2023年12月 Google Professional-Cloud-Architect認定リアル2023年最新の模擬試験合格させます
Professional-Cloud-Architect試験問題と有効なProfessional-Cloud-Architect問題集でPDF
質問 # 89
Your company captures all web traffic data in Google Analytics 360 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?
- A. 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-analysts' group the IAM role of BigQuery dataViewer. Share the appropriate table with view access with each respective analyst country- group. - B. 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-analysts' group the IAM role of BigQuery jobUser. Share the appropriate dataset with view access with each respective analyst country- group. - C. 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-analysts' group the IAM role of BigQuery dataViewer. Share the appropriate dataset with view access with each respective analyst country- group. - D. 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-analysts' group the IAM role of BigQuery jobUser. Share the appropriate tables with view access with each respective analyst country- group.
正解：B
質問 # 90
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. 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 - 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. Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job
正解：C
解説：
Explanation/Reference:
Explanation:
Storageguarantees 2 replicates which are geo diverse (100 miles apart) which can get better remote
latency and availability.
More importantly, is that multiregional heavily leverages Edge caching and CDNs to provide the content to
the end users.
All this redundancy and caching means that Multiregional comes with overhead to sync and ensure
consistency between geo-diverse areas. As such, it's much better for write-once-read-many scenarios.
This means frequently accessed (e.g. "hot" objects) around the world, such as website content, streaming
videos, gaming or mobile applications.
References: https://medium.com/google-cloud/google-cloud-storage-what-bucket-class-for-the-best-
performance-5c847ac8f9f2
質問 # 91
Your company's user-feedback portal comprises a standard LAMP stack replicated across two zones. It is deployed in the us-central1 region and uses autoscaled managed instance groups on all layers, except the database. Currently, only a small group of select customers have access to the portal. The portal meets a
99.99% availability SLA under these conditions However next quarter, your company will be making the portal available to all users, including unauthenticated users. You need to develop a resiliency testing strategy to ensure the system maintains the SLA once they introduce additional user load. What should you do?
- A. Expose the new system to a larger group of users, and increase group ' size each day until autoscale logic is tnggered on all layers. At the same time, terminate random resources on both zones.
- B. Capture existing users input, and replay captured user load until resource utilization crosses 80%. Also, derive estimated number of users based on existing users usage of the app, and deploy enough resources to handle 200% of expected load.
- C. Capture existing users input, and replay captured user load until autoscale is triggered on all layers. At the same time, terminate all resources in one of the zones.
- D. Create synthetic random user input, replay synthetic load until autoscale logic is triggered on at least one layer, and introduce "chaos" to the system by terminating random resources on both zones.
正解：C
質問 # 92
Your company wants to start using Google Cloud resources but wants to retain their on-premises Active Directory domain controller for identity management. What should you do?
- A. Use Google Cloud Directory Sync to synchronize Active Directory usernames with cloud identities and configure SAML SSO.
- B. Use the Admin Directory API to authenticate against the Active Directory domain controller.
- C. Use Cloud Identity-Aware Proxy configured to use the on-premises Active Directory domain controller as an identity provider.
- D. Use Compute Engine to create an Active Directory (AD) domain controller that is a replica of the on- premises AD domain controller using Google Cloud Directory Sync.
正解：A
質問 # 93
A development team at your company has created a dockerized HTTPS web application. You need to deploy the application on Google Kubernetes Engine (GKE) and make sure that the application scales automatically.
How should you deploy to GKE?
- A. Use the Horizontal Pod Autoscaler and enable cluster autoscaling. Use an Ingress resource to load-balance the HTTPS traffic.
- B. Use the Horizontal Pod Autoscaler and enable cluster autoscaling on the Kubernetes cluster. Use a Service resource of type LoadBalancer to load-balance the HTTPS traffic.
- C. Enable autoscaling on the Compute Engine instance group. Use an Ingress resource to load-balance the HTTPS traffic.
- D. Enable autoscaling on the Compute Engine instance group. Use a Service resource of type LoadBalancer to load-balance the HTTPS traffic.
正解：B
解説：
Explanation/Reference: https://cloud.google.com/kubernetes-engine/docs/how-to/cluster-autoscaler
質問 # 94
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 be applied after the release is in the production environment.
- B. Unit tests are no longer required, only end-to-end tests.
- C. Tests should scale well beyond the prior approaches.
- D. Tests should include directly testing the Google Cloud Platform (GCP) infrastructure.
正解：C
解説：
Explanation
From Scenario:
A few of their games were more popular than expected, and they had problems scaling their application servers, MySQL databases, and analytics tools.
Requirements for Game Analytics Platform include: Dynamically scale up or down based on game activity
質問 # 95
During a high traffic portion of the day, one of your relational databases crashes, but the replica is never promoted to a master. You want to avoid this in the future. What should you do?
- A. Choose larger instances for your database.
- B. Implement routinely scheduled failovers of your databases.
- C. Use a different database.
- D. Create snapshots of your database more regularly.
正解：D
解説：
Explanation: https://cloud.google.com/solutions/disaster-recovery-cookbook
質問 # 96
Your agricultural division is experimenting with fully autonomous vehicles. You want your architecture to promote strong security during vehicle operation.
Which two architectures should you consider? (Choose two.)
- A. Use a trusted platform module (TPM) and verify firmware and binaries on boot.
- B. Use multiple connectivity subsystems for redundancy.
- C. Enclose the vehicle's drive electronics in a Faraday cage to isolate chips.
- D. Use a functional programming language to isolate code execution cycles.
- E. Require IPv6 for connectivity to ensure a secure address space.
- F. Treat every micro service call between modules on the vehicle as untrusted.
正解：A、F
質問 # 97
Case Study: 7 - Mountkirk Games
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of their games using some server-side integration. Historically, they have used cloud providers to lease physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Business Requirements
Increase to a global footprint.
Improve uptime - downtime is loss of players.
Increase efficiency of the cloud resources we use.
Reduce latency to all customers.
Technical Requirements
Requirements for Game Backend Platform
Dynamically scale up or down based on game activity.
Connect to a transactional database service to manage user profiles and game state.
Store game activity in a timeseries database service for future analysis.
As the system scales, ensure that data is not lost due to processing backlogs.
Run hardened Linux distro.
Requirements for Game Analytics Platform
Dynamically scale up or down based on game activity
Process incoming data on the fly directly from the game servers
Process data that arrives late because of slow mobile networks
Allow queries to access at least 10 TB of historical data
Process files that are regularly uploaded by users' mobile devices
Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the game to target users.
Additionally, our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
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?
- A. BigQuery
- B. Cloud Datastore
- C. Cloud Bigtable
- D. Cloud Spanner
正解：C
質問 # 98
Your company is running a stateless application on a Compute Engine instance. The application is used heavily during regular business hours and lightly outside of business hours. Users are reporting that the application is slow during peak hours. You need to optimize the application's performance. What should you do?
- A. Create a custom image from the existing disk. Create an instance template from the custom image.
Create an autoscaled managed instance group from the instance template. - B. Create an instance template from the existing disk. Create a custom image from the instance template.
Create an autoscaled managed instance group from the custom image. - C. Create a snapshot of the existing disk. Create a custom image from the snapshot. Create an autoscaled managed instance group from the custom image.
- D. Create a snapshot of the existing disk. Create an instance template from the snapshot. Create an autoscaled managed instance group from the instance template.
正解：A
質問 # 99
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?
- A. Use Cloud SQL for its ability to automatically manage storage increases and compatibility with MySQL. Use separate database instances for each season.
- 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 Firestore for its scalable and flexible document-based database. Use collections to aggregate race data by season and event.
- D. Use BigQuery for its scalability and ability to add columns to a schema. Partition race data based on season.
正解：D
質問 # 100
Your company has successfully migrated to the cloud and wants to analyze their data stream to optimize
operations. They do not have any existing code for this analysis, so they are exploring all their options.
These options include a mix of batch and stream processing, as they are running some hourly jobs and
live-processing some data as it comes in.
Which technology should they use for this?
- A. Google Cloud Dataflow
- B. Google Compute Engine with Google BigQuery
- C. Google Container Engine with Bigtable
- D. Google Cloud Dataproc
正解：A
解説：
Explanation/Reference:
Explanation:
Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and
batch (historical) modes with equal reliability and expressiveness -- no more complex workarounds or
compromises needed.
References: https://cloud.google.com/dataflow/
質問 # 101
For this question, refer to the TerramEarth case study.
TerramEarth's CTO wants to use the raw data from connected vehicles to help identify approximately when a vehicle in the development team to focus their failure. You want to allow analysts to centrally query the vehicle dat a. Which architecture should you recommend?
A)
B)
C)
D)
- A. Option B
- B. Option A
- C. Option D
- D. Option C
正解：B
解説：
https://cloud.google.com/solutions/iot/
https://cloud.google.com/solutions/designing-connected-vehicle-platform
https://cloud.google.com/solutions/designing-connected-vehicle-platform#data_ingestion
http://www.eweek.com/big-data-and-analytics/google-touts-value-of-cloud-iot-core-for-analyzing-connected-car-data
https://cloud.google.com/solutions/iot/
The push endpoint can be a load balancer.
A container cluster can be used.
Cloud Pub/Sub for Stream Analytics
References: https://cloud.google.com/pubsub/
https://cloud.google.com/solutions/iot/
https://cloud.google.com/solutions/designing-connected-vehicle-platform
https://cloud.google.com/solutions/designing-connected-vehicle-platform#data_ingestion
http://www.eweek.com/big-data-and-analytics/google-touts-value-of-cloud-iot-core-for-analyzing-connected-car-data
https://cloud.google.com/solutions/iot/
質問 # 102
You need to develop procedures to verify resilience of disaster recovery for remote recovery using GCP. Your production environment is hosted on-premises. You need to establish a secure, redundant connection between your on premises network and the GCP network.
What should you do?
- A. Verify that Dedicated Interconnect can replicate files to GCP. Verify that Cloud VPN can establish a secure connection between your networks if Dedicated Interconnect fails.
- B. Verify that the Transfer Appliance can replicate files to GCP. Verify that Cloud VPN can establish a secure connection between your networks if the Transfer Appliance fails.
- C. Verify that Dedicated Interconnect can replicate files to GCP. Verify that direct peering can establish a secure connection between your networks if Dedicated Interconnect fails.
- D. Verify that the Transfer Appliance can replicate files to GCP. Verify that direct peering can establish a secure connection between your networks if the Transfer Appliance fails.
正解：A
解説：
https://cloud.google.com/interconnect/docs/how-to/direct-peering
質問 # 103
For this question, refer to the TerramEarth case study
Your 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. Create secondary credentials for each dealer that can be given to the trusted third party.
- C. Build SAML 2.0 SSO compatibility into your authentication system.
- D. Restrict data access based on the source IP address of the partner systems.
正解：A
解説：
Explanation
https://cloud.google.com/appengine/docs/flexible/go/authorizing-apps
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations#delegate_application_autho Delegate application authorization with OAuth2 Cloud Platform APIs support OAuth 2.0, and scopes provide granular authorization over the methods that are supported. Cloud Platform supports both service-account and user-account OAuth, also called three-legged OAuth.
References:
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations#delegate_application_autho
https://cloud.google.com/appengine/docs/flexible/go/authorizing-apps
質問 # 104
You want to create a private connection between your instances on Compute Engine and your on- premises data center. You require a connection of at least 20 Gbps. You want to follow Google- recommended practices. How should you set up the connection?
- A. Create a Cloud Content Delivery Network (Cloud CDN) and connect it to your on-premises datacenter using a single Cloud VPN.
- B. Create a VPC and connect it to your on-premises data center using a single Cloud VPN.
- C. Create a Cloud Content Delivery Network (Cloud CDN) and connect it to your on-premises data center using Dedicated Interconnect.
- D. Create a VPC and connect it to your on-premises data center using Dedicated Interconnect.
正解：B
質問 # 105
Your company wants to track whether someone is present in a meeting room reserved for a scheduled meeting. There are 1000 meeting rooms across 5 offices on 3 continents.
Each room is equipped with a motion sensor that reports its status every second. The data from the motion detector includes only a sensor ID and several different discrete items of information. Analysts will use this data, together with information about account owners and office locations. Which database type should you use?
- A. Flat file
- B. NoSQL
- C. Relational
- D. Blobstore
正解：B
質問 # 106
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?
- A. Make sure there are no other users consuming the 1 Gbps link, and use multi-thread transfer to upload the data to Cloud Storage.
- B. Export files to an encrypted USB device, send the device to Google Cloud, and request an import of the data to Cloud Storage
- C. Request Transfer Appliances from Google Cloud, export the data to appliances, and return the appliances to Google Cloud.
- D. Configure the Storage Transfer service from Google Cloud to send the data from your data center to Cloud Storage
正解：C
質問 # 107
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?
- A. Migrate from FTP to streaming transport, migrate from CSV to binary format, and develop machine learning analysis of metrics.
- B. Migrate from CSV to binary format, migrate from FTP to SFTP transport, 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.
正解：C
解説：
The Avro binary format is the preferred format for loading compressed data. Avro data is faster to load because the data can be read in parallel, even when the data blocks are compressed.
Cloud Storage supports streaming transfers with the gsutil tool or boto library, based on HTTP chunked transfer encoding. Streaming data lets you stream data to and from your Cloud Storage account as soon as it becomes available without requiring that the data be first saved to a separate file. Streaming transfers are useful if you have a process that generates data and you do not want to buffer it locally before uploading it, or if you want to send the result from a computational pipeline directly into Cloud Storage.
References:
https://cloud.google.com/storage/docs/streaming
https://cloud.google.com/bigquery/docs/loading-data
質問 # 108
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. 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
- B. 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
- C. Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job
- D. Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job
正解：B
解説：
Storageguarantees 2 replicates which are geo diverse (100 miles apart) which can get better remote latency and availability.
More importantly, is that multiregional heavily leverages Edge caching and CDNs to provide the content to the end users.
All this redundancy and caching means that Multiregional comes with overhead to sync and ensure consistency between geo-diverse areas. As such, it's much better for write-once-read-many scenarios. This means frequently accessed (e.g. "hot" objects) around the world, such as website content, streaming videos, gaming or mobile applications.
Reference: https://medium.com/google-cloud/google-cloud-storage-what-bucket-class-for-the-best- performance-5c847ac8f9f2
質問 # 109
You need to develop procedures to test a disaster plan for a mission-critical application. You want to use Google-recommended practices and native capabilities within GCP.
What should you do?
- A. Use Deployment Manager to automate provisioning. Use Stackdriver to monitor and debug your tests.
- B. Use gcloud scripts to automate service provisioning. Use Activity Logs monitor and debug your tests.
- C. Use automated scripts to automate service provisioning. Use Activity Logs monitor and debug your tests.
- D. Use Deployment Manager to automate service provisioning. Use Activity Logs to monitor and debug your tests.
正解：A
解説：
https://cloud.google.com/solutions/dr-scenarios-planning-guide
質問 # 110
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