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Viewing questions 31-40 out of questions

Questions # 31:

TerramEarth has about 1 petabyte (PB) of vehicle testing data in a private data center. You want to move the data to Cloud Storage for your machine learning team. Currently, a 1-Gbps interconnect link is available for you. The machine learning team wants to start using the data in a month. What should you do?

Options:

Request Transfer Appliances from Google Cloud, export the data to appliances, and return the appliances to Google Cloud.

Configure the Storage Transfer service from Google Cloud to send the data from your data center to Cloud Storage

Make sure there are no other users consuming the 1 Gbps link, and use multi-thread transfer to upload the data to Cloud Storage.

Export files to an encrypted USB device, send the device to Google Cloud, and request an import of the data to Cloud Storage

Questions # 32:

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

Options:

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.

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.

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.

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

Questions # 33:

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?

Options:

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.

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.

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.

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.

Questions # 34:

You are migrating a Linux-based application from your private data center to Google Cloud. The TerramEarth security team sent you several recent Linux vulnerabilities published by Common Vulnerabilities and Exposures (CVE). You need assistance in understanding how these vulnerabilities could impact your migration. What should you do?

Options:

Open a support case regarding the CVE and chat with the support engineer.

Read the CVEs from the Google Cloud Status Dashboard to understand the impact.

Read the CVEs from the Google Cloud Platform Security Bulletins to understand the impact

Post a question regarding the CVE in Stack Overflow to get an explanation

Post a question regarding the CVE in a Google Cloud discussion group to get an explanation

Questions # 35:

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?

Options:

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.

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.

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

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

Questions # 36:

For this question, refer to the TerramEarth case study. You are asked to design a new architecture for the

ingestion of the data of the 200,000 vehicles that are connected to a cellular network. You want to follow

Google-recommended practices.

Considering the technical requirements, which components should you use for the ingestion of the data?

Options:

Google Kubernetes Engine with an SSL Ingress

Cloud IoT Core with public/private key pairs

Compute Engine with project-wide SSH keys

Compute Engine with specific SSH keys

Questions # 37:

Your company captures all web traffic data in Google Analytics 260 and stores it in BigQuery. Each country has its own dataset. Each dataset has multiple tables. You want analysts from each country

to be able to see and query only the data for their respective countries.

How should you configure the access rights?

Options:

Create a group per country. Add analysts to their respective country-groups. Create a single group

‘all_analysts’, and add all country-groups as members. Grant the ‘all-analysis’ group the IAM role of

BigQuery jobUser. Share the appropriate dataset with view access with each respective analyst country-group.

Create a group per country. Add analysts to their respective country-groups. Create a single group

‘all_analysts’, and add all country-groups as members. Grant the ‘all-analysis’ group the IAM role of

BigQuery jobUser. Share the appropriate tables with view access with each respective analyst countrygroup.

Create a group per country. Add analysts to their respective country-groups. Create a single group

‘all_analysts’, and add all country-groups as members. Grant the ‘all-analysis’ group the IAM role of

BigQuery dataViewer. Share the appropriate dataset with view access with each respective analyst

country-group.

Create a group per country. Add analysts to their respective country-groups. Create a single group

‘all_analysts’, and add all country-groups as members. Grant the ‘all-analysis’ group the IAM role of

BigQuery dataViewer. Share the appropriate table with view access with each respective analyst countrygroup.

Questions # 38:

Your organization has decided to restrict the use of external IP addresses on instances to only approved instances. You want to enforce this requirement across all of your Virtual Private Clouds (VPCs). What should you do?

Options:

Remove the default route on all VPCs. Move all approved instances into a new subnet that has a default route to an internet gateway.

Create a new VPC in custom mode. Create a new subnet for the approved instances, and set a default route to the internet gateway on this new subnet.

Implement a Cloud NAT solution to remove the need for external IP addresses entirely.

Set an Organization Policy with a constraint on constraints/compute.vmExternalIpAccess. List the approved instances in the allowedValues list.

Questions # 39:

Your company creates rendering software which users can download from the company website. Your

company has customers all over the world. You want to minimize latency for all your customers. You want to follow Google-recommended practices.

How should you store the files?

Options:

Save the files in a Multi-Regional Cloud Storage bucket.

Save the files in a Regional Cloud Storage bucket, one bucket per zone of the region.

Save the files in multiple Regional Cloud Storage buckets, one bucket per zone per region.

Save the files in multiple Multi-Regional Cloud Storage buckets, one bucket per multi-region.

Questions # 40:

You have deployed an application to Kubernetes Engine, and are using the Cloud SQL proxy container to

make the Cloud SQL database available to the services running on Kubernetes. You are notified that the

application is reporting database connection issues. Your company policies require a post-mortem. What should you do?

Options:

Use gcloud sql instances restart.

Validate that the Service Account used by the Cloud SQL proxy container still has the Cloud Build Editor role.

In the GCP Console, navigate to Stackdriver Logging. Consult logs for Kubernetes Engine and Cloud SQL.

In the GCP Console, navigate to Cloud SQL. Restore the latest backup. Use kubect1 to restart all pods.

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Viewing questions 31-40 out of questions

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