[2024年更新]合格できるGoogle Professional-Cloud-Architect試験最新282問題
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質問 # 107
Your company and one of its partners each nave a Google Cloud protect in separate organizations. Your company s protect (prj-a) runs in Virtual Private Cloud (vpc-a). The partner's project (prj-b) runs in vpc-b. There are two instances running on vpc-a and one instance running on vpc-b Subnets denned in both VPCs are not overlapping. You need to ensure that all instances communicate with each other via internal IPs minimizing latency and maximizing throughput. What should you do?
- A. Set up a VPN between vpc-a and vpc-b using Cloud VPN
- B. Configure IAP TCP forwarding on the instance in vpc b and then launch the following gcloud command from one of the instance in vpc-gcloud
- C. Set up a network peering between vpc-a and vpc-b
正解：B
解説：
1. Create an additional instance in vpc-a
2. Create an additional instance n vpc-b
3. Instal OpenVPN in newly created instances
4. Configure a VPN tunnel between vpc-a and vpc-b with the help of OpenVPN
質問 # 108
Your development team has installed a new Linux kernel module on the batch servers in Google Compute Engine (GCE) virtual machines (VMs) to speed up the nightly batch process. Two days after the installation,
50% of the batch servers failed the nightly batch run. You want to collect details on the failure to pass back to the development team.
Which three actions should you take? Choose 3 answers.
- A. Use gcloud or Cloud Console to connect to the serial console and observe the logs
- B. Adjust the Google Stackdriver timeline to match the failure time, and observe the batch server metrics
- C. Identify whether a live migration event of the failed server occurred, using in the activity log
- D. Use Stackdriver Logging to search for the module log entries
- E. Read the debug GCE Activity log using the API or Cloud Console
- F. Export a debug VM into an image, and run the image on a local server where kernel log messages will be displayed on the native screen
正解：A、B、D
質問 # 109
You need to deploy an application on Google Cloud that must run on a Debian Linux environment. The application requires extensive configuration in order to operate correctly. You want to ensure that you can install Debian distribution updates with minimal manual intervention whenever they become available. What should you do?
- A. Create a Debian-based Compute Engine instance, install and configure the application, and use OS patch management to install available updates.
- B. Create a Docker container with Debian as the base image. Install and configure the application as part of the Docker image creation process. Host the container on Google Kubernetes Engine and restart the container whenever a new update is available.
- C. Create a Compute Engine instance template using the most recent Debian image. Create an instance from this template, and install and configure the application as part of the startup script. Repeat this process whenever a new Google-managed Debian image becomes available.
- D. Create an instance with the latest available Debian image. Connect to the instance via SSH, and install and configure the application on the instance. Repeat this process whenever a new Google-managed Debian image becomes available.
正解：A
質問 # 110
For this question, refer to the Dress4Win case study. You want to ensure that your on-premises
architecture meets business requirements before you migrate your solution.
What change in the on-premises architecture should you make?
- A. Resize compute resources to match predefined Compute Engine machine types.
- B. Downgrade MySQL to v5.7, which is supported by Cloud SQL for MySQL.
- C. Containerize the micro services and host them in Google Kubernetes Engine.
- D. Replace RabbitMQ with Google Pub/Sub.
正解：A
解説：
Explanation/Reference:
Question Set 1
質問 # 111
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?
- A. Use Google App Engine with a JAX-RS Jersey Java-based framework. Focus on an API for the public.
- B. Use Google App Engine with Google Cloud Endpoints. Focus on an API for dealers and partners.
- C. Use Google Container Engine with a Tomcat container with the Swagger (Open API Specification) framework. Focus on an API for dealers and partners.
- D. Use Google App Engine with the Swagger (open API Specification) framework. Focus on an API for the public.
- E. Use Google Container Engine with a Django Python container. Focus on an API for the public.
正解：B
質問 # 112
For this question, refer to the JencoMart case study.
JencoMart wants to move their User Profiles database to Google Cloud Platform. Which Google Database should they use?
- A. Google Cloud Datastore
- B. Cloud Spanner
- C. Google BigQuery
- D. Google Cloud SQL
正解：A
解説：
https://cloud.google.com/datastore/docs/concepts/overview
Common workloads for Google Cloud Datastore:
User profiles
Product catalogs
Game state
References: https://cloud.google.com/storage-options/
https://cloud.google.com/datastore/docs/concepts/overview
Topic 4, Dress4Win case study
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a website and mobile application. The company also cultivates an active social network that connects their users with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a freemium app model.
Company Background
Dress4win's application has grown from a few servers in the founder's garage to several hundred servers and appliances in a colocated data center. However, the capacity of their infrastructure is now insufficient for the application's rapid growth. Because of this growth and the company's desire to innovate faster, Dress4win is committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4win is considering moving their development and test environments. They are also considering building a disaster recovery site, because their current infrastructure is at a single location. They are not sure which components of their architecture they can migrate as is and which components they need to change before migrating them.
Existing Technical Environment
The Dress4win application is served out of a single data center location.
Databases:
MySQL - user data, inventory, static data
Redis - metadata, social graph, caching
Application servers:
Tomcat - Java micro-services
Nginx - static content
Apache Beam - Batch processing
Storage appliances:
iSCSI for VM hosts
Fiber channel SAN - MySQL databases
NAS - image storage, logs, backups
Apache Hadoop/Spark servers:
Data analysis
Real-time trending calculations
MQ servers:
Messaging
Social notifications
Events
Miscellaneous servers:
Jenkins, monitoring, bastion hosts, security scanners
Business Requirements
Build a reliable and reproducible environment with scaled parity of production.
Improve security by defining and adhering to a set of security and Identity and Access Management (IAM) best practices for cloud.
Improve business agility and speed of innovation through rapid provisioning of new resources.
Analyze and optimize architecture for performance in the cloud.
Migrate fully to the cloud if all other requirements are met.
Technical Requirements
Evaluate and choose an automation framework for provisioning resources in cloud.
Support failover of the production environment to cloud during an emergency.
Identify production services that can migrate to cloud to save capacity.
Use managed services whenever possible.
Encrypt data on the wire and at rest.
Support multiple VPN connections between the production data center and cloud environment.
CEO Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a new competitor could use a public cloud platform to offset their up-front investment and freeing them to focus on developing better features.
CTO Statement
We have invested heavily in the current infrastructure, but much of the equipment is approaching the end of its useful life. We are consistently waiting weeks for new gear to be racked before we can start new projects.
Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
CFO Statement
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total cost of ownership (TCO) analysis over the next 5 years puts a cloud strategy between 30 to 50% lower than our current model.
質問 # 113
You are tasked with building an online analytical processing (OLAP) marketing analytics and reporting tool.
This requires a relational database that can operate on hundreds of terabytes of data. What is the Google recommended tool for such applications?
- A. Cloud Spanner, because it is globally distributed
- B. Cloud SQL, because it is a fully managed relational database
- C. BigQuery, because it is designed for large-scale processing of tabular data
- D. Cloud Firestore, because it offers real-time synchronization across devices
正解：A
解説：
Reference: https://cloud.google.com/files/BigQueryTechnicalWP.pdf
質問 # 114
You are designing a mobile chat application. You want to ensure people cannot spoof chat messages, by providing a message were sent by a specific user.
What should you do
- A. Tag messages client side with the originating user identifier and the destination user.
- B. Encrypt the message client side using block-based encryption with a shared key.
- C. Use a trusted certificate authority to enable SSL connectivity between the client application and the server.
- D. Use public key infrastructure (PKI) to encrypt the message client side using the originating user's private key.
正解：C
解説：
Explanation
Encrypting each block and tagging each message at the client side is an overhead on the application. Best method which has been adopted since years is contacting the SSL provider and use the public certificate to encrypt the traffic between client and the server.
質問 # 115
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. 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.
- B. 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.
- 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. 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.
正解：D
質問 # 116
You need to deploy a stateful workload on Google Cloud. The workload can scale horizontally, but each instance needs to read and write to the same POSIX filesystem. At high load, the stateful workload needs to support up to 100 MB/s of writes. What should you do?
- A. Use a regional persistent disk for each instance.
- B. Create a Cloud Storage bucket and mount it in each instance using gcsfuse.
- C. Create a Cloud Filestore instance and mount it in each instance.
- D. Use a persistent disk for each instance.
正解：B
解説：
Reference: https://cloud.google.com/storage/docs/gcs-fuse
質問 # 117
Your company is building a new architecture to support its data-centric business focus. You are responsible for setting up the network. Your company's mobile and web-facing applications will be deployed on- premises, and all data analysis will be conducted in GCP. The plan is to process and load 7 years of archived .csv files totaling 900 TB of data and then continue loading 10 TB of data daily. You currently have an existing 100-MB internet connection.
What actions will meet your company's needs?
- A. Compress and upload both archived files and files uploaded daily using the gsutil -moption.
- B. Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish a connection with Google using a Dedicated Interconnect or Direct Peering connection and use it to upload files daily.
- C. Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish a Cloud VPN Tunnel to VPC networks over the public internet, and compress and upload files daily.
- D. Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish one Cloud VPN Tunnel to VPC networks over the public internet, and compress and upload files daily using the gsutil-m option.
正解：B
解説：
Explanation/Reference:
質問 # 118
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?
- A. Capture all operating data, train machine learning models that identify ideal operations, and run locally to make operational adjustments automatically
- B. Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud Messaging (GCM) to make operational adjustments automatically
- C. Have you engineers inspect the data for patterns, and then create an algorithm with rules that 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
正解：A
解説：
Explanation/Reference:
TerramEarth, B
Testlet 1
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries. About 80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in
100 countries. Their mission is to build products that make their customers more productive.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second. Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced. The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second, with 22 hours of operation per day, TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux and Windows-based systems that reside in a single
U.S, west coast based data center. These systems gzip CSV files from the field and upload via FTP, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
* Decrease unplanned vehicle downtime to less than 1 week
* Support the dealer network with more data on how their customers use their equipment to better position new products and services
* Have the ability to partner with different companies - especially with seed and fertilizer suppliers in the fast- growing agricultural business - to create compelling joint offerings for their customers Technical Requirements
* Expand beyond a single datacenter to decrease latency to the American midwest and east coast
* Create a backup strategy
* Increase security of data transfer from equipment to the datacenter
* Improve data in the data warehouse
* Use customer and equipment data to anticipate customer needs
Application 1: Data ingest
A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:
* Windows Server 2008 R2
- 16 CPUs
- 128 GB of RAM
- 10 TB local HDD storage
Application 2: Reporting
An off the shelf application that business analysts use to run a daily report to see what equipment needs repair.
Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application at a time.
Compute:
* Off the shelf application. License tied to number of physical CPUs
- Windows Server 2008 R2
- 16 CPUs
- 32 GB of RAM
- 500 GB HDD
Data warehouse:
* A single PostgreSQL server
- RedHat Linux
- 64 CPUs
- 128 GB of RAM
- 4x 6TB HDD in RAID 0
Executive Statement
Our competitive advantage has always been in our manufacturing process, with our ability to build better vehicles for lower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. My goals are to build our skills while addressing immediate market needs through incremental innovations.
質問 # 119
You have been asked to select the storage system for the click-data of your company's large portfolio of websites. This data is streamed in from a custom website analytics package at a typical rate of 6,000 clicks per minute, with bursts of up to 8,500 clicks per second. It must been stored for future analysis by your data science and user experience teams. Which storage infrastructure should you choose?
- A. Google Cloud Storage
- B. Google cloud Datastore
- C. Google Cloud Bigtable
- D. Google Cloud SQL
正解：A
質問 # 120
You have a Python web application with many dependencies that requires 0.1 CPU cores and 128 MB of memory to operate in production. You want to monitor and maximize machine utilization. You also to reliably deploy new versions of the application. Which set of steps should you take?
- A. Perform the following:
1) Create a managed instance group with n1-standard-1 type machines.
2) Build a Compute Engine image from the production branch that contains all of the dependencies and automatically starts the Python app.
3) Rebuild the Compute Engine image, and update the instance template to deploy new production releases. - B. Perform the following:
1) Create a Kubernetes Engine cluster with n1-standard-1 type machines.
2) Build a Docker image from the production branch with all of the dependencies, and tag it with the version number.
3) Create a Kubernetes Deployment with the imagePullPolicy set to "IfNotPresent" in the staging namespace, and then promote it to the production namespace after testing. - C. Perform the following:
1) Create a managed instance group with f1-micro type machines.
2) Use a startup script to clone the repository, check out the production branch, install the dependencies, and start the Python app.
3) Restart the instances to automatically deploy new production releases. - D. Perform the following:
1) Create a Kubernetes Engine (GKE) cluster with n1-standard-4 type machines.
2) Build a Docker image from the master branch will all of the dependencies, and tag it with "latest".
3) Create a Kubernetes Deployment in the default namespace with the imagePullPolicy set to "Always".Restart the pods to automatically deploy new production releases.
正解：D
解説：
Explanation
https://cloud.google.com/compute/docs/instance-templates
質問 # 121
Your company sends all Google Cloud logs to Cloud Logging. Your security team wants to monitor the logs.
You want to ensure that the security team can react quickly if an anomaly such as an unwanted firewall change or server breach is detected. You want to follow Google-recommended practices. What should you do?
- A. Export logs to a Cloud Storage bucket, and trigger Cloud Run with the relevant log events.
- B. Schedule a cron job with Cloud Scheduler. The scheduled job queries the logs every minute for the relevant events.
- C. Export logs to BigQuery, and trigger a query in BigQuery to process the log data for the relevant events.
- D. Export logs to a Pub/Sub topic, and trigger Cloud Function with the relevant log events.
正解：D
質問 # 122
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?
- A. 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
- B. 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
- 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. 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
正解：A
質問 # 123
You are analyzing and defining business processes to support your startup's trial usage of GCP, and you don't yet know what consumer demand for your product will be. Your manager requires you to minimize GCP service costs and adhere to Google best practices. What should you do?
- A. Utilize free tier and committed use discounts. Provision a staff position for service cost management.
- B. Utilize free tier and committed use discounts. Provide training to the team about service cost management.
- C. Utilize free tier and sustained use discounts. Provide training to the team about service cost management.
- D. Utilize free tier and sustained use discounts. Provision a staff position for service cost management.
正解：C
質問 # 124
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