course prepare for a Google certification?
It covers the container portion of the Professional Cloud DevOps Engineer certification syllabus, but there is no Google certification dedicated to GKE. If certification is your goal, our Google Cloud Professional Cloud DevOps Engineer Training Course is the route to take.