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Google Compute Engine Administrator

Last Updated: 08-03-2025

The Google Compute Engine Administrator course is designed for IT professionals, system administrators, and cloud engineers who want to gain deep expertise in managing Google Compute Engine (GCE) instances and virtual machine (VM) infrastructures on Google Cloud Platform (GCP). This hands-on training will guide you through the process of deploying, configuring, and managing scalable virtual machines using Google Cloud’s Compute Engine. You’ll learn to optimize performance, manage workloads efficiently, secure virtual machines, and automate administrative tasks, making you proficient in managing cloud-based infrastructure for enterprise-grade applications. Upon completion of this course, you'll have the skills to design and manage high-availability systems and ensure seamless operation of Google Compute Engine instances in a cloud environment.

 

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Schedule Learners Course Fee (Incl. of all Taxes) Register Your Interest
December 22nd - 25th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
Guaranteed-to-Run
10% Off
$1,280
$1,152
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December 27th - 04th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
10% Off
$1,280
$1,152
January 05th - 08th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
20% Off
$1,280
$1,024
January 10th - 18th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
20% Off
$1,280
$1,024
January 12th - 15th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
20% Off
$1,280
$1,024
January 19th - 28th
06:00 AM - 10:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
20% Off
$1,280
$1,024
January 26th - 29th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
Guaranteed-to-Run
20% Off
$1,280
$1,024

Course Prerequisites

  • Basic understanding of cloud computing concepts such as virtual machines, networking, and storage.
  • Experience with the Google Cloud Console and basic knowledge of Google Cloud services such as Google Cloud Storage and Google Cloud Networking.
  • Familiarity with Linux or Windows server administration and basic system commands.
  • Basic knowledge of command-line interface (CLI) tools and scripting for automation (Bash, Python, or similar).
  • No prior experience with Google Compute Engine is required, though familiarity with cloud infrastructures will be helpful.

Learning Objectives

By the end of the Google Compute Engine Administrator course, you will be able to:

  1. Understand the core components of Google Compute Engine (GCE), including instances, virtual machine types, and their use cases.
  2. Deploy and configure virtual machine instances using Google Cloud Console and Cloud SDK (gcloud command-line tool).
  3. Create and manage VM images and disk snapshots for backup and disaster recovery purposes.
  4. Implement auto-scaling and load balancing for high availability and better performance of applications running on virtual machines.
  5. Secure Compute Engine instances using Google Cloud IAM (Identity and Access Management), firewall rules, and security best practices.
  6. Set up persistent disks, cloud storage, and cloud snapshots to manage application data and backups efficiently.
  7. Manage virtual machine networking in Google Cloud, including VPC networks, firewalls, and Cloud DNS.
  8. Automate instance creation and management using Google Cloud Deployment Manager and Terraform for Infrastructure as Code (IaC).
  9. Monitor and optimize Compute Engine performance using Google Cloud Operations Suite (formerly Stackdriver) for logs, metrics, and alerts.
  10. Design and implement cost-effective cloud infrastructures by managing VM configurations, disk types, and other resources in Google Cloud.
  11. Prepare for Google Cloud certifications such as the Professional Cloud Architect or Associate Cloud Engineer.

Target Audience

This course is ideal for:

  • System administrators and cloud engineers who want to enhance their ability to manage and optimize virtual machines and cloud infrastructure on Google Cloud.
  • IT professionals looking to transition to the cloud and specialize in Google Compute Engine.
  • Developers who need to gain a deeper understanding of virtual machine management and infrastructure deployment for cloud-based applications.
  • DevOps engineers and infrastructure managers looking to learn best practices for managing cloud workloads and ensuring uptime in scalable cloud environments.
  • Technical architects and solution architects looking to design and implement highly available systems with Google Cloud Compute Engine.

Course Modules

  • Introduction to Compute Engine

    • Overview of Google Compute Engine and its role in Google Cloud.
    • Understanding the Google Cloud Console and Cloud SDK.
    • Creating and managing virtual machines on Google Compute Engine.
  • Configuring and Managing VM Instances

    • Creating custom images and instance templates.
    • Managing VM instance configurations, including metadata and custom attributes.
    • Scaling VM instances manually and using instance groups.
    • Working with persistent disks and snapshots.
  • Networking in Compute Engine

    • Configuring VPC networks and subnetting.
    • Setting up internal and external IP addresses.
    • Configuring firewalls and network security.
    • Load balancing and traffic distribution.
  • Security and Identity Management

    • Configuring IAM (Identity and Access Management) for VM instances.
    • Managing access to Compute Engine resources and integrating with Google Cloud IAM.
    • Using Google Cloud Security features, including encryption and audit logs.
  • Monitoring and Troubleshooting

    • Setting up Google Cloud Monitoring for VM health and performance.
    • Analyzing logs with Google Cloud Logging.
    • Troubleshooting VM instances and network issues.
  • Automation and Cost Optimization

    • Automating VM provisioning with scripts and Cloud Deployment Manager.
    • Managing cost-effective resource provisioning.
    • Optimizing performance and reducing costs through autoscaling and preemptible VMs.

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