PCD practice questions 51–60

1. Question 51 · 357 in bank

   You are developing a single-player mobile game backend that has unpredictable traffic patterns as users interact with the game throughout the day and night. You want to optimize costs by ensuring that you have enough resources to handle requests, but minimize over-provisioning. You also want the system to handle traffic spikes efficiently. Which compute platform should you use?

   • ACloud Run
   • BCompute Engine with managed instance groups
   • CCompute Engine with unmanaged instance groups
   • DGoogle Kubernetes Engine using cluster autoscaling

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   Answer: A

   Explanation

   Compute Engine answers are eliminated because they can't scale quickly enough. GKE Answer is ruled out because you can end up overprovisioned, also cannot scale out to add more nodes quickly enough.

   Source: Adapted from community discussion — micoams

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2. Question 52 · 357 in bank

   The development teams in your company want to manage resources from their local environments. You have been asked to enable developer access to each team’s Google Cloud projects. You want to maximize efficiency while following Google-recommended best practices. What should you do?

   • AAdd the users to their projects, assign the relevant roles to the users, and then provide the users with each relevant Project ID.
   • BAdd the users to their projects, assign the relevant roles to the users, and then provide the users with each relevant Project Number.
   • CCreate groups, add the users to their groups, assign the relevant roles to the groups, and then provide the users with each relevant Project ID.
   • DCreate groups, add the users to their groups, assign the relevant roles to the groups, and then provide the users with each relevant Project Number.

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   Answer: C

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3. Question 53 · 357 in bank

   Your company’s product team has a new requirement based on customer demand to autoscale your stateless and distributed service running in a Google Kubernetes Engine (GKE) duster. You want to find a solution that minimizes changes because this feature will go live in two weeks. What should you do?

   • ADeploy a Vertical Pod Autoscaler, and scale based on the CPU load.
   • BDeploy a Vertical Pod Autoscaler, and scale based on a custom metric.
   • CDeploy a Horizontal Pod Autoscaler, and scale based on the CPU toad.
   • DDeploy a Horizontal Pod Autoscaler, and scale based on a custom metric.

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   Answer: C

   Explanation

   C is the answer. https://cloud.google.com/kubernetes-engine/docs/concepts/horizontalpodautoscaler The Horizontal Pod Autoscaler changes the shape of your Kubernetes workload by automatically increasing or decreasing the number of Pods in response to the workload's CPU or memory consumption, or in response to custom metrics reported from within Kubernetes or external metrics from sources outside of your cluster.

   Source: Adapted from community discussion — zellck

   References

   • Google Cloud documentation

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4. Question 54 · 357 in bank

   Your application is composed of a set of loosely coupled services orchestrated by code executed on Compute Engine. You want your application to easily bring up new Compute Engine instances that find and use a specific version of a service. How should this be configured?

   • ADefine your service endpoint information as metadata that is retrieved at runtime and used to connect to the desired service.
   • BDefine your service endpoint information as label data that is retrieved at runtime and used to connect to the desired service.
   • CDefine your service endpoint information to be retrieved from an environment variable at runtime and used to connect to the desired service.
   • DDefine your service to use a fixed hostname and port to connect to the desired service. Replace the service at the endpoint with your new version.

   Show answer

   Answer: A

   Explanation

   Ansuwer is A: Labels are used to categorize and organize resources in Google Cloud Platform, such as Compute Engine instances. While they can also be used to store endpoint information, they may not be as flexible as metadata when it comes to dynamically retrieving information at runtime. Additionally, labels are associated with individual resources, so updating the label data would require modifying the specific resource, rather than a centralized metadata store. In some cases, using labels may be more appropriate, such as when you want to categorize and organize your resources, but for managing service endpoints in a loosely coupled architecture, metadata is generally a more flexible and scalable solution.

   Source: Adapted from community discussion — mrvergara

   References

   • Google Cloud documentation
   • Google Cloud documentation
   • Google Cloud documentation

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5. Question 55 · 357 in bank

   Select 2

   You are developing a microservice-based application that will run on Google Kubernetes Engine (GKE). Some of the services need to access different Google Cloud APIs. How should you set up authentication of these services in the cluster following Google-recommended best practices? (Choose two.)

   • AUse the service account attached to the GKE node.
   • BEnable Workload Identity in the cluster via the gcloud command-line tool.
   • CAccess the Google service account keys from a secret management service.
   • DStore the Google service account keys in a central secret management service.
   • EUse gcloud to bind the Kubernetes service account and the Google service account using roles/iam.workloadIdentity.

   Show answer

   Answer: BE

   Explanation

   A is incorrect. While it could work, all the services are using the same service account, there is no separation of permissions, and no detailed logging. B and E together connect GKE and Google service accounts, so GKE can authenticate a service with a Google service account. C is incorrect. While this is feasible, it’s not the recommended practice for workload identity because of the mandatory key rotation of the service accounts. D is incorrect. While this is feasible, it’s not the recommended practice for workload identity because of the mandatory key rotation of the service accounts. E and B together connect GKE and Google service accounts, so GKE can authenticate a service with a Google service account.

   Source: Adapted from community discussion — telp

   References

   • Google Cloud documentation
   • Google Cloud documentation
   • Google Cloud documentation

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6. Question 56 · 357 in bank

   Your development team has been tasked with maintaining a .NET legacy application. The application incurs occasional changes and was recently updated. Your goal is to ensure that the application provides consistent results while moving through the CI/CD pipeline from environment to environment. You want to minimize the cost of deployment while making sure that external factors and dependencies between hosting environments are not problematic. Containers are not yet approved in your organization. What should you do?

   • ARewrite the application using .NET Core, and deploy to Cloud Run. Use revisions to separate the environments.
   • BUse Cloud Build to deploy the application as a new Compute Engine image for each build. Use this image in each environment.
   • CDeploy the application using MS Web Deploy, and make sure to always use the latest, patched MS Windows Server base image in Compute Engine.
   • DUse Cloud Build to package the application, and deploy to a Google Kubernetes Engine cluster. Use namespaces to separate the environments.

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   Answer: B

   References

   • Google Cloud documentation

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7. Question 57 · 357 in bank

   You are using Cloud Build to build and test application source code stored in Cloud Source Repositories. The build process requires a build tool not available in the Cloud Build environment. What should you do?

   • ADownload the binary from the internet during the build process.
   • BBuild a custom cloud builder image and reference the image in your build steps.
   • CInclude the binary in your Cloud Source Repositories repository and reference it in your build scripts.
   • DAsk to have the binary added to the Cloud Build environment by filing a feature request against the Cloud Build public Issue Tracker.

   Show answer

   Answer: B

   References

   • Google Cloud documentation

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8. Question 58 · 357 in bank

   The new version of your containerized application has been tested and is ready to deploy to production on Google Kubernetes Engine. You were not able to fully load-test the new version in pre-production environments, and you need to make sure that it does not have performance problems once deployed. Your deployment must be automated. What should you do?

   • AUse Cloud Load Balancing to slowly ramp up traffic between versions. Use Cloud Monitoring to look for performance issues.
   • BDeploy the application via a continuous delivery pipeline using canary deployments. Use Cloud Monitoring to look for performance issues. and ramp up traffic as the metrics support it.
   • CDeploy the application via a continuous delivery pipeline using blue/green deployments. Use Cloud Monitoring to look for performance issues, and launch fully when the metrics support it.
   • DDeploy the application using kubectl and set the spec.updateStrategv.type to RollingUpdate. Use Cloud Monitoring to look for performance issues, and run the kubectl rollback command if there are any issues.

   Show answer

   Answer: B

   Explanation

   B. Deploy the application via a continuous delivery pipeline using canary deployments. Use Cloud Monitoring to look for performance issues, and ramp up traffic as the metrics support it. Canary deployment strategy can be used to mitigate risk in the production deployment process. In this strategy, a small subset of traffic is routed to the new version of the application, while the rest of the traffic is sent to the current version. This allows for real-time monitoring of the new version's performance before fully rolling it out to all users. If there are any issues or performance problems, the traffic can be immediately routed back to the previous version. Cloud Monitoring can be used to monitor performance metrics and make informed decisions about when to ramp up traffic to the new version

   Source: Adapted from community discussion — Teraflow

   References

   • Google Cloud documentation
   • Kubernetes documentation
   • Google Cloud documentation

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9. Question 59 · 357 in bank

   Users are complaining that your Cloud Run-hosted website responds too slowly during traffic spikes. You want to provide a better user experience during traffic peaks. What should you do?

   • ARead application configuration and static data from the database on application startup.
   • BPackage application configuration and static data into the application image during build time.
   • CPerform as much work as possible in the background after the response has been returned to the user.
   • DEnsure that timeout exceptions and errors cause the Cloud Run instance to exit quickly so a replacement instance can be started.

   Show answer

   Answer: B

   Explanation

   B is the answer. https://cloud.google.com/blog/topics/developers-practitioners/3-ways-optimize-cloud-run-response-times Instead of computing things upon startup, compute them lazily. The initialization of global variables always occurs during startup, which increases cold start time. Use lazy initialization for infrequently used objects to defer the time cost and decrease cold start times.

   Source: Adapted from community discussion — zellck

   References

   • Google Cloud documentation

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10. Question 60 · 357 in bank

    You are a developer working on an internal application for payroll processing. You are building a component of the application that allows an employee to submit a timesheet, which then initiates several steps: • An email is sent to the employee and manager, notifying them that the timesheet was submitted. • A timesheet is sent to payroll processing for the vendor's API. • A timesheet is sent to the data warehouse for headcount planning. These steps are not dependent on each other and can be completed in any order. New steps are being considered and will be implemented by different development teams. Each development team will implement the error handling specific to their step. What should you do?

    • ADeploy a Cloud Function for each step that calls the corresponding downstream system to complete the required action.
    • BCreate a Pub/Sub topic for each step. Create a subscription for each downstream development team to subscribe to their step's topic.
    • CCreate a Pub/Sub topic for timesheet submissions. Create a subscription for each downstream development team to subscribe to the topic.
    • DCreate a timesheet microservice deployed to Google Kubernetes Engine. The microservice calls each downstream step and waits for a successful response before calling the next step.

    Show answer

    Answer: C

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PCD practice, question 51. 357 questions available.