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

Section	Objectives
Implement site reliability engineering (SRE) practices	- Define and manage SLI, SLO, and SLA 1. Error budgets and monitoring strategies - Incident management and postmortems 1. Alerting and on-call practices
Optimize performance and continuous delivery	- System performance optimization 1. Scaling strategies and load handling - Monitoring and observability 1. Performance tuning and feedback loops 2. Cloud Monitoring and Logging
Develop and implement CI/CD pipelines	- Build and manage CI/CD pipelines using Google Cloud tools 1. Artifact repository management 2. Cloud Build pipeline design - Automate build, test, and deployment processes 1. Deployment automation strategies 2. Release management practices
Implement security and compliance	- Compliance and governance 1. Audit logging and policy enforcement - Secure CI/CD pipelines 1. IAM and least privilege access 2. Secret and credential management

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q189-Q194):

NEW QUESTION # 189
You recently noticed that one Of your services has exceeded the error budget for the current rolling window period. Your company's product team is about to launch a new feature. You want to follow Site Reliability Engineering (SRE) practices.
What should you do?

A. Notify the team about the lack of error budget and ensure that all their tests are successful so the launch will not further risk the error budget.
B. Look through other metrics related to the product and find SLOs with remaining error budget.
Reallocate the error budgets and allow the feature launch.
C. Notify the team that their error budget is used up. Negotiate with the team for a launch freeze or tolerate a slightly worse user experience.
D. Escalate the situation and request additional error budget.

Answer: C

Explanation:
The correct answer is A. Notify the team that their error budget is used up. Negotiate with the team for a launch freeze or tolerate a slightly worse user experience.
According to the Site Reliability Engineering (SRE) practices, an error budget is the amount of unreliability that a service can tolerate without harming user satisfaction1.An error budget is derived from the service-level objectives (SLOs), which are the measurable goals for the service quality2. When a service exceeds its error budget, it means that it has violated its SLOs and may have negatively impacted the users.In this case, the SRE team should notify the product team that their error budget is used up and negotiate with them for a launch freeze or a lower SLO3. A launch freeze means that no new features are deployed until the service reliability is restored. A lower SLO means that the product team accepts a slightly worse user experience in exchange for launching new features. Both options require a trade-off between reliability and innovation, and should be agreed upon by both teams.
The other options are incorrect because they do not follow the SRE practices.Option B is incorrect because it violates the principle of error budget autonomy, which means that each service should have its own error budget and SLOs, and should not borrow or reallocate them from other services4. Option C is incorrect because it does not address the root cause of the error budget overspend, and may create unrealistic expectations for the service reliability. Option D is incorrect because it does not prevent the possibility of introducing new errors or bugs with the feature launch, which may further degrade the service quality and user satisfaction.
Reference:
Error Budgets, Error Budgets.Service Level Objectives, Service Level Objectives.Error Budget Policies, Error Budget Policies.Error Budget Autonomy, Error Budget Autonomy.

NEW QUESTION # 190
Your team of Infrastructure DevOps Engineers is growing, and you are starting to use Terraform to manage infrastructure. You need a way to implement code versioning and to share code with other team members. What should you do?

A. Store the Terraform code in a version-control system. Establish procedures for pushing new versions and merging with the master.
B. Store the Terraform code in a Cloud Storage bucket using object versioning. Give access to the bucket to every team member so they can download the files.
C. Store the Terraform code in a network shared folder with child folders for each version release. Ensure that everyone works on different files.
D. Store the Terraform code in a shared Google Drive folder so it syncs automatically to every team member's computer. Organize files with a naming convention that identifies each new version.

Answer: A

Explanation:
https://www.terraform.io/docs/cloud/guides/recommended-practices/part3.3.html

NEW QUESTION # 191
Your team has an application built by using a Dockerfile. The build is executed from Cloud Build, and the resulting artifacts are stored in Artifact Registry. Your team is reporting that builds are slow. You need to increase build speed, while following Google-recommended practices. What should you do?

A. Cache the container layers of the build process to Cloud Storage. Add the most frequently modified files to the later stages of the build process.
B. Use the --cache-from parameter, and point to Artifact Registry. Add the most frequently modified files to the earlier stages of the build process.
C. Cache the container layers of the build process to Cloud Storage. Add the most frequently modified files to the earlier stages of the build process.
D. Use the --cache-from parameter, and point to Artifact Registry. Add the most frequently modified files to the later stages of the build process.

Answer: D

Explanation:
To speed up Docker builds, optimize layer caching. Google Cloud recommends using --cache-from with Artifact Registry, and placing frequently changed files late in the Dockerfile so earlier layers can be reused.
"Put instructions that are less likely to change (like installing packages) early in the Dockerfile, and more frequently changing lines (like copying app code) near the end."
- Dockerfile Best Practices
"Use the --cache-from argument to pull layers from previously built images in Artifact Registry."
- Cloud Build Docker Caching
This dramatically reduces build time by avoiding redundant rebuilds of static layers.

NEW QUESTION # 192
You are performing a semiannual capacity planning exercise for your flagship service. You expect a service user growth rate of 10% month-over-month over the next six months. Your service is fully containerized and runs on Google Cloud Platform (GCP). using a Google Kubernetes Engine (GKE) Standard regional cluster on three zones with cluster autoscaler enabled. You currently consume about 30% of your total deployed CPU capacity, and you require resilience against the failure of a zone. You want to ensure that your users experience minimal negative impact as a result of this growth or as a result of zone failure, while avoiding unnecessary costs. How should you prepare to handle the predicted growth?

A. Because you are at only 30% utilization, you have significant headroom and you won't need to add any additional capacity for this rate of growth.
B. Proactively add 60% more node capacity to account for six months of 10% growth rate, and then perform a load test to make sure you have enough capacity.
C. Verity the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verity your expected resource needs.
D. Because you are deployed on GKE and are using a cluster autoscaler. your GKE cluster will scale automatically, regardless of growth rate.

Answer: C

NEW QUESTION # 193
Your application artifacts are being built and deployed via a CI/CD pipeline. You want the CI/CD pipeline to securely access application secrets. You also want to more easily rotate secrets in case of a security breach.
What should you do?

A. Encrypt the secrets and store them in the source code repository. Store a decryption key in a separate repository and grant your pipeline access to it.
B. Store secrets in a separate configuration file on Git. Provide select developers with access to the configuration file.
C. Store secrets in Cloud Storage encrypted with a key from Cloud KMS. Provide the CI/CD pipeline with access to Cloud KMS via IAM.
D. Prompt developers for secrets at build time. Instruct developers to not store secrets at rest.

Answer: C

NEW QUESTION # 194
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