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Free Google Certified Professional - Cloud Architect (GCP) Practice Questions

Question # 51

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.

Discussion 0
Question # 52

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:

A.  

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

B.  

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

C.  

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

D.  

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

E.  

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

Discussion 0
Question # 53

For this question, refer to the TerramEarth case study. You need to implement a reliable, scalable GCP solution for the data warehouse for your company, TerramEarth. Considering the TerramEarth business and technical requirements, what should you do?

Options:

A.  

Replace the existing data warehouse with BigQuery. Use table partitioning.

B.  

Replace the existing data warehouse with a Compute Engine instance with 96 CPUs.

C.  

Replace the existing data warehouse with BigQuery. Use federated data sources.

D.  

Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional Compute Engine pre-emptible instance with 32 CPUs.

Discussion 0
Question # 54

For this question, refer to the TerramEarth case study. A new architecture that writes all incoming data to

BigQuery has been introduced. You notice that the data is dirty, and want to ensure data quality on an

automated daily basis while managing cost.

What should you do?

Options:

A.  

Set up a streaming Cloud Dataflow job, receiving data by the ingestion process. Clean the data in a Cloud Dataflow pipeline.

B.  

Create a Cloud Function that reads data from BigQuery and cleans it. Trigger it. Trigger the Cloud Function from a Compute Engine instance.

C.  

Create a SQL statement on the data in BigQuery, and save it as a view. Run the view daily, and save the result to a new table.

D.  

Use Cloud Dataprep and configure the BigQuery tables as the source. Schedule a daily job to clean the data.

Discussion 0
Question # 55

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:

A.  

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

B.  

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

C.  

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

D.  

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

Discussion 0
Question # 56

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?

Options:

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.

Discussion 0
Question # 57

For this question refer to the TerramEarth case study.

Which of TerramEarth ' s legacy enterprise processes will experience significant change as a result of increased Google Cloud Platform adoption.

Options:

A.  

Opex/capex allocation, LAN changes, capacity planning

B.  

Capacity planning, TCO calculations, opex/capex allocation

C.  

Capacity planning, utilization measurement, data center expansion

D.  

Data Center expansion, TCO calculations, utilization measurement

Discussion 0
Question # 58

For this question refer to the TerramEarth case study

Operational parameters such as oil pressure are adjustable on each of TerramEarth ' s vehicles to increase their efficiency, depending on their environmental conditions. Your primary goal is to increase the operating efficiency of all 20 million cellular and unconnected vehicles in the field How can you accomplish this goal?

Options:

A.  

Have your engineers inspect the data for patterns, and then create an algorithm with rules that make operational adjustments automatically.

B.  

Capture all operating data, train machine learning models that identify ideal operations, and run locally to make operational adjustments automatically.

C.  

Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud Messaging (GCM) to make operational adjustments automatically.

D.  

Capture all operating data, train machine learning models that identify ideal operations, and host in Google Cloud Machine Learning (ML) Platform to make operational adjustments automatically.

Discussion 0
Question # 59

For this question, refer to the TerramEarth case study.

TerramEarth has equipped unconnected trucks with servers and sensors to collet telemetry data. Next year they want to use the data to train machine learning models. They want to store this data in the cloud while reducing costs. What should they do?

Options:

A.  

Have the vehicle’ computer compress the data in hourly snapshots, and store it in a Google Cloud storage (GCS) Nearline bucket.

B.  

Push the telemetry data in Real-time to a streaming dataflow job that compresses the data, and store it in Google BigQuery.

C.  

Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Cloud Bigtable.

D.  

Have the vehicle ' s computer compress the data in hourly snapshots, a Store it in a GCS Coldline bucket.

Discussion 0
Question # 60

For this question, refer to the TerramEarth case study

You analyzed TerramEarth ' s business requirement to reduce downtime, and found that they can achieve a majority of time saving by reducing customers ' wait time for parts You decided to focus on reduction of the 3 weeks aggregate reporting time Which modifications to the company ' s processes should you recommend?

Options:

A.  

Migrate from CSV to binary format, migrate from FTP to SFTP transport, and develop machine learning analysis of metrics.

B.  

Migrate from FTP to streaming transport, migrate from CSV to binary format, and develop machine learning analysis of metrics.

C.  

Increase fleet cellular connectivity to 80%, migrate from FTP to streaming transport, and develop machine learning analysis of metrics.

D.  

Migrate from FTP to SFTP transport, develop machine learning analysis of metrics, and increase dealer local inventory by a fixed factor.

Discussion 0

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