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For this question, refer to the Dress4Win case study. Which of the compute services should be migrated as –is and would still be an optimized architecture for performance in the cloud?

A.

Web applications deployed using App Engine standard environment

B.

RabbitMQ deployed using an unmanaged instance group

C.

Hadoop/Spark deployed using Cloud Dataproc Regional in High Availability mode

D.

Jenkins, monitoring, bastion hosts, security scanners services deployed on custom machine types

For this question, refer to the Dress4Win case study. To be legally compliant during an audit, Dress4Win must be able to give insights in all administrative actions that modify the configuration or metadata of resources on Google Cloud.

What should you do?

A.

Use Stackdriver Trace to create a trace list analysis.

B.

Use Stackdriver Monitoring to create a dashboard on the project’s activity.

C.

Enable Cloud Identity-Aware Proxy in all projects, and add the group of Administrators as a member.

D.

Use the Activity page in the GCP Console and Stackdriver Logging to provide the required insight.

For this question, refer to the Dress4Win case study. You want to ensure that your on-premises architecture meets business requirements before you migrate your solution.

What change in the on-premises architecture should you make?

A.

Replace RabbitMQ with Google Pub/Sub.

B.

Downgrade MySQL to v5.7, which is supported by Cloud SQL for MySQL.

C.

Resize compute resources to match predefined Compute Engine machine types.

D.

Containerize the micro services and host them in Google Kubernetes Engine.

For this question, refer to the Dress4Win case study. You are responsible for the security of data stored in

Cloud Storage for your company, Dress4Win. You have already created a set of Google Groups and assigned the appropriate users to those groups. You should use Google best practices and implement the simplest design to meet the requirements.

Considering Dress4Win’s business and technical requirements, what should you do?

A.

Assign custom IAM roles to the Google Groups you created in order to enforce security requirements.

Encrypt data with a customer-supplied encryption key when storing files in Cloud Storage.

B.

Assign custom IAM roles to the Google Groups you created in order to enforce security requirements.

Enable default storage encryption before storing files in Cloud Storage.

C.

Assign predefined IAM roles to the Google Groups you created in order to enforce security requirements.

Utilize Google’s default encryption at rest when storing files in Cloud Storage.

D.

Assign predefined IAM roles to the Google Groups you created in order to enforce security requirements. Ensure that the default Cloud KMS key is set before storing files in Cloud Storage.

For this question, refer to the Dress4Win case study. Dress4Win is expected to grow to 10 times its size in 1 year with a corresponding growth in data and traffic that mirrors the existing patterns of usage. The CIO has set the target of migrating production infrastructure to the cloud within the next 6 months. How will you configure the solution to scale for this growth without making major application changes and still maximize the ROI?

A.

Migrate the web application layer to App Engine, and MySQL to Cloud Datastore, and NAS to Cloud Storage. Deploy RabbitMQ, and deploy Hadoop servers using Deployment Manager.

B.

Migrate RabbitMQ to Cloud Pub/Sub, Hadoop to BigQuery, and NAS to Compute Engine with Persistent Disk storage. Deploy Tomcat, and deploy Nginx using Deployment Manager.

C.

Implement managed instance groups for Tomcat and Nginx. Migrate MySQL to Cloud SQL, RabbitMQ to Cloud Pub/Sub, Hadoop to Cloud Dataproc, and NAS to Compute Engine with Persistent Disk storage.

D.

Implement managed instance groups for the Tomcat and Nginx. Migrate MySQL to Cloud SQL, RabbitMQ to Cloud Pub/Sub, Hadoop to Cloud Dataproc, and NAS to Cloud Storage.

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.

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. 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.

For this question, refer to the Mountkirk Games case study. You need to analyze and define the technical architecture for the compute workloads for your company, Mountkirk Games. Considering the Mountkirk Games business and technical requirements, what should you do?

A.

Create network load balancers. Use preemptible Compute Engine instances.

B.

Create network load balancers. Use non-preemptible Compute Engine instances.

C.

Create a global load balancer with managed instance groups and autoscaling policies. Use preemptible Compute Engine instances.

D.

Create a global load balancer with managed instance groups and autoscaling policies. Use non-preemptible Compute Engine instances.

Mountkirk Games wants you to secure the connectivity from the new gaming application platform to Google

Cloud. You want to streamline the process and follow Google-recommended practices. What should you do?

A.

Configure Workload Identity and service accounts to be used by the application platform.

B.

Use Kubernetes Secrets, which are obfuscated by default. Configure these Secrets to be used by the

application platform.

C.

Configure Kubernetes Secrets to store the secret, enable Application-Layer Secrets Encryption, and use

Cloud Key Management Service (Cloud KMS) to manage the encryption keys. Configure these Secrets to

be used by the application platform.

D.

Configure HashiCorp Vault on Compute Engine, and use customer managed encryption keys and Cloud

Key Management Service (Cloud KMS) to manage the encryption keys. Configure these Secrets to be used

by the application platform.