Google Professional Cloud DevOps Engineer Exam Preparation

AVG Duration11h
Course Created with Sketch. 9 Resources Created with Sketch. 1 Labs Created with Sketch. 5


******** PREVIEW *******

This learning path is still in development and requires additional content to cover all of the points assessed in the exam. We are busy working on new content to fill the gaps. Until then, the courses and labs currently available in this Learning Path will allow you to get started in preparing for this certification.


This learning path is designed to help you prepare for the Google Professional Cloud DevOps Engineer exam. Candidates who pass the exam will earn the Google Professional Cloud DevOps Engineer certification.

The Professional Cloud DevOps Engineer exam tests your knowledge of five subject areas.

If you have any feedback relating to this learning path, feel free to get in touch with us at

Learning Objectives

  • Applying site reliability engineering principles to a service
  • Building and implementing CI/CD pipelines for a service
  • Implementing service monitoring strategies
  • Optimizing service performance
  • Managing service incidents

Intended Audience

  • DevOps Engineers who want to build/maintain infrastructure on Google Cloud Platform
  • People preparing for the Google Professional Cloud DevOps Engineer exam


  • Basic understanding of cloud concepts (virtual machines, containers, networking, etc)
  • General knowledge of IT architecture
  • Familiarity with DevOps practices and principles


Your certificate for this learning path

Learning Path Steps


In this course, you'll learn about GCP services such as compute, storage, and networking, and how to create virtual machines and web apps using the Google Cloud Console and gcloud CLI.


Use the gcloud CLI in Google Cloud Shell to create signed URLs to grant anyone access to objects stored in Google Cloud Storage for a set duration in this Lab.


This course explores GCP’s compute services, specifically App Engine and Kubernetes Engine.


Learn how to deploy containerized applications in Google Kubernetes Engine (GKE) clusters from the Cloud Console, Cloud Shell, and Marketplace in this Lab.


This course is intended to help prepare individuals seeking to pass the Google Cloud Professional Cloud Developer Certification Exam.


This course explores how to build CI/CD pipelines using tools such as Google Cloud Build, Google Container Registry, and Source Repository.


In this lab, you will use the GCP Cloud Deployment Manager service to create a template and then use it in the configuration you will deploy. You will also use Jinja for defining a template and YAML for the configuration.


In this course, we will explore some of the tools available to build and manage development environments intended for deployment on Google Cloud Platform products.


In this lab, you will clone a git repo that contains a simple docker application, you will set up a cloud build configuration, and you will run the cloud build configuration you defined.


This hands-on tutorial teaches you monitoring, testing, managing, and troubleshooting your GCP app infrastructure.


This course looks at how to control access to logging and monitoring on Google Cloud Platform through the use of permissions, roles, VPC Service Controls, and Logs Exporter.


In this lab, you will understand the best practices to monitor a compute engine instance by viewing the usage, creating alert policies and creating a chart.


This course explores the various ways to optimize resource utilization on GCP.


This course focuses on the predominant parts of managing service incidents and utilizing Google Cloud Platform to aid in the endeavor.

About the Author

Daniel began his career as a Software Engineer, focusing mostly on web and mobile development. After twenty years of dealing with insufficient training and fragmented documentation, he decided to use his extensive experience to help the next generation of engineers.

Daniel has spent his most recent years designing and running technical classes for both Amazon and Microsoft. Today at Cloud Academy, he is working on building out an extensive Google Cloud training library.

When he isn’t working or tinkering in his home lab, Daniel enjoys BBQing, target shooting, and watching classic movies.