Requirements

• Basic understanding of cloud computing concepts. Familiarity with Google Cloud Platform services. Some experience with DevOps practices and tools. No advanced programming skills required.

Description

GCP Professional DevOps Engineer Certification Practice Test – 2024

Are you gearing up for the GCP Professional DevOps Engineer certification exam? Boost your preparation with our top-tier practice questions, each complemented by in-depth answer explanations. Our practice tests are meticulously structured to encompass all aspects of GCP DevOps engineering, from fundamental concepts to complex application development and management in the cloud. The COMPREHENSIVE SOLUTION EXPLANATIONS offered at the end of each test are designed to deepen your understanding, hone your skills, and build your confidence for the real exam. Keep pace with the latest exam curriculum and standards, as our content is regularly updated to mirror the most recent developments.

COURSE FEATURES

• High-quality questions + Detailed solution explanations

• Reference links to official GCP documentation & reputable sources

• Content that reflects the newest exam syllabus

• Build knowledge, skills, & confidence for the exam

• Take full-length practice exams in one sitting

• Tackle intricate GCP DevOps engineering scenarios

• Master time management and exam strategies

• Lifetime course access for continuous certification preparation

• Mobile-friendly format for learning anytime, anywhere – Accessible via the Udemy mobile app

EXAM SECTIONS AND TOPICS

Section 1: Bootstrapping a Google Cloud Organization for DevOps (~17% of the exam) – 9 questions

1. Designing the overall resource hierarchy for an organization (2 questions)

   • Projects and folders

   • Shared networking

   • Identity and Access Management (IAM) roles and organization-level policies

   • Creating and managing service accounts

2. Managing infrastructure as code (2 questions)

   • Infrastructure as code tooling (e.g., Cloud Foundation Toolkit, Config Connector, Terraform, Helm)

   • Making infrastructure changes using Google-recommended practices and infrastructure as code blueprints

   • Immutable architecture

3. Designing a CI/CD architecture stack in Google Cloud, hybrid, and multi-cloud environments (2 questions)

   • CI with Cloud Build

   • CD with Google Cloud Deploy

   • Widely used third-party tooling (e.g., Jenkins, Git, ArgoCD, Packer)

   • Security of CI/CD tooling

4. Managing multiple environments (e.g., staging, production) (3 questions)

   • Determining the number of environments and their purpose

   • Creating environments dynamically for each feature branch with Google Kubernetes Engine (GKE) and Terraform

   • Config Management

Section 2: Building and Implementing CI/CD Pipelines for a Service (~23% of the exam) – 12 questions

1. Designing and managing CI/CD pipelines (3 questions)

   • Artifact management with Artifact Registry

   • Deployment to hybrid and multi-cloud environments (e.g., Anthos, GKE)

   • CI/CD pipeline triggers

   • Testing a new application version in the pipeline

   • Configuring deployment processes (e.g., approval flows)

   • CI/CD of serverless applications

2. Implementing CI/CD pipelines (3 questions)

   • Auditing and tracking deployments (e.g., Artifact Registry, Cloud Build, Google Cloud Deploy, Cloud Audit Logs)

   • Deployment strategies (e.g., canary, blue/green, rolling, traffic splitting)

   • Rollback strategies

   • Troubleshooting deployment issues

3. Managing CI/CD configuration and secrets (3 questions)

   • Secure storage methods and key rotation services (e.g., Cloud Key Management Service, Secret Manager)

   • Secret management

   • Build versus runtime secret injection

4. Securing the CI/CD deployment pipeline (3 questions)

   • Vulnerability analysis with Artifact Registry

   • Binary Authorization

   • IAM policies per environment

Section 3: Applying Site Reliability Engineering Practices to a Service (~23% of the exam) – 12 questions

1. Balancing change, velocity, and reliability of the service (2 questions)

   • Discovering SLIs (e.g., availability, latency)

   • Defining SLOs and understanding SLAs

   • Error budgets

   • Toil automation

   • Opportunity cost of risk and reliability (e.g., number of “nines”)

2. Managing service lifecycle (2 questions)

   • 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 and limits management)

   • Autoscaling using managed instance groups, Cloud Run, Cloud Functions, or GKE

   • Implementing feedback loops to improve a service

3. Ensuring healthy communication and collaboration for operations (2 questions)

   • Preventing burnout (e.g., setting up automation processes to prevent burnout)

   • Fostering a culture of learning and blamelessness

   • Establishing joint ownership of services to eliminate team silos

4. Mitigating incident impact on users (3 questions)

   • Communicating during an incident

   • Draining/redirecting traffic

   • Adding capacity

5. Conducting a postmortem (3 questions)

   • Documenting root causes

   • Creating and prioritizing action items

   • Communicating the postmortem to stakeholders

Section 4: Implementing Service Monitoring Strategies (~21% of the exam) – 11 questions

1. Managing logs (2 questions)

   • Collecting structured and unstructured logs from Compute Engine, GKE, and serverless platforms using Cloud Logging

   • Configuring the Cloud Logging agent

   • Collecting logs from outside Google Cloud

   • Sending application logs directly to the Cloud Logging API

   • Log levels (e.g., info, error, debug, fatal)

   • Optimizing logs (e.g., multiline logging, exceptions, size, cost)

2. Managing metrics with Cloud Monitoring (2 questions)

   • Collecting and analyzing application and platform metrics

   • Collecting networking and service mesh metrics

   • Using Metrics Explorer for ad hoc metric analysis

   • Creating custom metrics from logs

3. Managing dashboards and alerts in Cloud Monitoring (2 questions)

   • Creating a monitoring dashboard

   • Filtering and sharing dashboards

   • Configuring alerting

   • Defining alerting policies based on SLOs and SLIs

   • Automating alerting policy definition using Terraform

   • Using Google Cloud Managed Service for Prometheus to collect metrics and set up monitoring and alerting

4. Managing Cloud Logging platform (2 questions)

   • Enabling data access logs (e.g., Cloud Audit Logs)

   • Enabling VPC Flow Logs

   • Viewing logs in the Google Cloud console

   • Using basic versus advanced log filters

   • Logs exclusion versus logs export

   • Project-level versus organization-level export

   • Managing and viewing log exports

   • Sending logs to an external logging platform

   • Filtering and redacting sensitive data (e.g., personally identifiable information [PII], protected health information [PHI])

5. Implementing logging and monitoring access controls (3 questions)

   • Restricting access to audit logs and VPC Flow Logs with Cloud Logging

   • Restricting export configuration with Cloud Logging

   • Allowing metric and log writing with Cloud Monitoring

Section 5: Optimizing the Service Performance (~16% of the exam) – 8 questions

1. Identifying service performance issues (3 questions)

   • Using Google Cloud’s operations suite to identify cloud resource utilization

   • Interpreting service mesh telemetry

   • Troubleshooting issues with compute resources

   • Troubleshooting deploy time and runtime issues with applications

   • Troubleshooting network issues (e.g., VPC Flow Logs, firewall logs, latency, network details)

SAMPLE QUESTION + SOLUTION EXPLANATION

Question: To enhance the security of your CI/CD pipeline, you need to perform vulnerability analysis on container images before deployment. Which Google Cloud service should you use, and how does it help?

A. Use Cloud Spanner to monitor container images.

B. Enable vulnerability scanning in Artifact Registry to analyze container images for known security issues, ensuring that vulnerabilities are identified and addressed before deployment.

C. Manually inspect container images for vulnerabilities.

D. Deploy container images directly without any vulnerability checks.

Correct Answer: B

Explanation: Enabling vulnerability scanning in Artifact Registry helps analyze container images for known security issues. This proactive measure ensures that vulnerabilities are identified and addressed before deployment, enhancing the security and compliance of the CI/CD pipeline.

Who this course is for:

• IT professionals aiming to become certified Google Cloud Professional DevOps Engineers. Cloud engineers looking to enhance their knowledge and skills in DevOps practices. Beginners interested in learning about cloud DevOps engineering with a focus on Google Cloud Platform. Anyone preparing for the Google Cloud Professional DevOps Engineer certification exam.