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GCP Google Cloud Professional DevOps Engineer Certification

Name: GCP Google Cloud Professional DevOps Engineer Certification
Rating: 4.4 (2706 reviews)

Master Google Cloud DevOps Engineering with 16+ hours of high-quality video training and 100+ real-world hands-on demos.

Bestseller

Role Play

Created byAnkit Mistry : 200,000+ Students, GCP Certification - Google Cloud Academy | Associate Cloud & Professional Engineer Certifications

Last updated 11/2025

English

What you'll learn

Understand the core responsibilities and mindset of a Google Cloud Professional DevOps Engineer.
Learn how to design, implement, and maintain reliable systems using SRE principles.
Master key concepts such as SLIs, SLOs, SLAs, error budgets, and blameless postmortems.
Implement automation strategies to reduce toil and improve operational efficiency.
Explore Google Cloud infrastructure essentials such as networking, IAM, compute, and storage.
Learn how to build, package, and store application artifacts using Artifact Registry.
Develop hands-on CI/CD pipelines using Cloud Build, including triggers, steps, and automation workflows.
Deploy applications reliably using Google Cloud Deploy with progressive delivery.
Implement end-to-end deployment pipelines integrating Cloud Build, Artifact Registry, and GKE.
Learn to configure Kubernetes clusters on Google Kubernetes Engine (GKE) and deploy microservices.
Understand GKE security, node pools, autoscaling, networking, and workload best practices.
Apply Infrastructure as Code (IaC) using Terraform, including modules, state management, and automation.
Learn how to modernize and manage hybrid/multi-cloud applications using Anthos.
Implement advanced DevOps practices such as canary deployments, blue-green rollouts, and GitOps.
Learn to monitor applications using Cloud Monitoring dashboards, metrics, uptime checks, and alerts.
Analyze logs effectively using Cloud Logging, log-based metrics, and alerting policies.
Understand security best practices including IAM roles, service accounts, secrets management, and workload identity.
Build secure CI/CD pipelines with vulnerability scanning and policy enforcement.
Learn incident response strategies including monitoring, alerting, and production-readiness checklists.
Prepare confidently for the Google Cloud Professional DevOps Engineer Certification with structured, hands-on guidance.

Course content

23 sections • 130 lectures • 16h 35m total length

Introduction & Certification Overview7:12
Udemy tips1:52
Adjust playback speed from 0.5x to 2x and watch at 720p or higher, then rate the course from one to five stars and share feedback or use ask me later.

Google Cloud Overview3:41
Create GCP Account6:04
Create a Google Cloud free trial account by signing in, providing country and billing details, and activating $300 credit for 91 days.
[Hands-on] GCP Console Walkthrough6:36
Explore the Google Cloud console with a free trial: navigate services, use the search bar, view and customize the dashboard, manage projects, and explore tools like Cloud Shell.
GCP Regions & Zones10:41
Learn how Google Cloud regions and zones optimize low latency, high availability, and compliance by deploying resources across multiple zones and regions for disaster recovery.
[Hands-on] Creating GCP Projects4:14
Create a GCP project in this hands-on session, a top-level entity in the resource hierarchy, and note the project name, id, and number, including no organization versus organization-based accounts.
[Hands-on] Google Cloud Shell8:09
Explore Google Cloud Shell to manage Google Cloud services with the cloud console and gcloud CLI, using a full Linux VM with preinstalled tools and a browser editor.
Course Downloads0:05

1. Create Github Account & Repository3:47
Learn to create your first GitHub account and private repository for a Google Cloud DevOps trigger, and prepare to clone it locally in the next step.
2. Clone Repo with Authentication & Push Changes10:28
3. Create Cloudbuild.yaml7:05
Create cloudbuild.yaml to define cloud build steps in yaml, using alpine's sh entry point to display repository, branch, and commit, enable cloud logging, and set up a GitHub-connected trigger.
4. Create Trigger, Github connection from Google Cloud Console11:02
Create a cloud build trigger in the Google Cloud Console, connect to GitHub, select the main branch, and configure cloudbuild.yaml with a service account for secure execution.
5. Push Changes and Test Flow7:04
6. Explore All Build Details10:50
Explore the cloud build details and review build history filters. Analyze steps, triggers, and permissions while learning how logging options enhance cloud build insights.
7. Explorer Different Logging Options.mp48:31

1. Create Python App Trigger8:17
Explore creating a Python app trigger with cloudbuild.yaml, using a Python docker image to run hello.py, and configuring a Cloud Source Repository trigger for automatic builds.
2. Timeout options3:50
Explore how to configure timeout options in cloudbuild.yaml, including default 60-minute timeouts, maximum 24 hours, and per-step or global timeout overrides.
3. Build and Store Docker Image in Artifact Registry Part - 111:08
Learn to build a trigger that creates and pushes a docker image to Google artifact registry using a Flask Python app, with a dockerfile, requirements, and cloudbuild.yaml.
4. Build and Store Docker Image in Artifact Registry Part - 28:06
5. Deploy Container Image to Cloud Run (Serverless Deployment)21:05
6. Schedule Trigger11:10
7. Substitution Variables in Cloud Build17:58
Learn substitution variables in Google Cloud Build, including built-in project and build ids and custom YAML variables; discover how to pass them through triggers, manual invocations, and gcloud builds submit.
8. artifacts in cloudbuild.yaml8:16
Configure artifacts in Cloud Build YAML to preserve files created during a build. Store outputs like info.txt in a Google Cloud Storage bucket using the artifacts section.
9. waitfor16:52
Explore wait for in cloudbuild.yaml to control step execution, including dash wait for, parallel flows, dependent steps, and failure handling.
10. Create Maven Package and Push to Artifact Registry10:58
685

Section Introduction2:00
History of Software Development Cycle4:02
DevOps & SRE5:53
Explain how DevOps reduces silos between developers and operators, embraces failure, and drives automation and measurement, and how SRE defines roles and practices like blameless postmortems and error budgets.
Role of SRE3:15
Define the site reliability engineer role and responsibilities across development and operations, and how SRE collaborates with developers on CI/CD, toil, blameless postmortems, and metrics on Google Cloud.
Blameless Postmortem4:30
Error Budgets4:31
Define and apply an error budget to balance system change and stability, using reliability metrics to guide gradual deployments and downtime limits for feature releases.
Eliminating Toil3:27
SLO (Service level Objective)2:45
SLI (Service Level Indicator)4:21
Define and monitor the internal SLI to measure real performance against the SLO target, tracking latency to ensure 96% of requests meet 300 ms.
SLA (Service level Agreement)5:57
Explore service level agreements (SLA) as external commitments, distinguish them from internal SLOs, and learn how cloud providers offer compensation based on uptime thresholds.
Summary of above Concepts1:57

Introduction to Docker7:17
[Hands-on] Create Simple WebApp on Cloud Shell5:05
Create a simple Python-based web app using Flask in Google Cloud Shell, run it, preview via web review, then package as a Docker file and containerize.
[Hands-on] Create Dockerfile9:40
Containerize a Python Flask app by creating a Dockerfile, using a Python base image, installing Flask, copying main.py, and running the app to build and push a Docker image.
[Hands-on] Build Docker Image from Dockerfile11:35
[Hands-on] Push Docker image to container registry3:12
Push a docker image to a private Google Cloud container registry and enable the container registry API. Tag images with versions like 1.0 and 2.0 and push to gcr.io.

What is Container - V26:50
Explore containerization basics, including images and registries, and compare containers with virtual machines to see how Docker runtime enables portable, fast deployments on Google Cloud Run and GKE.
Dive into Docker - V25:09
Discover how Docker bundles apps into images to create lightweight containers that run on Linux systems, and how Dockerfile builds these images stored in Google Container Registry or Artifact Registry.
Introduction to Container Registry - V25:50
Explore the Google Cloud container registry, a project-scoped docker image store for pushing, pulling, and tagging docker images, and compare it to artifact registry with binary authorization.
Create First Docker images - V211:30
Optimize Docker image & Run Docker Container - V29:44
Switch Node base image to alpine, build a lightweight docker image, run a container with port mapping, and prepare the image for push to container or artifact registry.
Push Docker Image to Container registry - V27:55
Introduction to Artifact Registry - V28:46
Learn how Artifact Registry overcomes container registry limitations with fine-grained Cloud IAM access, regional and multi-regional repos, and support for Docker images and npm, Java, and Python packages.
Push Docker image to Artifact Registry - V24:49
Authenticate and configure docker for artifact registry in a chosen region using Cloud Shell, re-tag and push a docker image to artifact registry, and verify the upload.

Different Deployment Method for GCP Compute11:36
Explore Google Cloud compute options for deploying applications—Compute Engine, Kubernetes Engine, App Engine, Cloud Run, and Cloud Functions—and master blue-green, rolling, canary, and traffic splitting deployment strategies.
[Hands-on] Deploy to Google Cloud Function - I9:17
[Hands-on] Deploy to Google Cloud Function - II4:41
[Hands-on] Deploy app on Google App Engine - I14:15
[Hands-on] Deploy app on Google App Engine - II8:18
Deploy a new Google App Engine version without promoting traffic, use traffic splitting to gradually migrate to version 2.0, and verify traffic allocation across versions.
[Hands-on] Deploy Docker image on Cloud Run - I8:43
[Hands-on] Deploy Docker image on Cloud Run - II5:45
[Hands-on] Deploy Docker image on GKE - I9:36
Deploy a docker image on GKE by creating a cluster, deploying workloads, and exposing the service with a load balancer; demonstrate version 1 and 2 deployments.
[Hands-on] Deploy Docker image on GKE - II4:27
Master rolling updates of docker images on GKE using workloads, upgrading to version 2.0 with minimum seconds ready and controlled maximum surge and unavailable, and capture deployment YAML for CI/CD.
[Hands-on] Deploy on Google Compute Engine - I11:07
[Hands-on] Deploy on Google Compute Engine - II7:42
Deploy a non-containerized web app on Google Compute Engine with Ubuntu 18.04 LTS, enable http on port 80, install Apache2, and automate setup via a startup script.
[Hands-on] Instance template11:04
[Hands-on] Deploy with Managed Instance Group8:52
Create a managed instance group from the template to run homogeneous, auto-scaling virtual machines. Tune minimum and maximum instance settings, then look ahead to load balancing.
[Hands-on] Add Load balancer8:34

Introduction to CI/CD Pipeline5:27
Explore how continuous integration pushes code from a source code repository to a build server, creates artifacts, and how continuous deployment automatically deploys to a deployment server.
Different services for CI/CD5:40
Explore Google Cloud ci/cd services, from Cloud Source Repository and Cloud Build to artifact registries and deployment targets like Compute Engine, Kubernetes Engine, App Engine, Cloud Run, and Function.
CI/CD Pipeline implementation0:02

Introduction to Pipeline - 13:02
Build an automated ci/cd pipeline on Google Cloud by pushing code to a source repository, triggering Cloud Build to create Docker images from a Dockerfile and push to Container Registry.
[Hands-on] Step 01 : Pipeline - 112:02
Set up a Google Cloud source repository, commit and push code with git in Cloud Shell, and follow a simple repo-1 naming convention for the first ci/cd pipeline step.
[Hands-on] Step 02 : Pipeline - 17:58
[Hands-on] Step 03 : Pipeline - 13:03
Push code to the repository in cloud shell to trigger a new build. Commit __main__.py, push to master, and observe the automated CI/CD pipeline start and finish the build.

Requirements

Basic understanding of cloud computing concepts (no prior Google Cloud experience required).
Familiarity with Linux command line, software development, or IT operations is helpful but not mandatory.
A willingness to learn hands-on DevOps tools, automation, and Google Cloud services through practical examples.
Credit or debit card for Google cloud free trial account

Description

In today’s rapidly evolving technological landscape, organizations demand faster software delivery, higher reliability, and world-class performance. Businesses across every industry are adopting cloud-native DevOps, Site Reliability Engineering (SRE) practices, and modern automation tools to stay competitive. As a result, the demand for skilled Google Cloud DevOps Engineers is growing exponentially. This course is designed to help you master all the essential concepts, tools, and practical skills required to pass the Google Cloud Professional DevOps Engineer Certification—and become a highly skilled DevOps professional capable of architecting, deploying, automating, monitoring, and securing modern cloud applications on Google Cloud.

This comprehensive and hands-on course takes you through every major area of the certification exam blueprint while equipping you with real-world skills you can apply immediately. Whether you're a beginner stepping into DevOps, a cloud engineer looking to level up, or an experienced professional wanting to validate your skills, this course gives you everything you need in one structured learning path.

Why This Certification Is So Important

The Google Cloud Professional DevOps Engineer Certification is one of the most respected and career-boosting credentials in the cloud ecosystem. Companies worldwide use Google Cloud to build scalable, reliable, and secure applications—and DevOps Engineers are the backbone of ensuring these applications run efficiently.

By earning this certification, you demonstrate your ability to:

Implement SRE principles
Build CI/CD pipelines
Deploy applications on Kubernetes (GKE)
Automate infrastructure using Terraform
Monitor systems using Cloud Monitoring and Logging
Manage Cloud Build, Cloud Deploy, Artifact Registry
Ensure security, reliability, observability, and scalability

This course is crafted to help you build these skills using a highly practical and concept-driven approach, ensuring you not only pass the exam but also perform confidently in real DevOps engineering roles.

What Makes This Course Unique?

This course is not just theory. It blends conceptual understanding with hands-on demos, real-world examples, architectural breakdowns, and exam-focused explanations. It covers all major DevOps tools and Google Cloud services that you will encounter in the certification exam and in real enterprise environments.

Key highlights include:

Clear explanation of each domain from the exam guide
Step-by-step breakdowns of SRE concepts like SLOs, SLIs, SLAs, error budgets
Practical CI/CD pipelines using Cloud Build
Deployments using Cloud Deploy and Artifact Registry
Infrastructure automation with Terraform
Kubernetes deployments on Google Kubernetes Engine (GKE)
Anthos, hybrid cloud, and multi-cloud DevOps workflows
Logging, monitoring, dashboards, alerts, and production readiness
Security fundamentals including IAM, service accounts, least privilege, and workload identity
Mastering DevOps workflows from code to production

This combination of theory + practice ensures you fully understand the “why” behind each tool and technique.

What You Will Learn in This Course

This course covers the complete skill set required to become a successful Google Cloud DevOps Engineer. Some major learning outcomes include:

Understanding the role and responsibilities of a Professional Cloud DevOps Engineer
Applying Site Reliability Engineering (SRE) principles for reliability and performance
Creating meaningful SLIs, SLOs, SLAs, and managing error budgets
Implementing blameless postmortems, root cause analysis, and incident response workflows
Building fully automated CI/CD pipelines using Cloud Build and Cloud Deploy
Storing, managing, and scanning artifacts using Artifact Registry
Creating production-ready Kubernetes workloads on GKE
Configuring clusters, autoscaling, workload identity, node pools, networking, and security
Automating infrastructure deployments using Terraform
Writing Terraform modules, managing versions, and creating reproducible environments
Monitoring systems using Cloud Monitoring, dashboards, metrics, alerts, uptime checks
Working with Cloud Logging, logs-based metrics, and troubleshooting distributed systems
Implementing DevOps security practices including IAM, Secrets Manager, VPC Service Controls
Using Anthos for hybrid and multi-cloud DevOps
Implementing blue-green, canary, and progressive delivery strategies
Preparing thoroughly for the Google Cloud Professional DevOps Engineer certification exam

Every topic is broken down in a simple, intuitive manner so learners at any experience level can easily follow along.

Course Structure Overview

The course is divided into well-organized sections, each containing multiple lectures that progressively build your knowledge:

1. Introduction to DevOps, Google Cloud, and SRE

You begin by understanding the evolution of DevOps, Google Cloud fundamentals, and the core SRE concepts that power reliability at Google scale. We explore the history of software development, how DevOps emerged, and where SRE fits into modern engineering practices.

2. SRE Fundamentals

This section dives deep into essential SRE practices such as SLIs, SLOs, SLAs, error budgets, blameless postmortems, eliminating toil, and building resilient systems. These principles form the backbone of the DevOps exam and your job as a DevOps engineer.

3. Google Cloud Services for DevOps

You learn foundational services like IAM, Cloud Storage, Compute Engine, networking, service accounts, and other Google Cloud basics essential for DevOps workflows.

4. CI/CD with Cloud Build

This highly practical section teaches you how to build, automate, and integrate CI/CD pipelines:

Build triggers
Build steps
Substitutions
YAML configuration
Multi-step pipelines
Securing pipelines
Integrating testing and scanning tools

5. Artifact Registry

You explore how to configure Docker repositories, store artifacts, scan vulnerabilities, and integrate the registry with Cloud Build and GKE.

6. Continuous Delivery with Cloud Deploy

Learn how to automate deployments using release pipelines, rollout strategies, approvals, and multi-environment progression.

7. Google Kubernetes Engine (GKE)

One of the exam’s biggest sections, this part teaches you:

Cluster creation
Node pools
Autoscaling
Workload management
Ingress & networking
GKE security
Logging & monitoring for Kubernetes
Rolling updates and canary deployments

8. Infrastructure Automation Using Terraform

You learn to write Terraform code for provisioning Google Cloud resources, managing remote backend states, creating reusable modules, and automating cloud infrastructure end-to-end.

9. Monitoring, Logging & Observability

This section covers:

Cloud Monitoring dashboards
Alerting policies
Uptime checks
SLO monitoring
Cloud Logging queries
Log-based metrics
Debugging production incidents

10. Security, IAM & Governance

Understand DevOps-specific security practices including IAM roles, service accounts, workloads identity, least privilege, Secrets Manager, and secure pipeline design.

11. Anthos & Modern DevOps Workflows

You learn how modern enterprises use Anthos to manage multi-cloud and hybrid DevOps, service mesh, and centralized policy management.

12. Exam Preparation Section

The course includes targeted exam guidance, tips, strategies, and key concepts you must revise before attempting the certification exam.

Anyone wanting a high-paying DevOps or Site Reliability Engineering role will benefit immensely from this course.

Career Impact & Industry Demand

Completing this course and achieving the Professional DevOps Engineer certification opens doors to roles such as:

Cloud DevOps Engineer
SRE (Site Reliability Engineer)
Cloud Engineer
Infrastructure Engineer
CI/CD Architect
Kubernetes Engineer
Cloud Automation Engineer

Global salaries for DevOps engineers are among the highest in the industry. Companies running scalable systems—Google, Meta, Amazon, Microsoft, Netflix, Uber, and countless others—need professionals with these skills.

Teaching Style & Learning Approach

This course is designed with a teaching flow that simplifies even the most complex DevOps concepts. You will learn through:

Visual explanations
Real-world analogies
Hands-on demos
Step-by-step walkthroughs
Clear, beginner-friendly explanations

You’ll never feel lost—every concept builds upon the previous one.

Final Word

If you want to become a highly skilled Google Cloud DevOps Engineer, build world-class pipelines, deploy on GKE, automate infrastructure, implement SRE principles, and master monitoring, logging, and security—this is the perfect course for you.

With structured content, practical demos, and certification-focused guidance, you’ll walk away fully prepared for the Google Cloud Professional DevOps Engineer exam and confident in your ability to operate production-grade systems on Google Cloud.

Enroll today and accelerate your career in DevOps and Cloud Engineering!

Regards

Ankit Mistry

Who this course is for:

IT professionals, cloud engineers, and developers preparing for the Google Cloud Professional DevOps Engineer Certification.
DevOps engineers looking to deepen their skills in CI/CD, Cloud Build, Cloud Deploy, GKE, Terraform, and SRE practices.
System administrators and operations engineers who want to transition into cloud-native DevOps roles.
Software engineers who want to learn how to build, deploy, monitor, and maintain scalable cloud applications on Google Cloud.
Students, beginners, or career-switchers seeking a practical, hands-on pathway into DevOps and Google Cloud engineering.

GCP Google Cloud Professional DevOps Engineer Certification

What you'll learn

Explore related topics

Course content

Introduction2 lectures • 9min

GCP Basics7 lectures • 40min

[NEW] Creating First trigger in Google Cloud Build - V27 lectures • 59min

[NEW] More Feature of Google Cloud Build - V210 lectures • 1hr 58min

SRE - Site Reliability Engineering11 lectures • 43min

Basics of Docker5 lectures • 37min

Docker, Container & Registry - V28 lectures • 1hr 1min

Deploy Application on Google Cloud14 lectures • 2hr 4min

CI/CD Pipeline3 lectures • 11min

CI/CD Pipeline - 14 lectures • 26min

Requirements

Description

Who this course is for: