Professional-Cloud-ArchitectのPDF問題集で2024年08月28日試験問題 有効なProfessional-Cloud-Architect問題集
究極のProfessional-Cloud-Architect準備ガイドで無料最新のGoogle練習テスト問題集
この認定は2年間有効で、Professional-Cloud-Architect 試験の現在のバージョンに合格することで更新できます。GCP における専門知識を示すだけでなく、この認定はクラウド技術やソリューションに対する候補者の能力を示し、クラウド関連の分野で働く IT プロフェッショナルにとって貴重な資産となります。
Google Professional-Cloud-Architect 認定試験の出題範囲：
| トピック | 出題範囲 |
|---|---|
| トピック 1 |
|
| トピック 2 |
|
| トピック 3 |
|
| トピック 4 |
|
| トピック 5 |
|
質問 # 152
Your company has multiple on-premises systems that serve as sources for reporting. The data has not been maintained well and has become degraded over time. You want to use Google-recommended practices to detect anomalies in your company data. What should you do?
- A. Upload your files into Cloud Storage. Use Cloud Datalab to explore and clean your data.
- B. Connect Cloud Dataprep to your on-premises systems. Use Cloud Dataprep to explore and clean your data.
- C. Connect Cloud Datalab to your on-premises systems. Use Cloud Datalab to explore and clean your data.
- D. Upload your files into Cloud Storage. Use Cloud Dataprep to explore and clean your data.
正解：D
解説：
https://cloud.google.com/dataprep/
質問 # 153
Dress4Win has asked you for advice on how to migrate their on-premises MySQL deployment to the
cloud.
They want to minimize downtime and performance impact to their on-premises solution during the
migration.
Which approach should you recommend?
- A. Create a new MySQL cluster in the cloud, configure applications to begin writing to both on premises
and cloud MySQL masters, and destroy the original cluster at cutover. - B. Create a dump of the MySQL replica server into the cloud environment, load it into: Google Cloud
Datastore, and configure applications to read/write to Cloud Datastore at cutover. - C. Setup a MySQL replica server/slave in the cloud environment, and configure it for asynchronous
replication from the MySQL master server on-premises until cutover. - D. Create a dump of the on-premises MySQL master server, and then shut it down, upload it to the cloud
environment, and load into a new MySQL cluster.
正解：C
解説：
Professional Cloud Architect
Testlet 1
Company Overview
JencoMart is a global retailer with over 10,000 stores in 16 countries. The stores carry a range of goods,
such as groceries, tires, and jewelry. One of the company's core values is excellent customer service. In
addition, they recently introduced an environmental policy to reduce their carbon output by 50% over the
next 5 years.
Company Background
JencoMart started as a general store in 1931, and has grown into one of the world's leading brands, known
for great value and customer service. Over time, the company transitioned from only physical stores to a
stores and online hybrid model, with 25% of sales online. Currently, JencoMart has little presence in Asia,
but considers that market key for future growth.
Solution Concept
JencoMart wants to migrate several critical applications to the cloud but has not completed a technical
review to determine their suitability for the cloud and the engineering required for migration. They currently
host all of these applications on infrastructure that is at its end of life and is no longer supported.
Existing Technical Environment
JencoMart hosts all of its applications in 4 data centers: 3 in North American and 1 in Europe; most
applications are dual-homed.
JencoMart understands the dependencies and resource usage metrics of their on-premises architecture.
Application: Customer loyalty portal
LAMP (Linux, Apache, MySQL and PHP) application served from the two JencoMart-owned U.S. data
centers.
Database
Oracle Database stores user profiles
- 20 TB
- Complex table structure
- Well maintained, clean data
- Strong backup strategy
PostgreSQL database stores user credentials
- Single-homed in US West
- No redundancy
- Backed up every 12 hours
- 100% uptime service level agreement (SLA)
- Authenticates all users
Compute
30 machines in US West Coast, each machine has:
- Twin, dual core CPUs
- 32 GB of RAM
- Twin 250 GB HDD (RAID 1)
20 machines in US East Coast, each machine has:
- Single, dual-core CPU
- 24 GB of RAM
- Twin 250 GB HDD (RAID 1)
Storage
Access to shared 100 TB SAN in each location
Tape backup every week
Business Requirements
Optimize for capacity during peak periods and value during off-peak periods
Guarantee service availability and support
Reduce on-premises footprint and associated financial and environmental impact
Move to outsourcing model to avoid large upfront costs associated with infrastructure purchase
Expand services into Asia
Technical Requirements
Assess key application for cloud suitability
Modify applications for the cloud
Move applications to a new infrastructure
Leverage managed services wherever feasible
Sunset 20% of capacity in existing data centers
Decrease latency in Asia
CEO Statement
JencoMart will continue to develop personal relationships with our customers as more people access the
web. The future of our retail business is in the global market and the connection between online and in-
store experiences. As a large, global company, we also have a responsibility to the environment through
"green" initiatives and policies.
CTO Statement
The challenges of operating data centers prevent focus on key technologies critical to our long-term
success. Migrating our data services to a public cloud infrastructure will allow us to focus on big data and
machine learning to improve our service to customers.
CFO Statement
Since its founding, JencoMart has invested heavily in our data services infrastructure. However, because
of changing market trends, we need to outsource our infrastructure to ensure our long-term success. This
model will allow us to respond to increasing customer demand during peak periods and reduce costs.
質問 # 154
A lead engineer wrote a custom tool that deploys virtual machines in the legacy data center. He wants to migrate the custom tool to the new cloud environment You want to advocate for the adoption of Google Cloud Deployment Manager What are two business risks of migrating to Cloud Deployment Manager? Choose 2 answers
- A. Cloud Deployment Manager requires a Google APIs service account to run.
- B. Cloud Deployment Manager APIs could be deprecated in the future.
- C. Cloud Deployment Manager can be used to permanently delete cloud resources.
- D. Cloud Deployment Manager only supports automation of Google Cloud resources.
- E. Cloud Deployment Manager is unfamiliar to the company's engineers.
- F. Cloud Deployment Manager uses Python.
正解：C、D
質問 # 155
Your company is designing its application landscape on Compute Engine. Whenever a zonal outage occurs, the application should be restored in another zone as quickly as possible with the latest application data. You need to design the solution to meet this requirement. What should you do?
- A. Create a snapshot schedule for the disk containing the application data. Whenever a zonal outage occurs, use the latest snapshot to restore the disk in the same zone.
- B. Create a snapshot schedule for the disk containing the application data. Whenever a zonal outage occurs, use the latest snapshot to restore the disk in another zone within the same region.
- C. Configure the Compute Engine instances with an instance template for the application, and use a regional persistent disk for the application data. Whenever a zonal outage occurs, use the instance template to spin up the application in another zone in the same region. Use the regional persistent disk for the application data.
- D. Configure the Compute Engine instances with an instance template for the application, and use a regional persistent disk for the application data. Whenever a zonal outage occurs, use the instance template to spin up the application in another region. Use the regional persistent disk for the application data,
正解：C
解説：
Explanation
Regional persistent disk is a storage option that provides synchronous replication of data between two zones in a region. Regional persistent disks can be a good building block to use when you implement HA services in Compute Engine. https://cloud.google.com/compute/docs/disks/high-availability-regional-persistent-disk
質問 # 156
Case Study: 2 - TerramEarth Case Study
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.
Company Background
TerramEarth formed in 1946, when several small, family owned companies combined to retool after World War II. The company cares about their employees and customers and considers them to be extended members of their family.
TerramEarth is proud of their ability to innovate on their core products and find new markets as their customers' needs change. For the past 20 years trends in the industry have been largely toward increasing productivity by using larger vehicles with a human operator.
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-based systems that reside in a data center. These systems gzip CSV files from the field and upload via FTP, transform and aggregate them, 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, without
increasing the cost of carrying surplus inventory
- Support the dealer network with more data on how their customers use
their equipment IP 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
CEO Statement
We have been successful in capitalizing on the trend toward larger vehicles to increase the productivity of our customers. Technological change is occurring rapidly and TerramEarth has taken advantage of connected devices technology to provide our customers with better services, such as our intelligent farming equipment. With this technology, we have been able to increase farmers' yields by 25%, by using past trends to adjust how our vehicles operate. These advances have led to the rapid growth of our agricultural product line, which we expect will generate 50% of our revenues by 2020.
CTO Statement
Our competitive advantage has always been in the manufacturing process with our ability to build better vehicles for tower 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. Unfortunately, our CEO doesn't take technology obsolescence seriously and he considers the many new companies in our industry to be niche players. My goals are to build our skills while addressing immediate market needs through incremental innovations.
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 field will have a catastrophic failure. You want to allow analysts to centrally query the vehicle data. Which architecture should you recommend?
A:
B:
C:
D:
- A. Option D
- B. Option A
- C. Option B
- D. Option C
正解：B
解説：
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 # 157
You created a pipeline that can deploy your source code changes to your infrastructure in instance groups for self-healing. One of the changes negatively affects your key performance indicator. You are not sure how to fix it, and investigation could take up to a week.
What should you do?
- A. Log in to a server, and iterate on the fox locally
- B. Log into the servers with the bad code change, and swap in the previous code
- C. Change the instance group template to the previous one, and delete all instances
- D. Revert the source code change, and rerun the deployment pipeline
正解：D
質問 # 158
Your company is using BigQuery as its enterprise data warehouse. Data is distributed over several Google Cloud projects. All queries on BigQuery need to be billed on a single project. You want to make sure that no query costs are incurred on the projects that contain the data. Users should be able to query the datasets, but not edit them.
How should you configure users' access roles?
- A. Add all users to a group. Grant the group the roles of BigQuery dataViewer on the billing project and BigQuery user on the projects that contain the data.
- B. Add all users to a group. Grant the group the role of BigQuery user on the billing project and BigQuery dataViewer on the projects that contain the data.
- C. Add all users to a group. Grant the group the roles of BigQuery dataViewer on the billing project and BigQuery jobUser on the projects that contain the data.
- D. Add all users to a group. Grant the group the roles of BigQuery jobUser on the billing project and BigQuery dataViewer on the projects that contain the data.
正解：B
質問 # 159
Your customer is moving their corporate applications to Google Cloud Platform. The security team wants detailed visibility of all resources in the organization. You use Resource Manager to set yourself up as the org admin. What Cloud Identity and Access Management (Cloud IAM) roles should you give to the security team?
- A. Org viewer, Project owner
- B. Org viewer, Project viewer
- C. Org admin, Project browser
- D. Project owner, Network admin
正解：B
解説：
A is not correct because Project owner is too broad. The security team does not need to be able to make changes to projects.
B is correct because:
- Org viewer grants the security team permissions to view the organization's display name.
- Project viewer grants the security team permissions to see the resources within projects.
C is not correct because Org admin is too broad. The security team does not need to be able to make changes to the organization.
D is not correct because Project owner is too broad. The security team does not need to be able to make changes to projects.
https://cloud.google.com/resource-manager/docs/access-control-org#using_predefined_roles
質問 # 160
Case Study: 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.
For this question, refer to the Dress4Win case study.
As part of their new application experience, Dress4Wm allows customers to upload images of themselves. The customer has exclusive control over who may view these images. Customers should be able to upload images with minimal latency and also be shown their images quickly on the main application page when they log in. Which configuration should Dress4Win use?
- A. Use a distributed file system to store customers' images. As storage needs increase, add more persistent disks and/or nodes. Use a Google Cloud SQL database to maintain metadata that maps each customer's ID to their image files.
- B. Store image files in a Google Cloud Storage bucket. Add custom metadata to the uploaded images in Cloud Storage that contains the customer's unique ID.
- C. Store image files in a Google Cloud Storage bucket. Use Google Cloud Datastore to maintain metadata that maps each customer's ID and their image files.
- D. Use a distributed file system to store customers' images. As storage needs increase, add more persistent disks and/or nodes. Assign each customer a unique ID, which sets each file's owner attribute, ensuring privacy of images.
正解：B
質問 # 161
Dress4Win would like to become familiar with deploying applications to the cloud by successfully deploying
some applications quickly, as is. They have asked for your recommendation.
What should you advise?
- A. Suggest moving their in-house databases to the cloud and continue serving requests to on-premise
applications. - B. Identify self-contained applications with external dependencies as a first move to the cloud.
- C. Recommend moving their message queuing servers to the cloud and continue handling requests to on-
premise applications. - D. Identify enterprise applications with internal dependencies and recommend these as a first move to the
cloud.
正解：A
質問 # 162
Your team is developing a web application that will be deployed on Google Kubernetes Engine (GKE). Your CTO expects a successful launch and you need to ensure your application can handle the expected load of tens of thousands of users. You want to test the current deployment to ensure the latency of your application stays below a certain threshold. What should you do?
- A. Enable autoscaling on the GKE cluster and enable horizontal pod autoscaling on your application deployments. Send curl requests to your application, and validate if the auto scaling works.
- B. Use a load testing tool to simulate the expected number of concurrent users and total requests to your application, and inspect the results.
- C. Replicate the application over multiple GKE clusters in every Google Cloud region. Configure a global HTTP (S) load balancer to expose the different clusters over a single global IP address.
- D. Use Cloud Debugger in the development environment to understand the latency between the different microservices.
正解：B
質問 # 163
You need to upload files from your on-premises environment to Cloud Storage. You want the files to be encrypted on Cloud Storage using customer-supplied encryption keys. What should you do?
- A. Use gsutil to create a bucket, and use the flag --encryption-key to supply the encryption key. Use gsutil to upload the files to that bucket.
- B. Supply the encryption key in a .boto configuration file. Use gsutil to upload the files.
- C. Supply the encryption key using gcloud config. Use gsutil to upload the files to that bucket.
- D. Use gsutil to upload the files, and use the flag --encryption-key to supply the encryption key.
正解：A
質問 # 164
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. Data Center expansion, TCO calculations, utilization measurement
- B. Capacity planning, TCO calculations, opex/capex allocation
- C. Capacity planning, utilization measurement, data center expansion
- D. Opex/capex allocation, LAN changes, capacity planning
正解：B
解説：
Capacity planning, TCO calculations, opex/capex allocation From the case study, it can conclude that Management (CXO) all concern rapid provision of resources (infrastructure) for growing as well as cost management, such as Cost optimization in Infrastructure, trade up front capital expenditures (Capex) for ongoing operating expenditures (Opex), and Total cost of ownership (TCO)
質問 # 165
You have developed a non-critical update to your application that is running in a managed instance group, and have created a new instance template with the update that you want to release. To prevent any possible impact to the application, you don't want to update any running instances. You want any new instances that are created by the managed instance group to contain the new update. What should you do?
- A. Start a new rolling update. Select the Proactive update mode.
- B. Start a new rolling restart operation.
- C. Start a new rolling update. Select the Opportunistic update mode.
- D. Start a new rolling replace operation.
正解：A
質問 # 166
Your organization has a 3-tier web application deployed in the same network on Google Cloud Platform. Each tier (web, API, and database) scales independently of the others Network traffic should flow through the web to the API tier and then on to the database tier.
Traffic should not flow between the web and the database tier. How should you configure the network?
- A. Set up software based firewalls on individual VMs.
- B. Add tags to each tier and set up firewall rules to allow the desired traffic flow.
- C. Add each tier to a different subnetwork.
- D. Add tags to each tier and set up routes to allow the desired traffic flow.
正解：B
質問 # 167
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. 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
- B. Set up a network peering between vpc-a and vpc-b
- C. Set up a VPN between vpc-a and vpc-b using Cloud VPN
正解：A
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 # 168
Your organization has a 3-tier web application deployed in the same network on Google Cloud Platform. Each tier (web, API, and database) scales independently of the others. Network traffic should flow through the web to the API tier and then on to the database tier. Traffic should not flow between the web and the database tier.
How should you configure the network?
- A. Add tags to each tier and set up routes to allow the desired traffic flow
- B. Add tags to each tier and set up firewall rules to allow the desired traffic flow
- C. Set up software based firewalls on individual VMs
- D. Add each tier to a different subnetwork
正解：B
解説：
Google Cloud Platform(GCP) enforces firewall rules through rules and tags. GCP rules and tags can be defined once and used across all regions.
Reference: https://cloud.google.com/docs/compare/openstack/
https://aws.amazon.com/it/blogs/aws/building-three-tier-architectures-with-security-groups/
質問 # 169
Your customer is receiving reports that their recently updated Google App Engine application is taking approximately 30 seconds to load for some of their users. This behavior was not reported before the update. What strategy should you take?
- A. Work with your ISP to diagnose the problem.
- B. Roll back to an earlier known good release initially, then use Stackdriver Trace and logging to diagnose the problem in a development/test/staging environment.
- C. Open a support ticket to ask for network capture and flow data to diagnose the problem, then roll back your application.
- D. Roll back to an earlier known good release, then push the release again at a quieter period to investigate. Then use Stackdriver Trace and logging to diagnose the problem.
正解：B
解説：
Stackdriver Logging allows you to store, search, analyze, monitor, and alert on log data and events from Google Cloud Platform and Amazon Web Services (AWS). Our API also allows ingestion of any custom log data from any source. Stackdriver Logging is a fully managed service that performs at scale and can ingest application and system log data from thousands of VMs. Even better, you can analyze all that log data in real time.
References:
https://cloud.google.com/logging/
質問 # 170
Your company is moving 75 TB of data into Google Cloud. You want to use Cloud Storage and follow Google- recommended practices. What should you do?
- A. Move your data onto a Transfer Appliance. Use a Transfer Appliance Rehydrator to decrypt the data into Cloud Storage.
- B. Install gsutil on each server that contains data. Use resumable transfers to upload the data into Cloud Storage.
- C. Move your data onto a Transfer Appliance. Use Cloud Dataprep to decrypt the data into Cloud Storage.
- D. Install gsutil on each server containing data. Use streaming transfers to upload the data into Cloud Storage.
正解：A
質問 # 171
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. Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud Messaging (GCM) to make operational adjustments automatically
- B. Have you engineers inspect the data for patterns, and then create an algorithm with rules that make operational adjustments automatically
- C. Capture all operating data, train machine learning models that identify ideal operations, and run locally 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
正解：C
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 # 172
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. Data Center expansion, TCO calculations, utilization measurement
- B. Capacity planning, TCO calculations, opex/capex allocation
- C. Capacity planning, utilization measurement, data center expansion
- D. Opex/capex allocation, LAN changes, capacity planning
正解：B
解説：
Explanation
Capacity planning, TCO calculations, opex/capex allocation From the case study, it can conclude that Management (CXO) all concern rapid provision of resources (infrastructure) for growing as well as cost management, such as Cost optimization in Infrastructure, trade up front capital expenditures (Capex) for ongoing operating expenditures (Opex), and Total cost of ownership (TCO)
質問 # 173
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. Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud Messaging (GCM) to make operational adjustments automatically
- B. Have you engineers inspect the data for patterns, and then create an algorithm with rules that make operational adjustments automatically
- C. Capture all operating data, train machine learning models that identify ideal operations, and run locally 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
正解：D
解説：
Explanation/Reference:
References: https://cloud.google.com/customers/ocado/
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 # 174
......
Google Professional-Cloud-Architect認定試験は、複数選択とシナリオベースの質問で構成される厳格で包括的です。この試験では、組織のビジネスおよび技術的要件を満たすGCPソリューションを設計、開発、管理する候補者の能力を評価します。認定試験では、GCPインフラストラクチャ、ネットワーキング、セキュリティ、データストレージ、分析、機械学習など、幅広いトピックをカバーしています。試験に合格すると、GCPにおける候補者の習熟度が示され、専門家レベルでGCPソリューションを設計、開発、管理する能力を検証します。
合格率 取得する秘訣はProfessional-Cloud-Architect認定試験エンジンPDF：https://www.jpntest.com/shiken/Professional-Cloud-Architect-mondaishu
今すぐ試そう！高評価Google Professional-Cloud-Architect試験問題集：https://drive.google.com/open?id=1jzGHozJo5ecOVu0zxyIK5CgcJ6iTShgZ