PCDOE practice questions 181–190

1. Question 181 · 210 in bank

   Your organization wants to collect system logs that will be used to generate dashboards in Cloud Operations for their Google Cloud project. You need to configure all current and future Compute Engine instances to collect the system logs, and you must ensure that the Ops Agent remains up to date. What should you do?

   • AUse the gcloud CLI to install the Ops Agent on each VM listed in the Cloud Asset Inventory,
   • BSelect all VMs with an Agent status of Not detected on the Cloud Operations VMs dashboard. Then select Install agents.
   • CUse the gcloud CLI to create an Agent Policy.
   • DInstall the Ops Agent on the Compute Engine image by using a startup script

   Show answer

   Answer: C

   Explanation

   Option A suggests using the gcloud CLI to install the Ops Agent on each VM manually, which can be time-consuming and error-prone, especially when dealing with a large number of instances. option B is the most efficient and appropriate choice for deploying and ensuring the continued use of the Ops Agent on both existing and future Compute Engine instances in your Google Cloud project.

   Source: Adapted from community discussion — ManishKS

   References

   • Google Cloud documentation

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2. Question 182 · 210 in bank

   Your company has a Google Cloud resource hierarchy with folders for production, test, and development. Your cyber security team needs to review your company's Google Cloud security posture to accelerate security issue identification and resolution. You need to centralize the logs generated by Google Cloud services from all projects only inside your production folder to allow for alerting and near-real time analysis. What should you do?

   • AEnable the Workflows API and route all the logs to Cloud Logging.
   • BCreate a central Cloud Monitoring workspace and attach all related projects.
   • CCreate an aggregated log sink associated with the production folder that uses a Pub/Sub topic as the destination.
   • DCreate an aggregated log sink associated with the production folder that uses a Cloud Logging bucket as the destination.

   Show answer

   Answer: C

   Explanation

   It clearly mentions here that "Sinks to Cloud Storage are processed hourly while other destination types are processed in real time." https://cloud.google.com/logging/docs/export/configure_export_v2#:~:text=New%20log%20sinks%20to%20Cloud%20Storage%20buckets%20might%20take%20several%20hours%20to%20start%20routing%20logs.%20Sinks%20to%20Cloud%20Storage%20are%20processed%20hourly%20while%20other%20destination%20types%20are%20processed%20in%20real%20time. D is eliminated

   Source: Adapted from community discussion — alpha_canary

   References

   • Google Cloud documentation

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3. Question 183 · 210 in bank

   You are configuring the frontend tier of an application deployed in Google Cloud. The frontend tier is hosted in nginx and deployed using a managed instance group with an Envoy-based external HTTP(S) load balancer in front. The application is deployed entirely within the europe-west2 region, and only serves users based in the United Kingdom. You need to choose the most cost-effective network tier and load balancing configuration. What should you use?

   • APremium Tier with a global load balancer
   • BPremium Tier with a regional load balancer
   • CStandard Tier with a global load balancer
   • DStandard Tier with a regional load balancer

   Show answer

   Answer: D

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4. Question 184 · 210 in bank

   You recently deployed your application in Google Kubernetes Engine (GKE) and now need to release a new version of the application. You need the ability to instantly roll back to the previous version of the application in case there are issues with the new version. Which deployment model should you use?

   • APerform a rolling deployment, and test your new application after the deployment is complete.
   • BPerform A/B testing, and test your application periodically after the deployment is complete.
   • CPerform a canary deployment, and test your new application periodically after the new version is deployed.
   • DPerform a blue/green deployment, and test your new application after the deployment is complete.

   Show answer

   Answer: D

   References

   • Google Cloud documentation

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5. Question 185 · 210 in bank

   Select 2

   You deploy a new release of an internal application during a weekend maintenance window when there is minimal user tragic. After the window ends, you learn that one of the new features isn't working as expected in the production environment. After an extended outage, you roll back the new release and deploy a fix. You want to modify your release process to reduce the mean time to recovery so you can avoid extended outages in the future. What should you do? (Choose two.)

   • ABefore merging new code, require 2 different peers to review the code changes.
   • BAdopt the blue/green deployment strategy when releasing new code via a CD server.
   • CIntegrate a code linting tool to validate coding standards before any code is accepted into the repository.
   • DRequire developers to run automated integration tests on their local development environments before release.
   • EConfigure a CI server. Add a suite of unit tests to your code and have your CI server run them on commit and verify any changes.

   Show answer

   Answer: BE

   Explanation

   Ans: B & E A: No, More peers to review dont automate anything B: Ok CD C: No, Linting is for code format D: No, Integration test are needed but its better automatically E: Ok CI CI/CD its OK

   Source: Adapted from community discussion — francisco_guerra

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6. Question 186 · 210 in bank

   You are building and deploying a microservice on Cloud Run for your organization. Your service is used by many applications internally. You are deploying a new release, and you need to test the new version extensively in the staging and production environments. You must minimize user and developer impact. What should you do?

   • ADeploy the new version of the service to the staging environment. Split the traffic, and allow 1% of traffic through to the latest version. Test the latest version. If the test passes, gradually roll out the latest version to the staging and production environments.
   • BDeploy the new version of the service to the staging environment. Split the traffic, and allow 50% of traffic through to the latest version. Test the latest version. If the test passes, send all traffic to the latest version. Repeat for the production environment.
   • CDeploy the new version of the service to the staging environment with a new-release tag without serving traffic. Test the new-release version. If the test passes, gradually roll out this tagged version. Repeat for the production environment.
   • DDeploy a new environment with the green tag to use as the staging environment. Deploy the new version of the service to the green environment and test the new version. If the tests pass, send all traffic to the green environment and delete the existing staging environment. Repeat for the production environment.

   Show answer

   Answer: C

   Explanation

   This approach allows you to deploy and test the new version without impacting users, as no traffic is directed to the new version initially. After thorough testing in the staging environment, you can confidently roll out the new version to a small percentage of users in the production environment, gradually increasing it while monitoring performance and stability. This method offers a controlled and safe way to introduce changes.

   Source: Adapted from community discussion — filipemotta

   References

   • Google Cloud documentation

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7. Question 187 · 210 in bank

   You work for a global organization and run a service with an availability target of 99% with limited engineering resources. For the current calendar month, you noticed that the service has 99.5% availability. You must ensure that your service meets the defined availability goals and can react to business changes, including the upcoming launch of new features. You also need to reduce technical debt while minimizing operational costs. You want to follow Google-recommended practices. What should you do?

   • AAdd N+1 redundancy to your service by adding additional compute resources to the service.
   • BIdentify, measure, and eliminate toil by automating repetitive tasks.
   • CDefine an error budget for your service level availability and minimize the remaining error budget.
   • DAllocate available engineers to the feature backlog while you ensure that the service remains within the availability target.

   Show answer

   Answer: B

   Explanation

   Option B suggests focusing on identifying, measuring, and eliminating toil through the automation of repetitive tasks. In the context of running a service with a 99% availability target and limited engineering resources, this approach aligns with Google's Site Reliability Engineering (SRE) principles. By automating manual and repetitive operational work, engineering teams can enhance efficiency, reduce the risk of human error, and free up valuable resources. The emphasis on eliminating toil not only contributes to meeting availability targets by minimizing the potential for errors but also allows engineering teams to allocate more time to strategic tasks, reducing technical debt, and facilitating a more agile response to business changes, such as the launch of new features. Overall, Option B addresses the need for operational efficiency and resource optimization to ensure the reliability of the service.

   Source: Adapted from community discussion — xhilmi

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8. Question 188 · 210 in bank

   You are developing the deployment and testing strategies for your CI/CD pipeline in Google Cloud. You must be able to: • Reduce the complexity of release deployments and minimize the duration of deployment rollbacks. • Test real production traffic with a gradual increase in the number of affected users. You want to select a deployment and testing strategy that meets your requirements. What should you do?

   • ARecreate deployment and canary testing
   • BBlue/green deployment and canary testing
   • CRolling update deployment and A/B testing
   • DRolling update deployment and shadow testing

   Show answer

   Answer: B

   References

   • Google Cloud documentation

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9. Question 189 · 210 in bank

   Select 2

   You are creating a CI/CD pipeline to perform Terraform deployments of Google Cloud resources. Your CI/CD tooling is running in Google Kubernetes Engine (GKE) and uses an ephemeral Pod for each pipeline run. You must ensure that the pipelines that run in the Pods have the appropriate Identity and Access Management (IAM) permissions to perform the Terraform deployments. You want to follow Google-recommended practices for identity management. What should you do? (Choose two.)

   • ACreate a new Kubernetes service account, and assign the service account to the Pods. Use Workload Identity to authenticate as the Google service account.
   • BCreate a new JSON service account key for the Google service account, store the key as a Kubernetes secret, inject the key into the Pods, and set the GOOGLE_APPLICATION_CREDENTIALS environment variable.
   • CCreate a new Google service account, and assign the appropriate IAM permissions.
   • DCreate a new JSON service account key for the Google service account, store the key in the secret management store for the CI/CD tool, and configure Terraform to use this key for authentication.
   • EAssign the appropriate IAM permissions to the Google service account associated with the Compute Engine VM instances that run the Pods.

   Show answer

   Answer: AC

   Explanation

   Option A: Suggests creating a new Kubernetes service account and assigning it to the Pods. This service account is then associated with a Google service account using Workload Identity. This setup enables seamless authentication of Pods as the specified Google service account without relying on manual management of service account keys. Option C: Complements the approach by emphasizing the creation of a new Google service account and assigning the necessary IAM permissions. While the Kubernetes service account establishes the identity within the GKE cluster, the Google service account is associated with the underlying Google Cloud resources, ensuring that the appropriate permissions are granted for Terraform deployments.

   Source: Adapted from community discussion — xhilmi

   References

   • Google Cloud documentation

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10. Question 190 · 210 in bank

    You are the on-call Site Reliability Engineer for a microservice that is deployed to a Google Kubernetes Engine (GKE) Autopilot cluster. Your company runs an online store that publishes order messages to Pub/Sub, and a microservice receives these messages and updates stock information in the warehousing system. A sales event caused an increase in orders, and the stock information is not being updated quickly enough. This is causing a large number of orders to be accepted for products that are out of stock. You check the metrics for the microservice and compare them to typical levels:

    

    You need to ensure that the warehouse system accurately reflects product inventory at the time orders are placed and minimize the impact on customers. What should you do?

    • ADecrease the acknowledgment deadline on the subscription.
    • BAdd a virtual queue to the online store that allows typical traffic levels.
    • CIncrease the number of Pod replicas.
    • DIncrease the Pod CPU and memory limits.

    Show answer

    Answer: C

    Explanation

    The increase in the number of undelivered messages indicates that the microservice is not fully processing the messages. It is believed that the number of messages that can be processed can be increased by increasing the number of pods.

    Source: Adapted from community discussion — YushiSato

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PCDOE practice, question 181. 210 questions available.