GCP DevOps ceritfcation syllabus topics exam guide pdf

a structured GCP DevOps Roadmap to guide you from a beginner to an expert:

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Professional Cloud DevOps Engineer
Certification exam guide

A Professional Cloud DevOps Engineer implements processes and capabilities throughout the
systems development lifecycle using Google-recommended methodologies and tools. They
enable ecient soware and infrastructure delivery while balancing reliability with delivery
speed. They optimize and maintain production systems and services.

Section 1: Bootstrapping and maintaining a Google Cloud organization (~15% of
the exam)

1.1 Designing the overall resource hierarchy for an organization. Considerations include:
● Projects and folders
● Shared networking
● Multi-project monitoring and logging
● Identity and Access Management (IAM) roles and organization-level policies
● Creating and managing service accounts
● Organizing resources by using an application-centric approach (e.g., App Hub)
1.2 Managing infrastructure. Considerations include:
● Infrastructure-as-code tooling (e.g., Cloud Foundation Toolkit, Cong Connector,
Terraform, Helm)
● Making infrastructure changes using Google-recommended practices and blueprints
● Automation with scripting (e.g., Python, Go)
1.3 Designing a CI/CD architecture stack in Google Cloud, hybrid, and multi-cloud
environments. Considerations include:
● Continuous integration (CI) with Cloud Build
● Continuous delivery (CD) with Cloud Deploy, including Kustomize and Skaold
● Widely used third-party tooling (e.g., Jenkins, Git, Argo CD, Packer)
● Security of CI/CD tooling

1.4 Managing multiple environments (e.g., staging, production). Considerations include:
● Determining the number of environments and their purpose
● Managing ephemeral environments
● Conguration and policy management
● Managing Google Kubernetes Engine (GKE) clusters across an enterprise
● Safe and secure patching and upgrading practices
1.5 Enabling secure cloud development environments. Considerations include:
● Conguring and managing cloud development environments (e.g., Cloud Workstations,
Cloud Shell)
● Bootstrapping environments with required tooling (e.g., custom images, IDE, Cloud
SDK)
● Leveraging AI to assist with development and operations (e.g., Cloud Code, Gemini
Code Assist)

Section 2: Building and implementing CI/CD pipelines for applications and
infrastructure (~27% of the exam)

2.1 Designing and managing CI/CD pipelines. Considerations include:
● Artifact management with Artifact Registry
● Deployment to hybrid and multi-cloud environments (e.g., GKE Enterprise)
● CI/CD pipeline triggers
● Testing a new application version in the pipeline
● Conguring deployment processes (e.g., approval ows)
● CI/CD of serverless applications
● Applying CI/CD practices to infrastructure (e.g., GKE clusters, managed instance
groups, Cloud Service Mesh conguration)
2.2 Implementing CI/CD pipelines. Considerations include:
● Auditing and tracking deployments (e.g., Artifact Registry, Cloud Build, Cloud Deploy,
Cloud Audit Logs)
● Deployment strategies (e.g., canary, blue/green, rolling, trac spliing)
● Troubleshooting and mitigating deployment issues
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2.3 Managing CI/CD conguration and secrets. Considerations include:
● Key management (e.g., Cloud Key Management Service)
● Secret management (e.g., Secret Manager, Certicate Manager)
● Build versus runtime secret injection
2.4 Securing the CI/CD deployment pipeline. Considerations include:
● Vulnerability analysis with Artifact Registry
● Soware supply chain security (e.g., Binary Authorization, Supply-chain Levels for
Soware Artifacts [SLSA] framework)
● IAM policies based on environment

Section 3: Applying site reliability engineering practices to applications (~23% of
the exam)

3.1 Balancing change, velocity, and reliability of the service. Considerations include:
● Dening SLIs (e.g., availability, latency), SLOs, and SLAs
● Error budgets
● Opportunity cost of risk and reliability (e.g., number of “nines”)
3.2 Managing service lifecycle. Considerations include:
● Service management (e.g., introduction of a new service by using a pre-service
onboarding checklist, launch plan, or deployment plan, deployment, maintenance, and
retirement)
● Capacity planning (e.g., quotas, limits)
● Autoscaling (e.g., managed instance groups, Cloud Run, GKE)
3.3 Mitigating incident impact on users. Considerations include:
● Draining/redirecting trac
● Adding capacity
● Rollback strategies
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Section 4: Implementing observability practices (~20% of the exam)

4.1 Managing logs. Considerations include:
● Collecting and importing logs (e.g., Cloud Logging agent, Cloud Audit Logs, VPC Flow
Logs, Cloud Service Mesh)
● Logging optimization (e.g., ltering, sampling, exclusions, cost, source considerations)
● Exporting logs (e.g., BigQuery, Pub/Sub, for auditing)
● Retaining logs
● Analyzing logs
● Handling sensitive data (e.g., personally identiable information [PII], protected health
information [PHI])
4.2 Managing metrics. Considerations include:
● Collecting and analyzing metrics (e.g., application, plaorm, networking, Cloud Service
Mesh, Google Cloud Managed Service for Prometheus, hybrid/multi-cloud)
● Creating custom metrics from logs
● Using Metrics Explorer for ad hoc metric analysis
● Creating synthetic monitors
4.3 Managing dashboards and alerts. Considerations include:
● Managing dashboards (e.g., creating, ltering, sharing, playbooks)
● Conguring alerting and alerting policies (e.g., SLIs, SLOs, cost control)
● Widely used third-party alerting tools

Section 5: Optimizing performance and troubleshooting (~15% of the exam)

5.1 Troubleshooting issues. Considerations include:
● Infrastructure issues
● Application issues
● CI/CD pipeline issues
● Observability issues
● Performance and latency issues

5.2 Implementing debugging tools in Google Cloud. Considerations include:
● Application instrumentation
● Cloud Trace
● Error Reporting
5.3 Optimizing resource utilization and costs. Considerations include:
● Observability costs
● Spot virtual machines (VMs)
● Infrastructure cost planning (e.g., commied-use discounts, sustained-use discounts,
network tiers)
● Google Cloud recommenders (e.g., cost, security, performance, manageability,
reliability)

gcp devops guide syllabus as on feb 2025

this skill boost course not enogugh https://www.cloudskillsboost.google/paths/20

Step 1: Learn the Basics of DevOps (0-1 Month)

Goal: Understand DevOps culture, CI/CD, and infrastructure as code (IaC).

Topics to Cover:

• What is DevOps? Principles & Benefits
• DevOps Lifecycle (Plan, Develop, Build, Test, Release, Deploy, Operate, Monitor)
• CI/CD Pipelines Overview
• Infrastructure as Code (IaC) Basics
• Git, GitHub, GitLab Basics

Resources:

• The DevOps Handbook (Book)
• DevOps Roadmap on KodeKloud, Udemy
• Google DevOps Foundations (Google Cloud Skills Boost)

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Step 2: Get Familiar with Google Cloud Platform (1-3 Months)

Goal: Understand GCP services and basic cloud computing concepts.

Topics to Cover:

• GCP Overview & Architecture
• GCP IAM (Identity & Access Management)
• Compute Services (Compute Engine, Kubernetes Engine, App Engine)
• Storage Services (Cloud Storage, Filestore, BigQuery)
• Networking (VPC, Load Balancers, Cloud NAT)
• Security & Compliance

Resources:

• Google Cloud Essentials (Google Cloud Skills Boost)
• Google Cloud Free Tier ($300 credits for practice)
• Coursera: Google Cloud Fundamentals

Practice:

• Deploy a VM on Compute Engine
• Set up IAM roles and permissions

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Step 3: Master Infrastructure as Code (IaC) (3-6 Months)

Goal: Automate cloud infrastructure using IaC tools.

Topics to Cover:

• Terraform (Infrastructure Automation)
• Google Cloud Deployment Manager
• YAML & JSON for Configuration Management
• Version Control with Git

Resources:

• HashiCorp Terraform Certification Guide
• Terraform GCP Modules (registry.terraform.io)
• Google Cloud Deployment Manager Docs

Practice:

• Write Terraform scripts to deploy a Kubernetes cluster
• Use Deployment Manager to provision GCP resources

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Step 4: Learn Kubernetes & Containerization (6-9 Months)

Goal: Deploy and manage containerized applications on GCP.

Topics to Cover:

• Docker Basics (Containers, Images, Volumes)
• Kubernetes Fundamentals (Pods, Services, Deployments)
• Google Kubernetes Engine (GKE)
• Helm Charts for Application Management
• Service Mesh (Istio)

Resources:

• Kubernetes.io Official Docs
• Docker & Kubernetes on GCP (YouTube, Udemy)
• Google Cloud Kubernetes Engine (Skill Boost)

Practice:

• Deploy a microservices application on GKE
• Use Helm to manage Kubernetes applications

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Step 5: Build CI/CD Pipelines on GCP (9-12 Months)

Goal: Automate deployments with CI/CD.

Topics to Cover:

• Cloud Build (CI/CD on GCP)
• Cloud Source Repositories (GitHub/GitLab Integration)
• Artifact Registry for Storing Docker Images
• Cloud Deploy for Continuous Deployment
• Jenkins & GitHub Actions for CI/CD

Resources:

• Google Cloud CI/CD Training
• Jenkins Pipelines & GCP Integration

Practice:

• Create a CI/CD pipeline using Cloud Build
• Deploy a GKE application using GitOps

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Step 6: Implement Monitoring & Security (12-15 Months)

Goal: Improve reliability and security in cloud environments.

Topics to Cover:

• Cloud Logging & Monitoring (Cloud Operations Suite)
• Prometheus & Grafana for Monitoring
• Cloud Security Best Practices
• Identity-Aware Proxy (IAP)
• Secrets Management (Secret Manager)

Resources:

• Google Cloud Security Training
• Prometheus & Grafana Docs

Practice:

• Set up logging & monitoring for a GKE cluster
• Secure workloads using IAM roles & IAP

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Step 7: Advanced DevOps & Site Reliability Engineering (SRE) (15+ Months)

Goal: Implement advanced DevOps practices and automation.

Topics to Cover:

• Site Reliability Engineering (SRE) Principles
• Infrastructure Monitoring & Incident Response
• Serverless Technologies (Cloud Run, Functions)
• Auto-scaling & Load Balancing
• Cost Optimization & FinOps

Resources:

• Google SRE Handbook
• Coursera: Site Reliability Engineering on GCP

Practice:

• Implement Blue-Green Deployment
• Set up auto-healing & auto-scaling workloads

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Step 8: Get Certified & Apply for Jobs

Recommended Certifications:
Google Associate Cloud Engineer
Google Professional DevOps Engineer
Kubernetes Certified Administrator (CKA)

Interview Preparation:

• Practice DevOps interview questions
• Work on real-world projects & contribute to open source
• Build a GitHub portfolio showcasing DevOps skills

GCP Google Cloud Professional DevOps Engineer Certification by udemy

What you’ll learn

1. DevOps & SRE Principal

In this module I will teach you DevOps best practices principle on which DevOps concept developed and how to implement all those DevOps practices with site reliability engineering concept like error budget, blameless post mortem, toil automation SLI, SLO, SLA.

2. CI/CD Pipeline implementation

In this module I will teach you about some docker basics how to create docker images and push to the central repository. How to deploy your application to various computer product in a GCP environment. We will implement 5 CI CD pipeline with the help of various GCP services like cloud source repositories, cloud build, artifact registry container registry, cloud deployment manager.

3. Other tools

Here we will learn about the two important toll Jenkins and terraform.

4. Container security deployment

In this module we will learn about various products of which we make secure container deployment like binary authorization, container scanning API and Google manage Base image to make your docker image more secure

5. Monitoring and logging

In this module we will learn how to monitor and lock service with cloud monitoring and logging and its various features like uptime check, alerting policy, Log exploration, Log router, Log sink, Log base metrics, debugger, trace and error reporting

6. Optimization of Resources

In this section we will learn about few topics optimize your service resource from various perspective like Billing, total cost of consideration, preemptible virtual Machine at a reduced cost, Discounts.

GCP Devops Git hub materials

https://github.com/sathishvj/awesome-gcp-certifications/blob/master/professional-cloud-devops-engineer.md

 

reference links

https://sre.google/

https://www.linkedin.com/pulse/how-pass-google-professional-cloud-devops-engineer-tips-saurabh-singh/