- Understand the role of DevOps in modern cloud environments.
- Explore the core principles of DevOps, including CI/CD and infrastructure as code.
- Learn how Google Cloud supports DevOps practices with tools and services.
- Review the certification objectives and career benefits.
Google Cloud Certification Training Course
Google Professional Cloud DevOps Engineer Certification Training Course
The Google Professional Cloud DevOps Engineer Certification Training Course by Accumentum is designed to equip cloud professionals with the expertise needed to excel in managing and improving cloud-based infrastructure using Google’s DevOps principles.
Course focus: DevOps culture, practices, and tools on Google Cloud, including CI/CD, monitoring and logging, and infrastructure automation.
Course Overview
Master Google Cloud DevOps practices for reliable, scalable cloud operations.
The Google Professional Cloud DevOps Engineer Certification Training Course by Accumentum is designed to equip cloud professionals with the expertise needed to excel in managing and improving cloud-based infrastructure using Google’s DevOps principles. This course is ideal for those aiming to enhance their capabilities in cloud development and operations, focusing on designing scalable, efficient, and secure systems on Google Cloud.
Participants will gain a deep understanding of the DevOps culture, practices, and tools, including continuous integration and delivery (CI/CD), monitoring and logging, and infrastructure automation. The course also emphasizes building reliable systems, optimizing performance, and managing services effectively. Through hands-on exercises and real-world case studies, learners will explore practical applications of Google Cloud’s DevOps tools and best practices to align cloud operations with business goals, enabling seamless value delivery.
This training is a must for IT professionals and cloud engineers seeking to advance their careers by mastering Google Cloud’s DevOps methodologies. It prepares candidates not only to pass the certification exam but also to drive operational excellence and service reliability within their organizations.
Course Objectives
Course objectives for the Google Professional Cloud DevOps Engineer Certification Training Course.
01
Master DevOps Principles
Master the core principles and practices of DevOps for efficient and effective cloud operations.
02
Build Reliable Systems
Explore the foundations of building reliable systems, including monitoring, logging, and performance optimization within Google Cloud.
03
Apply Google Cloud DevOps Tools
Apply Google Cloud DevOps tools and methodologies in practical scenarios to improve service delivery and streamline operations.
04
Align DevOps with Business Goals
Learn to design and implement DevOps strategies that align cloud services with organizational objectives, focusing on value creation and operational excellence.
Who Should Attend
- Professionals managing cloud infrastructure and operations who want to deepen their expertise in Google Cloud’s DevOps practices.
- Individuals working in IT development, infrastructure, or system operations seeking to enhance their skills in implementing cloud-based DevOps solutions.
- Managers overseeing cloud services or projects who aim to align operations with Google Cloud DevOps best practices for improved outcomes.
- Beginners looking to build a strong foundation in DevOps methodologies and cloud operations to advance their careers in the Google Cloud ecosystem.
Prerequisites
- Participants should have a basic knowledge of IT services and operations to build on during the course.
- Prior certifications or specific experience with DevOps or Google Cloud are not required to enroll.
- Familiarity with how IT systems support business processes and objectives is helpful but not mandatory.
- The course is designed to accommodate beginners while offering in-depth insights for those with prior experience in cloud operations and DevOps practices.
Pathway Map
The training course follows a ten-module Google Cloud DevOps learning path.
The curriculum moves from DevOps fundamentals through reliable systems, CI/CD, monitoring and logging, infrastructure as code, security, microservices, automation, troubleshooting, and exam preparation.
1
Introduction to Google Cloud DevOps
2
Building Reliable and Scalable Systems
3
Continuous Integration and Delivery (CI/CD)
4
Monitoring and Logging
5
Infrastructure as Code (IaC)
6
Security and Compliance in DevOps
7
Managing Microservices
8
Automation in Google Cloud
9
Troubleshooting and Performance Optimization
10
Exam Preparation and Practice
Course Content
- Design systems with fault tolerance and high availability on Google Cloud.
- Explore best practices for scaling applications to handle increased demand.
- Implement load balancing and auto-scaling strategies.
- Understand disaster recovery options and strategies.
- Learn the principles and benefits of CI/CD pipelines.
- Use Google Cloud Build to automate the build, test, and deployment process.
- Integrate Google Cloud tools with third-party CI/CD platforms.
- Troubleshoot common CI/CD pipeline issues.
- Understand the importance of observability in cloud operations.
- Use Google Cloud Operations Suite for real-time monitoring and metrics analysis.
- Implement centralized logging with Cloud Logging and Logging Query Language.
- Set up alerts and dashboards for proactive issue detection.
- Discover the benefits of managing infrastructure with code.
- Use Terraform to create, update, and manage Google Cloud resources.
- Implement version control and modularization in IaC projects.
- Explore Google Cloud Deployment Manager for resource automation.
- Learn to integrate security into DevOps practices (DevSecOps).
- Configure Identity and Access Management (IAM) for secure access.
- Implement data encryption and secure key management with Google Cloud KMS.
- Ensure compliance with organizational and regulatory standards.
- Understand microservices architecture and its benefits in DevOps.
- Use Google Kubernetes Engine (GKE) for containerized application management.
- Implement service discovery and communication within microservices.
- Monitor and troubleshoot microservices using Cloud Operations Suite.
- Explore automation techniques for repetitive tasks.
- Implement cloud automation using Google Cloud Functions and Cloud Workflows.
- Use automation scripts to manage resources and configurations.
- Schedule recurring tasks with Cloud Scheduler.
- Diagnose and resolve common issues in cloud deployments.
- Optimize application performance using Google Cloud monitoring tools.
- Identify and mitigate bottlenecks in systems and applications.
- Learn best practices for debugging and incident response.
- Review certification objectives and exam structure.
- Practice with mock exams and case study scenarios.
- Develop time management and test-taking strategies.
- Gain insights into maintaining your certification and continuing education.
Course Features
Course features of the Google Professional Cloud DevOps Engineer Certification Training Course.
Interactive Learning
Engage with expert instructors and peers through training sessions, discussions, and practical exercises.
Comprehensive Study Materials
Access extensive resources, including e-books, video lectures, and practice exams.
Real-World Applications
Work on real-life case studies and scenarios to apply project management concepts.
Certification Preparation
Receive guidance and tips to successfully pass the Google Professional Cloud DevOps Engineer certification exam.
Certification Exam
Prepare for the Google Professional Cloud DevOps Engineer Certification Exam.
Cloud DevOps Engineer Exam Readiness
Accumentum’s training course prepares learners to design, implement, and manage secure, scalable, and reliable systems on Google Cloud.
Upon completing the course, you will be fully prepared to take the Google Professional Cloud DevOps Engineer Certification Exam. Earning this certification validates your expertise in cloud DevOps practices, demonstrating your ability to design, implement, and manage secure, scalable, and reliable systems on Google Cloud. This achievement will significantly boost your career prospects in cloud operations and DevOps roles.
Exam Blueprint
What Google says the PCDE exam covers.
Google's Professional Cloud DevOps Engineer exam guide has 5 sections and 19 objectives. We've copied each one below in Google's own wording, with the approximate share of the exam it carries.
Google describes the role this way: "A Professional Cloud DevOps Engineer implements processes and capabilities throughout the systems development lifecycle using Google-recommended methodologies and tools. They enable efficient software and infrastructure delivery while balancing reliability with delivery speed. They optimize and maintain production systems and services for both performance and cost."
Section 1: Bootstrapping and maintaining a Google Cloud organization (about 20% of the exam)
1.1 Designing the overall resource hierarchy for an organization
- Organizing resources (for example application-centric, projects, folders)
- Shared networking (for example Shared VPC, VPC Network Peering, Private Service Connect)
- Multi-project monitoring and logging
- Identity and Access Management (IAM) roles and organization-level policies
- Creating and managing service accounts
- Data residency
1.2 Managing infrastructure
- Infrastructure-as-code tooling and managed services (for example Infrastructure Manager, Cloud Foundation Toolkit, Config Connector, GitOps, Terraform, Helm)
- Making infrastructure changes using Google-recommended practices and blueprints
- Automation with scripting (for example Python, Go)
1.3 Designing a CI/CD architecture stack in Google Cloud, hybrid, and multi-cloud environments
- Continuous integration (CI) with Cloud Build
- Continuous delivery (CD) with Cloud Deploy, including Kustomize and Skaffold
- Artifact Registry configuration
- Widely used third-party tooling (for example Git, Jenkins, Argo CD, Packer, kpt)
- Security of CI/CD tooling
1.4 Managing multiple environments (for example staging, production)
- Managing ephemeral environments
- Managing configuration and policy
- Managing Google Kubernetes Engine (GKE) clusters across an enterprise (for example fleets)
- Safe and secure patching and upgrading practices
1.5 Enabling secure cloud development environments
- Configuring and managing cloud development environments (for example Cloud Workstations, Cloud Shell)
- Bootstrapping environments with required tooling (for example custom images, IDE, Cloud SDK)
- Leveraging AI to assist with development and operations (for example Gemini Code Assist, Gemini Cloud Assist, Gemini CLI)
Section 2: Building and implementing CI/CD pipelines, including continuous testing, for application, infrastructure, and machine learning workloads (about 25% of the exam)
2.1 Designing pipelines
- CI/CD of applications and infrastructure
- Artifact management with Artifact Registry
- Deployment to hybrid and multi-cloud environments (for example GKE)
- CI/CD pipeline triggers
- Configuring deployment processes (for example approval flows)
2.2 Implementing and managing pipelines
- Auditing and tracking deployments (for example Artifact Registry, Cloud Build, Cloud Deploy, Cloud Audit Logs)
- Deployment strategies (for example canary, blue/green, rolling, traffic splitting, feature flags) and defining success metrics based on application or ML pipeline telemetry
- Troubleshooting and mitigating deployment issues
2.3 Managing pipeline configuration and secrets
- Key management (for example Cloud Key Management Service)
- Configuration and secret management (for example Secret Manager, Certificate Manager, Parameter Manager, Workload Identity Federation)
- Build versus runtime secret injection
2.4 Securing the deployment pipeline
- Artifact Analysis and vulnerability scanning
- Software supply chain security (for example Binary Authorization, Supply-chain Levels for Software Artifacts [SLSA] framework)
- IAM policies based on environment
Section 3: Applying site reliability engineering practices (about 18% of the exam)
3.1 Balancing change, velocity, and reliability of the service
- Defining SLIs (for example availability, latency), SLOs, and SLAs
- Error budgets (for example Cloud Service Mesh definitions)
- Opportunity cost of risk and reliability (for example number of “nines”)
3.2 Managing service lifecycle
- Service management (for example planning, deployment, maintenance, retirement)
- Capacity planning (for example quotas, limits, reservations, Dynamic Workload Scheduler)
- Autoscaling (for example managed instance groups, Cloud Run, GKE)
3.3 Mitigating incident impact on users
- Draining/redirecting traffic
- Adding capacity
- Rollback strategies
Section 4: Implementing observability practices and troubleshooting issues (about 25% of the exam)
4.1 Instrumenting and collecting telemetry
- Collecting and importing logs (for example Ops Agent, OpenTelemetry, Cloud Audit Logs, VPC Flow Logs, Cloud Service Mesh)
- Optimizing logs (for example filtering, sampling, exclusions, cost management, source considerations)
- Collecting metrics (for example from applications, platforms, networking, Cloud Service Mesh, Google Cloud Managed Service for Prometheus, hybrid/multi-cloud environments)
- Creating synthetic monitors to proactively probe application endpoints and workflows
- Creating custom metrics, including log-based metrics
4.2 Managing and analyzing logs
- Analyzing logs using the Logs Explorer and the Logging query language
- Exporting and retaining logs (for example routing to BigQuery, Pub/Sub, Cloud Storage)
- Handling sensitive data (for example using log processors to redact personally identifiable information [PII], protected health information [PHI])
- Using Gemini Cloud Assist for AI-powered log analysis
4.3 Managing metrics, dashboards, and alerts
- Analyzing metrics using the Metrics Explorer
- Managing dashboards (for example creating, filtering, sharing, playbooks, PromQL)
- Configuring alerting and alerting policies (for example SLIs, SLOs, cost control)
- Integrating with third-party alerting tools (for example webhooks, PagerDuty, Rootly)
- Leveraging Gemini Cloud Assist for metrics interpretation
4.4 Capturing and analyzing distributed traces
- Utilizing tracing frameworks (for example OpenTelemetry)
- Analyzing trace waterfalls and spans
- Correlating trace IDs with structured logs
- Employing Gemini Cloud Assist for trace analysis
4.5 Troubleshooting issues
- Infrastructure issues
- CI/CD pipeline issues
- Application issues
- Observability issues
- Performance and latency issues
Section 5: Optimizing performance and cost (about 12% of the exam)
5.1 Collecting performance information in Google Cloud
- Application performance monitoring
- Active Assist insights and recommendations
5.2 Implementing FinOps practices for optimizing resource utilization and costs
- Observability costs
- Spot virtual machines (VMs)
- Optimizing resource usage for cost and efficiency
- Infrastructure cost planning (for example committed-use discounts, sustained-use discounts, network tiers)
- Leveraging Google Cloud recommenders (for example cost, security, performance, manageability, reliability)
- Optimizing individual workload costs (for example GKE, Cloud Run, Compute Engine)
Who It Is For
Is PCDE the right fit for you?
It suits DevOps engineers, site reliability engineers, platform engineers and release managers who run production systems on Google Cloud. Developers who own their own pipelines and on-call rotations fit well too.
Google lists no prerequisites. Its recommended experience is 3+ years of industry experience including 1+ years designing and managing production systems using Google Cloud.
Exam Format
How the PCDE exam works.
Exam details
- Length: 2 hours
- Registration fee: $200 (plus tax where applicable)
- Languages: English and Japanese
- Format: 50 to 60 multiple choice and multiple select questions
- Delivery: online proctored from a remote location, or onsite at a testing center
- Prerequisites: none
Google doesn't publish a passing score on the certification page, so we don't guess at one. What we can tell you is how the questions behave. Multiple select items ask for more than one correct answer. In our experience, many questions are short scenarios where two options look reasonable and only one fits every requirement in the prompt.
That's why we train you to read for the constraint first. Cost, latency, compliance, operational effort and time to deliver are the words that usually decide the answer.
Study Plan
A practical path to PCDE.
We start with Section 1, Bootstrapping and maintaining a Google Cloud organization. It's about 20% of the exam, so we work its 5 objectives in hands-on labs and short scenario drills.
Next we cover Section 2, Building and implementing CI/CD pipelines, including continuous testing, for application, infrastructure, and machine learning workloads. It's about 25% of the exam, so we work its 4 objectives in hands-on labs and short scenario drills.
Then we move to Section 3, Applying site reliability engineering practices. It's about 18% of the exam, so we work its 3 objectives in hands-on labs and short scenario drills.
After that comes Section 4, Implementing observability practices and troubleshooting issues. It's about 25% of the exam, so we work its 5 objectives in hands-on labs and short scenario drills.
We wrap up with Section 5, Optimizing performance and cost. It's about 12% of the exam, so we work its 2 objectives in hands-on labs and short scenario drills.
Section 2 carries the most weight, so it gets the most review time. In the last week we run timed practice at the real pace, revisit your weakest sections and reread the exam guide line by line. Google also publishes sample questions and a learning path on the certification page, and we use both.
Exam Policies
Retakes and renewal for PCDE.
For professional exams, Google allows a maximum of four attempts in a two year period. If you don't pass, you can take it again after 14 days. After a second miss you wait 60 days, and after a third you wait 365 days before a fourth attempt.
Every attempt counts toward that limit, whatever the language or delivery method, and payment is required each time you register.
Professional certifications can be renewed starting 60 days before the expiration date, and Google's terms say early attempts may be rejected and the exam fee forfeited.
Online proctored exams run through Pearson. Google notes that if a session can't be restarted after you've seen exam content, the attempt counts and the retake policy applies, so check your system and connection ahead of time.
Career Outlook
Where PCDE can take you.
PCDE is aimed at DevOps engineers and site reliability engineers. BLS doesn't track cloud roles separately, so we use the closest occupation as a reference.
For a sense of pay, BLS puts the May 2025 median annual wage for software developers, quality assurance analysts and testers at $134,040. A median is the midpoint, so half earned more and half earned less, and your own pay will depend on location, experience and employer. Source: BLS Occupational Outlook Handbook.
Funding
Ways to pay for PCDE training.
Paying on your own? PCDE prep is eligible for PathPay, our monthly payment plan. Terms of 3, 4 and 6 months carry no added fee. 9, 12 and 18 month terms add 5%, 10% and 15%. Course access opens when your first payment clears.
Our funding page lists every other way to pay, and you can always talk with us or email info@accumentum.net before you enroll.
Frequently Asked Questions
Understand how Accumentum’s Google Professional Cloud DevOps Engineer Certification Training Course supports certification readiness, course delivery, and career advancement.
It is a Google Cloud certification that validates your expertise in cloud DevOps practices, demonstrating your ability to design, implement, and manage secure, scalable, and reliable systems on Google Cloud.
Professionals managing cloud infrastructure and operations, individuals working in IT development, infrastructure, or system operations, managers overseeing cloud services or projects, and beginners looking to build a strong foundation in DevOps methodologies and cloud operations.
Participants should have a basic knowledge of IT services and operations. Prior certifications or specific experience with DevOps or Google Cloud are not required to enroll.
Yes. The course is designed to accommodate beginners while offering in-depth insights for those with prior experience in cloud operations and DevOps practices.
Ten modules cover Google Cloud DevOps fundamentals, building reliable and scalable systems, CI/CD, monitoring and logging, infrastructure as code, security and compliance, microservices, automation, troubleshooting and performance optimization, and exam preparation.
The course works with Google Cloud Build, Google Cloud Operations Suite, Cloud Logging, Terraform, Google Cloud Deployment Manager, Google Cloud KMS, Google Kubernetes Engine (GKE), Cloud Functions, Cloud Workflows, and Cloud Scheduler.
Yes. Through hands-on exercises and real-world case studies, learners explore practical applications of Google Cloud’s DevOps tools and best practices.
The final module reviews certification objectives and exam structure, provides mock exams and case study scenarios, and develops time management and test-taking strategies.
Earning the certification significantly boosts career prospects in cloud operations and DevOps roles, and prepares you to drive operational excellence and service reliability within your organization.
Join the Google Professional Cloud DevOps Engineer Certification Training Course at Accumentum by visiting Accumentum’s registration page linked on this page.
Google lists 2 hours for 50 to 60 multiple choice and multiple select questions.
Google lists a registration fee of $200, plus tax where applicable.
Google offers it in English and Japanese.
Yes. You can take an online proctored exam from a remote location or an onsite proctored exam at a testing center.
For professional exams, Google allows a maximum of four attempts in a two year period. If you don't pass, you can take it again after 14 days. After a second miss you wait 60 days, and after a third you wait 365 days before a fourth attempt.
Professional certifications can be renewed starting 60 days before the expiration date, and Google's terms say early attempts may be rejected and the exam fee forfeited.
Yes. PCDE prep is eligible for PathPay. Terms of 3, 4 and 6 months add no fee, and longer terms add 5% to 15%.
Enrollment
Enroll in the Google Professional Cloud DevOps Engineer Certification Training Course at Accumentum.
Join the Google Professional Cloud DevOps Engineer Certification Training Course at Accumentum to kickstart your journey toward becoming a certified cloud DevOps professional. For more details and to enroll, visit Accumentum’s registration page linked below.
Advance your career with Google Cloud DevOps expertise.
Prepare for the Google Professional Cloud DevOps Engineer Certification Exam and learn to design, implement, and manage secure, scalable, and reliable systems on Google Cloud.