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Google Professional-Cloud-Architect Exam Dumps

Google Certified Professional - Cloud Architect (GCP)

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Total Questions : 248
Update Date : June 05, 2024
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Google Professional-Cloud-Architect Sample Questions

Question # 1

For this question, refer to the Mountkirk Games case study. Mountkirk Games' gaming servers are not automatically scaling properly. Last month, they rolled out a new feature, which suddenly became very popular. A record number of users are trying to use the service, but many of them are getting 503 errors and very slow response times. What should they investigate first?

A.Verify that the database is online.
B.Verify that the project quota hasn't been exceeded.
C.Verify that the new feature code did not introduce any performance bugs.
D.Verify that the load-testing team is not running their tool against production.



Question # 2

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?

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.



Question # 3

For this question, refer to the Mountkirk Games case study. Mountkirk Games wants to set up a continuous delivery pipeline. Their architecture includes many small services that they want to be able to update and roll back quickly. Mountkirk Games has the following requirements:• Services are deployed redundantly across multiple regions in the US and Europe.• Only frontend services are exposed on the public internet.• They can provide a single frontend IP for their fleet of services.• Deployment artifacts are immutable.Which set of products should they use?

A. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
B. Google Cloud Storage, Google App Engine, Google Network Load Balancer
C. Google Kubernetes Registry, Google Container Engine, Google HTTP(S) Load Balancer
D. Google Cloud Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager



Question # 4

For this question, refer to the Mountkirk Games case study. Mountkirk Games wants you to design their new testing strategy. How should the test coverage differ from their existing backends on the other platforms?

A. Tests should scale well beyond the prior approaches.
B. Unit tests are no longer required, only end-to-end tests.
C. Tests should be applied after the release is in the production environment.
D. Tests should include directly testing the Google Cloud Platform (GCP) infrastructure.



Question # 5

For this question, refer to the Mountkirk Games case study.Mountkirk Games has deployed their new backend on Google Cloud Platform (GCP). You want to create a thorough testing process for new versions of the backend before they are released to the public. You want the testing environment to scale in an economical way. How should you design the process?

A. Create a scalable environment in GCP for simulating production load.
B. Use the existing infrastructure to test the GCP-based backend at scale.
 C. Build stress tests into each component of your application using resources internal to GCP to simulate load.
D. Create a set of static environments in GCP to test different levels of load — for example, high, medium, and low.



Question # 6

For this question, refer to the Mountkirk Games case study.Mountkirk Games wants to set up a real-time analytics platform for their new game. The new platform must meet their technical requirements. Which combination of Google technologies will meet all of their requirements?

A. Container Engine, Cloud Pub/Sub, and Cloud SQL
B. Cloud Dataflow, Cloud Storage, Cloud Pub/Sub, and BigQuery
C. Cloud SQL, Cloud Storage, Cloud Pub/Sub, and Cloud Dataflow
D. Cloud Dataproc, Cloud Pub/Sub, Cloud SQL, and Cloud Dataflow
E. Cloud Pub/Sub, Compute Engine, Cloud Storage, and Cloud Dataproc



Question # 7

For this question, refer to the TerramEarth case studyYou 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?

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



Question # 8

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. Whichmethod should they use?

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.



Question # 9

For this question, refer to the TerramEarth case studyYour development team has created a structured API to retrieve vehicle data. They want to allow third parties to develop tools for dealerships that use this vehicle event data. You want to support delegated authorization against this data. What should you do?

A. Build or leverage an OAuth-compatible access control system.
B. Build SAML 2.0 SSO compatibility into your authentication system.
C. Restrict data access based on the source IP address of the partner systems.
D. Create secondary credentials for each dealer that can be given to the trusted third party.



Question # 10

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.

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



Question # 11

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?

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 regionbucket 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 job.



Question # 12

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?

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 Big Query.
C. Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Bigtable.
D. Have the vehicle's computer compress the data in hourly snapshots, a Store it in a GCS Coldline bucket.