Realistic Google Professional-Cloud-DevOps-Engineer Exam Questions with Accurate Answers

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Google Professional-Cloud-DevOps-Engineer Exam Syllabus Topics:

SectionWeightObjectives
Monitoring, Logging, and Debugging12%- Log management
  • 1. Structuring logs for efficient querying
  • 2. Implementing log-based metrics
  • 3. Configuring log retention policies
- Debugging and troubleshooting
  • 1. Debugging with Cloud Trace distributed tracing
  • 2. Using Cloud Debugger and Error Reporting
  • 3. Analyzing performance profiles with Cloud Profiler
- Cloud Operations Suite
  • 1. Implementing Cloud Logging with log sinks
  • 2. Configuring Cloud Monitoring metrics
  • 3. Creating uptime checks and alerts
Reliability and Site Reliability Engineering (SRE)24%- SLOs, SLIs, and SLAs
  • 1. Defining and implementing Service Level Objectives
  • 2. Error budget policies and management
  • 3. Setting appropriate Service Level Agreements
  • 4. Creating and interpreting Service Level Indicators
- Incident management
  • 1. Implementing on-call procedures
  • 2. Post-incident reviews and blameless postmortems
  • 3. Configuring automated incident response
- Monitoring and observability
  • 1. Configuring Cloud Monitoring and Logging
  • 2. Setting up alerting policies and incident management
  • 3. Creating dashboards for service health visibility
  • 4. Implementing distributed tracing with Cloud Trace
CI/CD Pipeline Development26%- CI/CD best practices
  • 1. Managing secrets in CI/CD pipelines
  • 2. Implementing shift-left testing
  • 3. Configuring quality gates and code coverage
- Containerization and Docker
  • 1. Implementing container security best practices
  • 2. Managing container registries
  • 3. Creating optimized Docker images (multi-stage builds)
- Designing and implementing CI/CD pipelines
  • 1. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.)
  • 2. Implementing build automation scripts
  • 3. Setting up artifact management with Artifact Registry
  • 4. Configuring build triggers and webhooks
  • 5. Configuring build caching strategies
Cloud Infrastructure Automation24%- Configuration management
  • 1. Using Ansible for configuration management
  • 2. Implementing configuration drift detection
  • 3. Managing secrets with Secret Manager
- Infrastructure as Code (IaC)
  • 1. Managing infrastructure modules and state
  • 2. Implementing with Terraform
  • 3. Implementing immutable infrastructure patterns
- Deployment strategies
  • 1. Blue-green deployments
  • 2. Feature flags with Firebase Remote Config or LaunchDarkly
  • 3. Canary releases and progressive rollouts
  • 4. Rolling updates with Kubernetes
Microservices Architecture14%- API management
  • 1. Implementing API versioning strategies
  • 2. Exposing APIs with Cloud Endpoints / Apigee
- Container orchestration with GKE
  • 1. Managing pod lifecycle and resource quotas
  • 2. Designing Kubernetes cluster architectures
  • 3. Implementing workload deployment and scaling
  • 4. Configuring node pools and auto-scaling
- Service mesh and networking
  • 1. Implementing Anthos Service Mesh / Istio
  • 2. Configuring traffic management and load balancing
  • 3. Implementing service-to-service authentication

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q39-Q44):

NEW QUESTION # 39
Your uses Jenkins running on Google Cloud VM instances for CI/CD. You need to extend the functionality to use infrastructure as code automation by using Terraform. You must ensure that the Terraform Jenkins instance is authorized to create Google Cloud resources. You want to follow Google-recommended practices- What should you do?

Answer: B

Explanation:
The correct answer is C)
Confirming that the Jenkins VM instance has an attached service account with the appropriate Identity and Access Management (IAM) permissions is the best way to ensure that the Terraform Jenkins instance is authorized to create Google Cloud resources. This follows the Google-recommended practice of using service accounts to authenticate and authorize applications running on Google Cloud1. Service accounts are associated with private keys that can be used to generate access tokens for Google Cloud APIs2. By attaching a service account to the Jenkins VM instance, Terraform can use the Application Default Credentials (ADC) strategy to automatically find and use the service account credentials3.
Answer A is incorrect because the auth application-default command is used to obtain user credentials, not service account credentials. User credentials are not recommended for applications running on Google Cloud, as they are less secure and less scalable than service account credentials1.
Answer B is incorrect because it involves downloading and copying the secret key value of the service account, which is not a secure or reliable way of managing credentials. The secret key value should be kept private and not exposed to any other system or user2. Moreover, setting the GOOGLE environment variable on the Jenkins server is not a valid way of providing credentials to Terraform. Terraform expects the credentials to be either in a file pointed by the GOOGLE_APPLICATION_CREDENTIALS environment variable, or in a provider block with the credentials argument3.
Answer D is incorrect because it involves using the Terraform module for Secret Manager, which is a service that stores and manages sensitive data such as API keys, passwords, and certificates. While Secret Manager can be used to store and retrieve credentials, it is not necessary or sufficient for authorizing the Terraform Jenkins instance. The Terraform Jenkins instance still needs a service account with the appropriate IAM permissions to access Secret Manager and other Google Cloud resources.


NEW QUESTION # 40
Your uses Jenkins running on Google Cloud VM instances for CI/CD. You need to extend the functionality to use infrastructure as code automation by using Terraform. You must ensure that the Terraform Jenkins instance is authorized to create Google Cloud resources. You want to follow Google-recommended practices- What should you do?

Answer: B

Explanation:
The correct answer is C.
Confirming that the Jenkins VM instance has an attached service account with the appropriate Identity and Access Management (IAM) permissions is the best way to ensure that the Terraform Jenkins instance is authorized to create Google Cloud resources. This follows the Google-recommended practice of using service accounts to authenticate and authorize applications running on Google Cloud1. Service accounts are associated with private keys that can be used to generate access tokens for Google Cloud APIs2. By attaching a service account to the Jenkins VM instance, Terraform can use the Application Default Credentials (ADC) strategy to automatically find and use the service account credentials3.
Answer A is incorrect because the auth application-default command is used to obtain user credentials, not service account credentials. User credentials are not recommended for applications running on Google Cloud, as they are less secure and less scalable than service account credentials1.
Answer B is incorrect because it involves downloading and copying the secret key value of the service account, which is not a secure or reliable way of managing credentials. The secret key value should be kept private and not exposed to any other system or user2. Moreover, setting the GOOGLE environment variable on the Jenkins server is not a valid way of providing credentials to Terraform. Terraform expects the credentials to be either in a file pointed by the GOOGLE_APPLICATION_CREDENTIALS environment variable, or in a provider block with the credentials argument3.
Answer D is incorrect because it involves using the Terraform module for Secret Manager, which is a service that stores and manages sensitive data such as API keys, passwords, and certificates. While Secret Manager can be used to store and retrieve credentials, it is not necessary or sufficient for authorizing the Terraform Jenkins instance. The Terraform Jenkins instance still needs a service account with the appropriate IAM permissions to access Secret Manager and other Google Cloud resources.


NEW QUESTION # 41
Your company follows Site Reliability Engineering principles. You are writing a postmortem for an incident, triggered by a software change, that severely affected users. You want to prevent severe incidents from happening in the future. What should you do?

Answer: C

Explanation:
Explanation
The best way to prevent severe incidents from happening in the future is to ensure that test cases that catch errors of this type are run successfully before new software releases. This is aligned with the Site Reliability Engineering principle of testing for reliability.


NEW QUESTION # 42
Your company follows Site Reliability Engineering practices. You are the Incident Commander for a new. customer-impacting incident. You need to immediately assign two incident management roles to assist you in an effective incident response. What roles should you assign?
Choose 2 answers

Answer: A,B

Explanation:
https://sre.google/workbook/incident-response/
"The main roles in incident response are the Incident Commander (IC), Communications Lead (CL), and Operations or Ops Lead (OL)." The Operations Lead is responsible for managing the operational aspects of the incident, such as deploying fixes, rolling back changes, or restoring backups. The External Customer Communications Lead is not a standard role in incident response, but it could be delegated by the Communications Lead if needed.


NEW QUESTION # 43
Your team has recently deployed an NGINX-based application into Google Kubernetes Engine (GKE) and has exposed it to the public via an HTTP Google Cloud Load Balancer (GCLB) ingress. You want to scale the deployment of the application's frontend using an appropriate Service Level Indicator (SLI). What should you do?

Answer: B

Explanation:
https://cloud.google.com/kubernetes-engine/docs/tutorials/autoscaling-metrics The Google Cloud HTTP Load Balancer (GCLB) provides metrics on the number of requests and the response latency for each backend service. These metrics can be used as custom metrics for the horizontal pod autoscaler (HPA) to scale the deployment based on the load. This is the correct solution to use an appropriate SLI for scaling.


NEW QUESTION # 44
......

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