Google PROFESSIONAL-CLOUD-DEVELOPER Online Practice Questions and Exam Preparation

Google PROFESSIONAL-CLOUD-DEVELOPER Online Questions & Answers

• Question 321:

  Your company uses Cloud Logging to manage large volumes of log data. You need to build a real-time log analysis architecture that pushes logs to a third-party application for processing.

  What should you do?

  A. Create a Cloud Logging log export to Pub/Sub.
  B. Create a Cloud Logging log export to BigQuery.
  C. Create a Cloud Logging log export to Cloud Storage.
  D. Create a Cloud Function to read Cloud Logging log entries and send them to the third-party application.
  A. Create a Cloud Logging log export to Pub/Sub.

• Question 322:

  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?

  A. Define your service endpoint information as metadata that is retrieved at runtime and used to connect to the desired service.
  B. Define your service endpoint information as label data that is retrieved at runtime and used to connect to the desired service.
  C. Define your service endpoint information to be retrieved from an environment variable at runtime and used to connect to the desired service.
  D. Define 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.
  A. Define your service endpoint information as metadata that is retrieved at runtime and used to connect to the desired service.

• Question 323:

  You are deploying your applications on Compute Engine. One of your Compute Engine instances failed to launch.

  What should you do? (Choose two.)

  A. Determine whether your file system is corrupted.
  B. Access Compute Engine as a different SSH user.
  C. Troubleshoot firewall rules or routes on an instance.
  D. Check whether your instance boot disk is completely full.
  E. Check whether network traffic to or from your instance is being dropped.
  A. Determine whether your file system is corrupted.
  D. Check whether your instance boot disk is completely full.

• Question 324:

  Which service should HipLocal use for their public APIs?

  A. Cloud Armor
  B. Cloud Functions
  C. Cloud Endpoints
  D. Shielded Virtual Machines
  C. Cloud Endpoints

• Question 325:

  You deployed a new application to Google Kubernetes Engine and are experiencing some performance degradation. Your logs are being written to Cloud Logging, and you are using a Prometheus sidecar model for capturing metrics. You need to correlate the metrics and data from the logs to troubleshoot the performance issue and send real-time alerts while minimizing costs.

  What should you do?

  A. Create custom metrics from the Cloud Logging logs, and use Prometheus to import the results using the Cloud Monitoring REST API.
  B. Export the Cloud Logging logs and the Prometheus metrics to Cloud Bigtable. Run a query to join the results, and analyze in Google Data Studio.
  C. Export the Cloud Logging logs and stream the Prometheus metrics to BigQuery. Run a recurring query to join the results, and send notifications using Cloud Tasks.
  D. Export the Prometheus metrics and use Cloud Monitoring to view them as external metrics. Configure Cloud Monitoring to create log-based metrics from the logs, and correlate them with the Prometheus data.
  D. Export the Prometheus metrics and use Cloud Monitoring to view them as external metrics. Configure Cloud Monitoring to create log-based metrics from the logs, and correlate them with the Prometheus data.

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  Explanation

  https://cloud.google.com/blog/products/operations/troubleshoot-gke-faster-with-monitoring-data-in-your-logs

• Question 326:

  You are a developer at a company that operates an ecommerce website. The website stores the customer order data in a Cloud SQL for PostgreSQL database. Data scientists on the marketing team access this data to run their reports. Every time they run these reports, the website's performance is negatively affected. You want to provide access to up-to-date customer order datasets without affecting your website.

  What should you do?

  A. Configure Cloud Scheduler to run an hourly Cloud Run function that exports the data from the Cloud SQL database into CSV format and sends the data to a Cloud Storage bucket.
  B. Set up a Bigtable table for the data science team. Configure the application to perform dual writes to both Cloud SQL and Bigtable simultaneously.
  C. Set up a BigQuery dataset for the data science team. Configure Datastream to replicate the relevant Cloud SQL tables in BigQuery.
  D. Create a clone of the PostgreSQL database instance for the data science team. Schedule a job to create a new clone every 15 minutes.
  C. Set up a BigQuery dataset for the data science team. Configure Datastream to replicate the relevant Cloud SQL tables in BigQuery.

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  Explanation

  https://careerfoundry.com/en/blog/data-analytics/where-to-find-free-datasets/

• Question 327:

  You are developing a secure document sharing platform. The platform allows users to share documents with other users who may be external to their organization. Access to these documents should be revoked after a configurable time period. The documents are stored in Cloud Storage.

  How should you configure Cloud Storage to support this functionality?

  A. Create signed policy documents on the Cloud Storage bucket.
  B. Apply access control list (ACL) permissions to the Cloud Storage bucket.
  C. Generate a signed URL for each document the user wants to share.
  D. Grant the Storage Object Viewer IAM role to all authenticated users.
  C. Generate a signed URL for each document the user wants to share.

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  Explanation

  https://cloud.google.com/storage/docs/access-control/

• Question 328:

  Your company recently modernized their monolith ecommerce site to a microservices application in GKE. Your team uses Google Cloud's operations suite for monitoring and logging. You want to improve the logging indexing and searchabilty in Cloud Logging across your microservices with the least amount of effort.

  What should you do?

  A. Ask the SRE team to enable Managed Service for Prometheus on your GKE cluster.
  B. Reconfigure your applications to write logs to an emptyDir volume. Configure a sidecar agent to read the logs and send them to the Cloud Logging API.
  C. Update your microservices code to emit logs in JSON format.
  D. Instrument your microservices code with OpenTelemetry libraries.
  C. Update your microservices code to emit logs in JSON format.

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  Explanation

  JSON-formatted logs are structured logs that make indexing and searching easier in Cloud Logging. Cloud Logging can automatically parse JSON logs, which allows for better indexing, querying, and filtering capabilities. By emitting logs in JSON format, you improve the searchability and organization of logs across your microservices with minimal code changes, as JSON logs provide structure to log entries without requiring additional services or configurations.

  Options like enabling Managed Service for Prometheus or instrumenting with OpenTelemetry are useful for monitoring and metrics, but they don't specifically improve log indexing and searchability in Cloud Logging.

• Question 329:

  You are developing an HTTP API hosted on a Compute Engine virtual machine instance that needs to be invoked by multiple clients within the same Virtual Private Cloud (VPC). You want clients to be able to get the IP address of the service.

  What should you do?

  A. Reserve a static external IP address and assign it to an HTTP(S) load balancing service's forwarding rule. Clients should use this IP address to connect to the service.
  B. Reserve a static external IP address and assign it to an HTTP(S) load balancing service's forwarding rule. Then, define an A record in Cloud DNS. Clients should use the name of the A record to connect to the service.
  C. Ensure that clients use Compute Engine internal DNS by connecting to the instance name with the url. https://[INSTANCE_NAME].[ZONE].c.[PROJECT_ID].internal/
  D. Ensure that clients use Compute Engine internal DNS by connecting to the instance name with the url https://[API_NAME]/[API_VERSION]/.
  C. Ensure that clients use Compute Engine internal DNS by connecting to the instance name with the url. https://[INSTANCE_NAME].[ZONE].c.[PROJECT_ID].internal/

• Question 330:

  You are developing a new application that has the following design requirements:

  1. Creation and changes to the application infrastructure are versioned and auditable.

  2. The application and deployment infrastructure uses Google-managed services as much as possible.

  3. The application runs on a serverless compute platform.

  How should you design the application's architecture?

  A. 1. Store the application and infrastructure source code in a Git repository. 2. Use Cloud Build to deploy the application infrastructure with Terraform. 3. Deploy the application to a Cloud Function as a pipeline step.
  B. 1. Deploy Jenkins from the Google Cloud Marketplace, and define a continuous integration pipeline in Jenkins. 2. Configure a pipeline step to pull the application source code from a Git repository. 3. Deploy the application source code to App Engine as a pipeline step.
  C. 1. Create a continuous integration pipeline on Cloud Build, and configure the pipeline to deploy the application infrastructure using Deployment Manager templates. 2. Configure a pipeline step to create a container with the latest application source code. 3. Deploy the container to a Compute Engine instance as a pipeline step.
  D. 1. Deploy the application infrastructure using gcloud commands. 2. Use Cloud Build to define a continuous integration pipeline for changes to the application source code. 3. Configure a pipeline step to pull the application source code from a Git repository, and create a containerized application. 4. Deploy the new container on Cloud Run as a pipeline step.
  A. 1. Store the application and infrastructure source code in a Git repository. 2. Use Cloud Build to deploy the application infrastructure with Terraform. 3. Deploy the application to a Cloud Function as a pipeline step.