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For this question, refer to the Dress4Win case study.

Dress4Win would like to become familiar with deploying applications to the cloud by successfully deploying some applications quickly, as is. They have asked for your recommendation. What should you advise?

A.

Identify self-contained applications with external dependencies as a first move to the cloud.

B.

Identify enterprise applications with internal dependencies and recommend these as a first move to the cloud.

C.

Suggest moving their in-house databases to the cloud and continue serving requests to on-premise applications.

D.

Recommend moving their message queuing servers to the cloud and continue handling requests to on-premise applications.

Your development teams release new versions of games running on Google Kubernetes Engine (GKE) daily.

You want to create service level indicators (SLIs) to evaluate the quality of the new versions from the user’s

perspective. What should you do?

A.

Create CPU Utilization and Request Latency as service level indicators.

B.

Create GKE CPU Utilization and Memory Utilization as service level indicators.

C.

Create Request Latency and Error Rate as service level indicators.

D.

Create Server Uptime and Error Rate as service level indicators.

You need to implement a network ingress for a new game that meets the defined business and technical

requirements. Mountkirk Games wants each regional game instance to be located in multiple Google Cloud

regions. What should you do?

A.

Configure a global load balancer connected to a managed instance group running Compute Engine

instances.

B.

Configure kubemci with a global load balancer and Google Kubernetes Engine.

C.

Configure a global load balancer with Google Kubernetes Engine.

D.

Configure Ingress for Anthos with a global load balancer and Google Kubernetes Engine.

You are implementing Firestore for Mountkirk Games. Mountkirk Games wants to give a new game

programmatic access to a legacy game ' s Firestore database. Access should be as restricted as possible. What

should you do?

A.

Create a service account (SA) in the legacy game ' s Google Cloud project, add this SA in the new game ' s IAM page, and then give it the Firebase Admin role in both projects

B.

Create a service account (SA) in the legacy game ' s Google Cloud project, add a second SA in the new game ' s IAM page, and then give the Organization Admin role to both SAs

C.

Create a service account (SA) in the legacy game ' s Google Cloud project, give it the Firebase Admin role, and then migrate the new game to the legacy game ' s project.

D.

Create a service account (SA) in the lgacy game ' s Google Cloud project, give the SA the Organization Admin rule and then give it the Firebase Admin role in both projects

Your development team has created a mobile game app. You want to test the new mobile app on Android and

iOS devices with a variety of configurations. You need to ensure that testing is efficient and cost-effective. What

should you do?

A.

Upload your mobile app to the Firebase Test Lab, and test the mobile app on Android and iOS devices.

B.

Create Android and iOS VMs on Google Cloud, install the mobile app on the VMs, and test the mobile app.

C.

Create Android and iOS containers on Google Kubernetes Engine (GKE), install the mobile app on the

containers, and test the mobile app.

D.

Upload your mobile app with different configurations to Firebase Hosting and test each configuration.

For this question, refer to the TerramEarth case study. Considering the technical requirements, how should you reduce the unplanned vehicle downtime in GCP?

A.

Use BigQuery as the data warehouse. Connect all vehicles to the network and stream data into BigQuery using Cloud Pub/Sub and Cloud Dataflow. Use Google Data Studio for analysis and reporting.

B.

Use BigQuery as the data warehouse. Connect all vehicles to the network and upload gzip files to a Multi-Regional Cloud Storage bucket using gcloud. Use Google Data Studio for analysis and reporting.

C.

Use Cloud Dataproc Hive as the data warehouse. Upload gzip files to a MultiRegional Cloud Storage

bucket. Upload this data into BigQuery using gcloud. Use Google data Studio for analysis and reporting.

D.

Use Cloud Dataproc Hive as the data warehouse. Directly stream data into prtitioned Hive tables. Use Pig scripts to analyze data.

For this question, refer to the TerramEarth case study.

You start to build a new application that uses a few Cloud Functions for the backend. One use case requires a Cloud Function func_display to invoke another Cloud Function func_query. You want func_query only to accept invocations from func_display. You also want to follow Google ' s recommended best practices. What should you do?

A.

Create a token and pass it in as an environment variable to func_display. When invoking func_query, include the token in the request Pass the same token to func _query and reject the invocation if the tokens are different.

B.

Make func_query ' Require authentication. ' Create a unique service account and associate it to func_display. Grant the service account invoker role for func_query. Create an id token in func_display and include the token to the request when invoking func_query.

C.

Make func _query ' Require authentication ' and only accept internal traffic. Create those two functions in the same VPC. Create an ingress firewall rule for func_query to only allow traffic from func_display.

D.

Create those two functions in the same project and VPC. Make func_query only accept internal traffic. Create an ingress firewall for func_query to only allow traffic from func_display. Also, make sure both functions use the same service account.

TerramEarth has a legacy web application that you cannot migrate to cloud. However, you still want to build a cloud-native way to monitor the application. If the application goes down, you want the URL to point to a " Site is unavailable " page as soon as possible. You also want your Ops team to receive a notification for the issue. You need to build a reliable solution for minimum cost

What should you do?

A.

Create a scheduled job in Cloud Run to invoke a container every minute. The container will check the application URL If the application is down, switch the URL to the " Site is unavailable " page, and notify the Ops team.

B.

Create a cron job on a Compute Engine VM that runs every minute. The cron job invokes a Python program to check the application URL If the application is down, switch the URL to the " Site is unavailable " page, and notify the Ops team.

C.

Create a Cloud Monitoring uptime check to validate the application URL If it fails, put a message in a Pub/Sub queue that triggers a Cloud Function to switch the URL to the " Site is unavailable " page, and notify the Ops team.

D.

Use Cloud Error Reporting to check the application URL If the application is down, switch the URL to the " Site is unavailable " page, and notify the Ops team.

You have broken down a legacy monolithic application into a few containerized RESTful microservices. You want to run those microservices on Cloud Run. You also want to make sure the services are highly available with low latency to your customers. What should you do?

A.

Deploy Cloud Run services to multiple availability zones. Create Cloud Endpoints that point to the services. Create a global HTIP(S) Load Balancing instance and attach the Cloud Endpoints to its backend.

B.

Deploy Cloud Run services to multiple regions Create serverless network endpoint groups pointing to the services. Add the serverless NE Gs to a backend service that is used by a global HTIP(S) Load Balancing instance.

C.

Cloud Run services to multiple regions. In Cloud DNS, create a latency-based DNS name that points to the services.

D.

Deploy Cloud Run services to multiple availability zones. Create a TCP/IP global load balancer. Add the Cloud Run Endpoints to its backend service.

For this question, refer to the TerramEarth case study. To be compliant with European GDPR regulation, TerramEarth is required to delete data generated from its European customers after a period of 36 months when it contains personal data. In the new architecture, this data will be stored in both Cloud Storage and BigQuery. What should you do?

A.

Create a BigQuery table for the European data, and set the table retention period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.

B.

Create a BigQuery table for the European data, and set the table retention period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action when with an Age condition of 36 months.

C.

Create a BigQuery time-partitioned table for the European data, and set the partition expiration period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.

D.

Create a BigQuery time-partitioned table for the European data, and set the partition period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action with an Age condition of 36 months.