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Google Cloud Compute Engine Masterclass: Zero to Expert
Google Cloud Compute Engine Masterclass: Zero to Expert
Master Google Cloud VMs with hands-on labs: machine types, Hyperdisk, MIGs, load balancing, security and cost saving
Created byAnkit Mistry : 266,000+ Students
Last updated 11/2026
English
What you'll learn
- Create, connect to and manage Linux and Windows VMs on Google Cloud using the Console, gcloud CLI, REST API, Python and Terraform
- Choose the right machine family (C4, N4, E2, H4D, M4, Z3, A4, G4) and provisioning model: Standard, Spot, Flex-start or Reservation-bound
- Work with Hyperdisk, Persistent Disk and Local SSD, including storage pools, regional disks, asynchronous replication and CMEK encryption
- Protect data with snapshots, instant snapshots, custom images, machine images and Backup and DR Service
- Build secure VM networks with static IPs, firewall policies, Cloud NAT, multiple NICs, IPv6 and Private Google Access
- Secure VM access with OS Login, IAP tunnelling, service accounts, org policies, Shielded VM and Confidential VM
- Scale apps with managed instance groups, autoscaling, autohealing, rolling and canary updates behind global load balancers
- Run GPUs and TPUs, monitor VMs with the Ops Agent, patch fleets with VM Manager and troubleshoot VMs that won't boot
- Cut costs with Spot VMs, committed use discounts, reservations, rightsizing recommendations and the Pricing Calculator
- Build a production-style, highly available web application in a 5-part capstone project
Explore related topics
Course content
24 sections • 221 lectures • 9h 30m total length
Requirements
- No previous Google Cloud experience needed – we start from creating your account
- Basic computer and IT knowledge (what a server, an operating system and an IP address are)
- A Google account and a credit or debit card for the Google Cloud free trial (the course shows you how to set budget alerts)
- Basic Linux command-line familiarity is helpful but not required – every command is shown and explained
Description
Virtual machines are at the heart of Google Cloud. Hosting a website, running a database, training an AI model on GPUs or moving servers from your data center all start with Compute Engine.
This course takes you from your very first VM to production-ready designs, one step at a time. It is built around two kinds of lectures:
111 short theory lectures (3–4 minutes each): each explains one concept clearly, with no long, boring videos.
Hands-on labs: you build everything yourself in a real Google Cloud project, using both the Console and the gcloud CLI. Every lab comes with a step-by-step guide you can follow at your own pace.
What's inside (24 sections):
Creating and managing Linux and Windows VMs
Every machine family explained, including the newest C4, N4, Axion (Arm), H4D, M4, X4/X5, Z3 and A4/G4 GPU series
Spot, Flex-start and Reservation-bound VMs
Hyperdisk, storage pools, regional disks and disaster recovery
Snapshots, custom images, machine images and Backup and DR
VM networking, firewall policies, Cloud NAT and IPv6
Secure access with OS Login and IAP, plus Shielded and Confidential VMs
Managed instance groups, autoscaling, autohealing and rolling updates
Global and internal load balancing
GPUs and TPUs
Monitoring, VM Manager and troubleshooting
Pricing, committed use discounts and cost optimization
Automation with gcloud, the REST API, Python, Terraform and Infrastructure Manager
Migrating VMs to Google Cloud
The course ends with a 5-part capstone project. You build a highly available web application from a golden image, using:
a regional managed instance group
a global load balancer with Cloud Armor
private VMs with Cloud NAT and IAP access
monitoring and alerts
a zero-downtime rolling update
Every lab ends with a clean-up step, so you learn without surprise bills.
The course covers the Compute Engine topics in the Associate Cloud Engineer and Professional Cloud Architect exams.
Who this course is for:
- Beginners who want to learn Google Cloud through its most-used service: virtual machines
- System administrators and IT professionals moving servers from on-premises to the cloud
- Students preparing for the Google Cloud Associate Cloud Engineer or Professional Cloud Architect exams
- AWS EC2 or Azure VM engineers who want to learn the Google Cloud way of doing things
- DevOps and cloud engineers who want to automate VMs with gcloud, Terraform and managed instance groups
- Developers and AI/ML engineers who need GPU or TPU VMs for their workloads