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

Section	Objectives
Optimize performance and continuous delivery	- Monitoring and observability 1. Performance tuning and feedback loops 2. Cloud Monitoring and Logging - System performance optimization 1. Scaling strategies and load handling
Implement security and compliance	- Compliance and governance 1. Audit logging and policy enforcement - Secure CI/CD pipelines 1. Secret and credential management 2. IAM and least privilege access
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
Develop and implement CI/CD pipelines	- Automate build, test, and deployment processes 1. Deployment automation strategies 2. Release management practices - Build and manage CI/CD pipelines using Google Cloud tools 1. Artifact repository management 2. Cloud Build pipeline design

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q35-Q40):

NEW QUESTION # 35
You support a service that recently had an outage. The outage was caused by a new release that exhausted the service memory resources. You rolled back the release successfully to mitigate the impact on users. You are now in charge of the post-mortem for the outage. You want to follow Site Reliability Engineering practices when developing the post-mortem. What should you do?

A. Focus on identifying the contributing causes of the incident rather than the individual responsible for the cause.
B. Use the Git history to find the related code commit. Prevent the engineer who made that commit from working on production services.
C. Plan individual meetings with all the engineers involved. Determine who approved and pushed the new release to production.
D. Focus on developing new features rather than avoiding the outages from recurring.

Answer: A

NEW QUESTION # 36
Your team is designing a new application for deployment into Google Kubernetes Engine (GKE). You need to set up monitoring to collect and aggregate various application-level metrics in a centralized location. You want to use Google Cloud Platform services while minimizing the amount of work required to set up monitoring. What should you do?

A. Emit all metrics in the form of application-specific log messages, pass these messages from the containers to the Stackdriver logging collector, and then observe metrics in Stackdriver.
B. Install the Cloud Pub/Sub client libraries, push various metrics from the application to various topics, and then observe the aggregated metrics in Stackdriver.
C. Publish various metrics from the application directly to the Slackdriver Monitoring API, and then observe these custom metrics in Stackdriver.
D. Install the OpenTelemetry client libraries in the application, configure Stackdriver as the export destination for the metrics, and then observe the application's metrics in Stackdriver.

Answer: C

NEW QUESTION # 37
You currently store the virtual machine (VM) utilization logs in Stackdriver. You need to provide an easy-to-share interactive VM utilization dashboard that is updated in real time and contains information aggregated on a quarterly basis. You want to use Google Cloud Platform solutions. What should you do?

A. 1. Export VM utilization logs from Stackdriver to BigOuery.
2. Create a dashboard in Data Studio.
3. Share the dashboard with your stakeholders.
B. 1. Export VM utilization logs from Stackdriver to a Cloud Storage bucket.
2. Enable the Cloud Storage API to pull the logs programmatically.
3. Build a custom data visualization application.
4. Display the pulled logs in a custom dashboard.
C. 1. Export VM utilization logs from Stackdriver to Cloud Pub/Sub.
2. From Cloud Pub/Sub, send the logs to a Security Information and Event Management (SIEM) system.
3. Build the dashboards in the SIEM system and share with your stakeholders.
D. 1. Export VM utilization logs (rom Stackdriver to BigQuery.
2. From BigQuery. export the logs to a CSV file.
3. Import the CSV file into Google Sheets.
4. Build a dashboard in Google Sheets and share it with your stakeholders.

Answer: A

NEW QUESTION # 38
You manage your company's primary revenue-generating application. You have an error budget policy in place that freezes production deployments when the application is close to breaching its SLO. A number of issues have recently occurred, and the application has exhausted its error budget. You need to deploy a new release to the application that includes a feature urgently required by your largest customer. You have been told that the release has passed all unit tests. What should you do?

A. Re-run the unit tests, and start the deployment of the feature if the tests pass.
B. Start the deployment of the feature immediately.
C. Deploy the feature to a subset of users, and gradually roll out to all users if there are no errors reported.
D. Delay the deployment of the feature until the error budget is replenished.

Answer: C

NEW QUESTION # 39
Your company wants to implement a CD pipeline in Cloud Deploy for a web service deployed to GKE. The web service currently does not have any automated testing. The Quality Assurance team must manually verify any new releases of the web service before any production traffic is processed. You need to design the CD pipeline. What should you do?

A. Create a single pipeline stage, and use a standard deployment strategy.
B. Create two pipeline stages, and use a canary deployment strategy.
C. Create two pipeline stages, and use a standard deployment strategy.
D. Create a single pipeline stage, and use a canary deployment strategy.

Answer: C

Explanation:
To allow manual QA approval, you need separate pipeline stages (e.g., staging # production) and manual promotion between them.
"Cloud Deploy supports multi-stage pipelines where you can manually approve releases before promotion."
- Cloud Deploy Promotion
"Use a standard strategy when there are no automated tests or SLOs to support rollback decisions."
- Deployment Strategies
Canary is best used when automated health checks and metrics exist, which is not the case here.

NEW QUESTION # 40
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