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

Question # 61

For this question, refer to the TerramEarth case study.

The TerramEarth development team wants to create an API to meet the company ' s business requirements. You want the development team to focus their development effort on business value versus creating a custom framework. Which method should they use?

Options:

A.  

Use Google App Engine with Google Cloud Endpoints. Focus on an API for dealers and partners.

B.  

Use Google App Engine with a JAX-RS Jersey Java-based framework. Focus on an API for the public.

C.  

Use Google App Engine with the Swagger (open API Specification) framework. Focus on an API for the public.

D.  

Use Google Container Engine with a Django Python container. Focus on an API for the public.

E.  

Use Google Container Engine with a Tomcat container with the Swagger (Open API Specification) framework. Focus on an API for dealers and partners.

Discussion 0
Question # 62

For this question, refer to the TerramEarth case study.

TerramEarth plans to connect all 20 million vehicles in the field to the cloud. This increases the volume to 20 million 600 byte records a second for 40 TB an hour. How should you design the data ingestion?

Options:

A.  

Vehicles write data directly to GCS.

B.  

Vehicles write data directly to Google Cloud Pub/Sub.

C.  

Vehicles stream data directly to Google BigQuery.

D.  

Vehicles continue to write data using the existing system (FTP).

Discussion 0
Question # 63

For this question, refer to the TerramEarth case study.

TerramEarth ' s 20 million vehicles are scattered around the world. Based on the vehicle ' s location its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US. Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles. You want to run this job on all the data. What is the most cost-effective way to run this job?

Options:

A.  

Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job.

B.  

Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job.

C.  

Launch a cluster in each region to preprocess and compress the raw data, then move the data into a multi region bucket and use a Dataproc cluster to finish the job.

D.  

Launch a cluster in each region to preprocess and compress the raw data, then move the data into a region bucket and use a Cloud Dataproc cluster to finish the jo

Discussion 0
Question # 64

For this question, refer to the TerramEarth case study.

To speed up data retrieval, more vehicles will be upgraded to cellular connections and be able to transmit data to the ETL process. The current FTP process is error-prone and restarts the data transfer from the start of the file when connections fail, which happens often. You want to improve the reliability of the solution and minimize data transfer time on the cellular connections. What should you do?

Options:

A.  

Use one Google Container Engine cluster of FTP servers. Save the data to a Multi-Regional bucket. Run the ETL process using data in the bucket.

B.  

Use multiple Google Container Engine clusters running FTP servers located in different regions. Save the data to Multi-Regional buckets in us, eu, and asia. Run the ETL process using the data in the bucket.

C.  

Directly transfer the files to different Google Cloud Multi-Regional Storage bucket locations in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process using the data in the bucket.

D.  

Directly transfer the files to a different Google Cloud Regional Storage bucket location in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process to retrieve the data from each Regional bucket.

Discussion 0
Question # 65

For this question, refer to the Mountkirk Games case study

Mountkirk Games needs to create a repeatable and configurable mechanism for deploying isolated application environments. Developers and testers can access each other ' s environments and resources, but they cannot access staging or production resources. The staging environment needs access to some services from production.

What should you do to isolate development environments from staging and production?

Options:

A.  

Create a project for development and test and another for staging and production.

B.  

Create a network for development and test and another for staging and production.

C.  

Create one subnetwork for development and another for staging and production.

D.  

Create one project for development, a second for staging and a third for production.

Discussion 0
Question # 66

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

Options:

A.  

Use Cloud SQL for time series data, and use Cloud Bigtable for historical data queries.

B.  

Use Cloud SQL to replace MySQL, and use Cloud Spanner for historical data queries.

C.  

Use Cloud Bigtable to replace MySQL, and use BigQuery for historical data queries.

D.  

Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use BigQuery for historical data queries.

Discussion 0
Question # 67

For this question, refer to the Mountkirk Games case study. Mountkirk Games wants to design their solution for the future in order to take advantage of cloud and technology improvements as they become available. Which two steps should they take? (Choose two.)

Options:

A.  

Store as much analytics and game activity data as financially feasible today so it can be used to train machine learning models to predict user behavior in the future.

B.  

Begin packaging their game backend artifacts in container images and running them on Kubernetes Engine to improve the availability to scale up or down based on game activity.

C.  

Set up a CI/CD pipeline using Jenkins and Spinnaker to automate canary deployments and improve development velocity.

D.  

Adopt a schema versioning tool to reduce downtime when adding new game features that require storing additional player data in the database.

E.  

Implement a weekly rolling maintenance process for the Linux virtual machines so they can apply critical kernel patches and package updates and reduce the risk of 0-day vulnerabilities.

Discussion 0
Question # 68

For this question, refer to the Mountkirk Games case study. You are in charge of the new Game Backend Platform architecture. The game communicates with the backend over a REST API.

You want to follow Google-recommended practices. How should you design the backend?

Options:

A.  

Create an instance template for the backend. For every region, deploy it on a multi-zone managed instance group. Use an L4 load balancer.

B.  

Create an instance template for the backend. For every region, deploy it on a single-zone managed instance group. Use an L4 load balancer.

C.  

Create an instance template for the backend. For every region, deploy it on a multi-zone managed instance group. Use an L7 load balancer.

D.  

Create an instance template for the backend. For every region, deploy it on a single-zone managed instance group. Use an L7 load balancer.

Discussion 0
Question # 69

For this question, refer to the Mountkirk Games case study. Which managed storage option meets Mountkirk’s technical requirement for storing game activity in a time series database service?

Options:

A.  

Cloud Bigtable

B.  

Cloud Spanner

C.  

BigQuery

D.  

Cloud Datastore

Discussion 0
Question # 70

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?

Options:

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.

Discussion 0

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