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Questions # 91:

For this question, refer to the TerramEarth case study. TerramEarth has decided to store data files in Cloud Storage. You need to configure Cloud Storage lifecycle rule to store 1 year of data and minimize file storage cost.

Which two actions should you take?

Options:

A.

Create a Cloud Storage lifecycle rule with Age: “30”, Storage Class: “Standard”, and Action: “Set to Coldline”, and create a second GCS life-cycle rule with Age: “365”, Storage Class: “Coldline”, and Action: “Delete”.

B.

Create a Cloud Storage lifecycle rule with Age: “30”, Storage Class: “Coldline”, and Action: “Set to Nearline”, and create a second GCS life-cycle rule with Age: “91”, Storage Class: “Coldline”, and Action: “Set to Nearline”.

C.

Create a Cloud Storage lifecycle rule with Age: “90”, Storage Class: “Standard”, and Action: “Set to Nearline”, and create a second GCS life-cycle rule with Age: “91”, Storage Class: “Nearline”, and Action: “Set to Coldline”.

D.

Create a Cloud Storage lifecycle rule with Age: “30”, Storage Class: “Standard”, and Action: “Set to Coldline”, and create a second GCS life-cycle rule with Age: “365”, Storage Class: “Nearline”, and Action: “Delete”.

Questions # 92:

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

Options:

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.

Questions # 93:

For this question, refer to the Helicopter Racing League (HRL) case study. HRL wants better prediction

accuracy from their ML prediction models. They want you to use Google’s AI Platform so HRL can understand

and interpret the predictions. What should you do?

Options:

A.

Use Explainable AI.

B.

Use Vision AI.

C.

Use Google Cloud’s operations suite.

D.

Use Jupyter Notebooks.

Questions # 94:

For this question, refer to the Helicopter Racing League (HRL) case study. Recently HRL started a new regional

racing league in Cape Town, South Africa. In an effort to give customers in Cape Town a better user

experience, HRL has partnered with the Content Delivery Network provider, Fastly. HRL needs to allow traffic

coming from all of the Fastly IP address ranges into their Virtual Private Cloud network (VPC network). You are

a member of the HRL security team and you need to configure the update that will allow only the Fastly IP

address ranges through the External HTTP(S) load balancer. Which command should you use?

Options:

A.

Apply a Cloud Armor security policy to external load balancers using a named IP list for Fastly.

B.

Apply a Cloud Armor security policy to external load balancers using the IP addresses that Fastly has published. C. Apply a VPC firewall rule on port 443 for Fastly IP address ranges.

C.

Apply a VPC firewall rule on port 443 for network resources tagged with scurceiplisr-fasrly.

Questions # 95:

For this question, refer to the Helicopter Racing League (HRL) case study. Your team is in charge of creating a

payment card data vault for card numbers used to bill tens of thousands of viewers, merchandise consumers,

and season ticket holders. You need to implement a custom card tokenization service that meets the following

requirements:

• It must provide low latency at minimal cost.

• It must be able to identify duplicate credit cards and must not store plaintext card numbers.

• It should support annual key rotation.

Which storage approach should you adopt for your tokenization service?

Options:

A.

Store the card data in Secret Manager after running a query to identify duplicates.

B.

Encrypt the card data with a deterministic algorithm stored in Firestore using Datastore mode.

C.

Encrypt the card data with a deterministic algorithm and shard it across multiple Memorystore instances.

D.

Use column-level encryption to store the data in Cloud SQL.

Questions # 96:

For this question, refer to the Helicopter Racing League (HRL) case study. A recent finance audit of cloud

infrastructure noted an exceptionally high number of Compute Engine instances are allocated to do video

encoding and transcoding. You suspect that these Virtual Machines are zombie machines that were not deleted

after their workloads completed. You need to quickly get a list of which VM instances are idle. What should you

do?

Options:

A.

Log into each Compute Engine instance and collect disk, CPU, memory, and network usage statistics for

analysis.

B.

Use the gcloud compute instances list to list the virtual machine instances that have the idle: true label set.

C.

Use the gcloud recommender command to list the idle virtual machine instances.

D.

From the Google Console, identify which Compute Engine instances in the managed instance groups are

no longer responding to health check probes.

Questions # 97:

For this question, refer to the Helicopter Racing League (HRL) case study. HRL is looking for a cost-effective

approach for storing their race data such as telemetry. They want to keep all historical records, train models

using only the previous season's data, and plan for data growth in terms of volume and information collected.

You need to propose a data solution. Considering HRL business requirements and the goals expressed by

CEO S. Hawke, what should you do?

Options:

A.

Use Firestore for its scalable and flexible document-based database. Use collections to aggregate race data

by season and event.

B.

Use Cloud Spanner for its scalability and ability to version schemas with zero downtime. Split race data

using season as a primary key.

C.

Use BigQuery for its scalability and ability to add columns to a schema. Partition race data based on

season.

D.

Use Cloud SQL for its ability to automatically manage storage increases and compatibility with MySQL. Use

separate database instances for each season.

Questions # 98:

For this question, refer to the Helicopter Racing League (HRL) case study. The HRL development team

releases a new version of their predictive capability application every Tuesday evening at 3 a.m. UTC to a

repository. The security team at HRL has developed an in-house penetration test Cloud Function called Airwolf.

The security team wants to run Airwolf against the predictive capability application as soon as it is released

every Tuesday. You need to set up Airwolf to run at the recurring weekly cadence. What should you do?

Options:

A.

Set up Cloud Tasks and a Cloud Storage bucket that triggers a Cloud Function.

B.

Set up a Cloud Logging sink and a Cloud Storage bucket that triggers a Cloud Function.

C.

Configure the deployment job to notify a Pub/Sub queue that triggers a Cloud Function.

D.

Set up Identity and Access Management (IAM) and Confidential Computing to trigger a Cloud Function.

Questions # 99:

A global media company is launching a new web application. The application backend is hosted on Compute Engine in us-central1 and serves both static assets (images, CSS, and JavaScript) and dynamic, user-specific content from a Cloud SQL database in the same region. Early user feedback from Europe and Asia indicates significant page load delays due to slow loading static content. You need to design a solution that minimizes latency for all global users accessing the static content. What should you do? Choose 2 answers.

Options:

A.

Create Cloud SQL read replicas in regions in Europe and Asia, and direct all database read traffic from those continents to their local replica.

B.

Use a regional external Network Load Balancer in us-central1 to better distribute the incoming global traffic.

C.

Enable Cloud CDN for the backend service that serves the static assets, and configure it as part of a global external HTTP(S) Load Balancer.

D.

Deploy the application frontend service to Compute Engine managed instance groups in regions in Europe and Asia. Use a global external HTTP(S) Load Balancer to route user traffic to the nearest region.

Questions # 100:

Your operations team currently stores 10 TB of data m an object storage service from a third-party provider. They want to move this data to a Cloud Storage bucket as quickly as possible, following Google-recommended practices. They want to minimize the cost of this data migration. When approach should they use?

Options:

A.

Use the gsutil mv command lo move the data

B.

Use the Storage Transfer Service to move the data

C.

Download the data to a Transfer Appliance and ship it to Google

D.

Download the data to the on-premises data center and upload it to the Cloud Storage bucket

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