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無料Google Professional-Cloud-Architect試験問題と解答トレーニングを提供しています [Q169-Q192]

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無料Google Professional-Cloud-Architect試験問題と解答トレーニングを提供しています

トップクラスGoogle Professional-Cloud-Architectオンライン問題集


Google Professional-Cloud-Architect（Google Certified Professional-Cloud Architect（GCP））認定試験は、Google Cloudを使用した安全、スケーラブル、信頼性の高いクラウドソリューションの設計、開発、および信頼性の高いクラウドソリューションの設計、開発、管理に関する個人の専門知識を検証するGoogleが提供するプロフェッショナル認定試験です。プラットフォーム（GCP）。この認定は、GCPを扱った経験があり、潜在的な雇用主またはクライアントにクラウドアーキテクチャスキルを実証したい個人向けに設計されています。


Google Professional-Cloud-Architect 認定は、IT プロフェッショナルやクラウドアーキテクトが、GCP を使用したクラウドソリューションの設計、開発、管理における専門知識を証明するための貴重な資格です。認定試験は、さまざまなトピックをカバーし、候補者が組織のニーズに合わせてスケーラブルで信頼性の高く、コスト効果の高いクラウドソリューションを設計、展開できる能力を評価するように設計されています。

 

質問 # 169
For this question, refer to the Dress4Win case study. You are responsible for the security of data stored in
Cloud Storage for your company, Dress4Win. You have already created a set of Google Groups and
assigned the appropriate users to those groups. You should use Google best practices and implement the
simplest design to meet the requirements.
Considering Dress4Win's business and technical requirements, what should you do?

  • A. Assign custom IAM roles to the Google Groups you created in order to enforce security requirements.
    Encrypt data with a customer-supplied encryption key when storing files in Cloud Storage.
  • B. Assign custom IAM roles to the Google Groups you created in order to enforce security requirements.
    Enable default storage encryption before storing files in Cloud Storage.
  • C. Assign predefined IAM roles to the Google Groups you created in order to enforce security
    requirements. Ensure that the default Cloud KMS key is set before storing files in Cloud Storage.
  • D. Assign predefined IAM roles to the Google Groups you created in order to enforce security
    requirements. Utilize Google's default encryption at rest when storing files in Cloud Storage.

正解：A


質問 # 170
Case Study: 5 - Dress4win
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. The application has grown from a few servers in the founder's garage to several hundred servers and appliances in a collocated 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 moving their development and test environments. They are also 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. All servers run Ubuntu LTS v16.04.
Databases:
MySQL. 1 server for user data, inventory, static data:

- MySQL 5.8
- 8 core CPUs
- 128 GB of RAM
- 2x 5 TB HDD (RAID 1)
Redis 3 server cluster for metadata, social graph, caching. Each server is:

- Redis 3.2
- 4 core CPUs
- 32GB of RAM
Compute:
40 Web Application servers providing micro-services based APIs and static content.

- Tomcat - Java
- Nginx
- 4 core CPUs
- 32 GB of RAM
20 Apache Hadoop/Spark servers:

- Data analysis
- Real-time trending calculations
- 8 core CPUS
- 128 GB of RAM
- 4x 5 TB HDD (RAID 1)
3 RabbitMQ servers for messaging, social notifications, and events:

- 8 core CPUs
- 32GB of RAM
Miscellaneous servers:

- Jenkins, monitoring, bastion hosts, security scanners
- 8 core CPUs
- 32GB of RAM
Storage appliances:
iSCSI for VM hosts

Fiber channel SAN - MySQL databases

- 1 PB total storage; 400 TB available
NAS - image storage, logs, backups

- 100 TB total storage; 35 TB available
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.

Technical Requirements
Easily create non-production environment in the cloud.

Implement an automation framework for provisioning resources in cloud.

Implement a continuous deployment process for deploying applications to the on-premises

datacenter or cloud.
Support failover of the production environment to cloud during an emergency.

Encrypt data on the wire and at rest.

Support multiple private connections between the production data center and cloud

environment.
Executive Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a competitor could use a public cloud platform to offset their up-front investment and free them to focus on developing better features. Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
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 for a public cloud strategy achieves a cost reduction between 30% and 50% over our current model.
For this question, refer to the Dress4Win case study. Dress4Win is expected to grow to 10 times its size in 1 year with a corresponding growth in data and traffic that mirrors the existing patterns of usage. The CIO has set the target of migrating production infrastructure to the cloud within the next 6 months. How will you configure the solution to scale for this growth without making major application changes and still maximize the ROI?

  • A. Migrate the web application layer to App Engine, and MySQL to Cloud Datastore, and NAS to Cloud Storage. Deploy RabbitMQ, and deploy Hadoop servers using Deployment Manager.
  • B. Implement managed instance groups for the Tomcat and Nginx. Migrate MySQL to Cloud SQL, RabbitMQ to Cloud Pub/Sub, Hadoop to Cloud Dataproc, and NAS to Cloud Storage.
  • C. Migrate RabbitMQ to Cloud Pub/Sub, Hadoop to BigQuery, and NAS to Compute Engine with Persistent Disk storage. Deploy Tomcat, and deploy Nginx using Deployment Manager.
  • D. Implement managed instance groups for Tomcat and Nginx. Migrate MySQL to Cloud SQL, RabbitMQ to Cloud Pub/Sub, Hadoop to Cloud Dataproc, and NAS to Compute Engine with Persistent Disk storage.

正解：B


質問 # 171
Your company has a project in Google Cloud with three Virtual Private Clouds (VPCs). There is a Compute Engine instance on each VPC. Network subnets do not overlap and must remain separated. The network configuration is shown below.

Instance #1 is an exception and must communicate directly with both Instance #2 and Instance #3 via internal IPs. How should you accomplish this?

  • A. Create two VPN tunnels via CloudVPN:
    * 1 between VPC #1 and VPC #2.
    * 1 between VPC #2 and VPC #3.
    Update firewall rules to enable traffic between the instances.
  • B. Peer all three VPCs:
    * Peer VPC #1 with VPC #2.
    * Peer VPC #2 with VPC #3.
    Update firewall rules to enable traffic between the instances.
  • C. Add two additional NICs to Instance #1 with the following configuration:
    * NIC1
    * VPC: VPC #2
    * SUBNETWORK: subnet #2
    * NIC2
    * VPC: VPC #3
    * SUBNETWORK: subnet #3
    Update firewall rules to enable traffic between instances.
  • D. Create a cloud router to advertise subnet #2 and subnet #3 to subnet #1.

正解：C

解説：
As per GCP documentation: "By default, every instance in a VPC network has a single network interface. Use these instructions to create additional network interfaces. Each interface is attached to a different VPC network, giving that instance access to different VPC networks in Google Cloud. You cannot attach multiple network interfaces to the same VPC network." Refer to: https://cloud.google.com/vpc/docs/create-use-multiple-interfaces
https://cloud.google.com/vpc/docs/create-use-multiple-interfaces#i_am_not_able_to_connect_to_secondary_interfaces_internal_ip


質問 # 172
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. Enable autoscaling on the Compute Engine instance group. Use a Service resource of type LoadBalancer to load-balance the HTTPS traffic.
  • B. Enable autoscaling on the Compute Engine instance group. Use an Ingress resource to load balance the HTTPS traffic.
  • C. 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.
  • D. Use the Horizontal Pod Autoscaler and enable cluster autoscaling. Use an Ingress resource to loadbalance the HTTPS traffic.

正解：C

解説：
https://cloud.google.com/kubernetes-engine/docs/tutorials/http-balancer
https://cloud.google.com/kubernetes-engine/docs/concepts/network-overview#ext-lb


質問 # 173
Your company is designing its data lake on Google Cloud and wants to develop different ingestion pipelines to collect unstructured data from different sources. After the data is stored in Google Cloud, it will be processed in several data pipelines to build a recommendation engine for end users on the website. The structure of the data retrieved from the source systems can change at any time. The data must be stored exactly as it was retrieved for reprocessing purposes in case the data structure is incompatible with the current processing pipelines. You need to design an architecture to support the use case after you retrieve the dat a. What should you do?

  • A. Send the data through the processing pipeline, and then store the processed data in a Cloud Storage bucket for reprocessing.
  • B. Store the data in a BigQuery table. Design the processing pipelines to retrieve the data from the table.
  • C. Send the data through the processing pipeline, and then store the processed data in a BigQuery table for reprocessing.
  • D. Store the data in a Cloud Storage bucket. Design the processing pipelines to retrieve the data from the bucket

正解：D

解説：
Topic 1, EHR Health Care
Company Overview
EHR Healthcare is a leading provider of electronic health record software to the medical industry. EHR Healthcare provides their software as a service to multi-national medical offices, hospitals, and insurance providers.
Solution concept
Due to rapid changes in the healthcare and insurance industry, EHR Healthcare's business has been growing exponentially year over year. They need to be able to scale their environment, adapt their disaster recovery plan, and roll out new continuous deployment capabilities to update their software at a fast pace. Google Cloud has been chosen to replace their current colocation facilities.
Existing technical environment
EHR's software is currently hosted in multiple colocation facilities. The lease on one of the data centers is about to expire.
Customer-facing applications are web-based, and many have recently been containerized to run on a group of Kubernetes clusters. Data is stored in a mixture of relational and NoSQL databases (MySQL, MS SQL Server, Redis, and MongoDB).
EHR is hosting several legacy file- and API-based integrations with insurance providers on-premises. These systems are scheduled to be replaced over the next several years. There is no plan to upgrade or move these systems at the current time.
Users are managed via Microsoft Active Directory. Monitoring is currently being done via various open source tools. Alerts are sent via email and are often ignored.
Business Requirements
* On-board new insurance providers as quickly as possible.
* Provide a minimum 99.9% availability for all customer-facing systems.
* Provide centralized visibility and proactive action on system performance and usage.
* Increase ability to provide insights into healthcare trends.
* Reduce latency to all customers.
* Maintain regulatory compliance.
* Decrease infrastructure administration costs.
* Make predictions and generate reports on industry trends based on provider data.
Technical Requirements
* Maintain legacy interfaces to insurance providers with connectivity to both on-premises systems and cloud providers.
* Provide a consistent way to manage customer-facing applications that are container-based.
* Provide a secure and high-performance connection between on-premises systems and Google Cloud.
* Provide consistent logging, log retention, monitoring, and alerting capabilities.
* Maintain and manage multiple container-based environments.
* Dynamically scale and provision new environments.
* Create interfaces to ingest and process data from new providers.
Executive statement
Our on-premises strategy has worked for years but has required a major investment of time and money in training our team on distinctly different systems, managing similar but separate environments, and responding to outages. Many of these outages have been a result of misconfigured systems, inadequate capacity to manage spikes in traffic, and inconsistent monitoring practices. We want to use Google Cloud to leverage a scalable, resilient platform that can span multiple environments seamlessly and provide a consistent and stable user experience that positions us for future growth.


質問 # 174
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 replace operation.
  • B. Start a new rolling restart operation.
  • C. Start a new rolling update. Select the Opportunistic update mode.
  • D. Start a new rolling update. Select the Proactive update mode.

正解：C

解説：
Explanation
In certain scenarios, an opportunistic update is useful because you don't want to cause instability to the system if it can be avoided. For example, if you have a non-critical update that can be applied as necessary without any urgency and you have a MIG that is actively being autoscaled, perform an opportunistic update so that Compute Engine does not actively tear down your existing instances to apply the update. When resizing down, the autoscaler preferentially terminates instances with the old template as well as instances that are not yet in a RUNNING state.


質問 # 175
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 # 176
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 Spanner
  • C. Cloud Datastore
  • D. Cloud Bigtable

正解：A


質問 # 177
For this question, refer to the JencoMart case study.
The migration of JencoMart's application to Google Cloud Platform (GCP) is progressing too slowly. The infrastructure is shown in the diagram. You want to maximize throughput. What are three potential bottlenecks? (Choose 3 answers.)

  • A. A separate storage layer outside the VMs, which is not suited for this task
  • B. A copy command that is not suited to operate over long distances
  • C. Fewer virtual machines (VMs) in GCP than on-premises machines
  • D. A tier of Google Cloud Storage that is not suited for this task
  • E. A single VPN tunnel, which limits throughput
  • F. Complicated internet connectivity between the on-premises infrastructure and GCP

正解：C、E、F


質問 # 178
You need to upgrade the EHR connection to comply with their requirements. The new connection design must support business-critical needs and meet the same network and security policy requirements. What should you do?

  • A. Add three new Cloud VPN connections.
  • B. Add a new Dedicated Interconnect connection.
  • C. Upgrade the bandwidth on the Dedicated Interconnect connection to 100 G.
  • D. Add a new Carrier Peering connection.

正解：B


質問 # 179
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. Cloud Pub/Sub, Compute Engine, Cloud Storage, and Cloud Dataproc
  • B. Container Engine, Cloud Pub/Sub, and Cloud SQL
  • C. Cloud Dataflow, Cloud Storage, Cloud Pub/Sub, and BigQuery
  • D. Cloud Dataproc, Cloud Pub/Sub, Cloud SQL, and Cloud Dataflow
  • E. Cloud SQL, Cloud Storage, Cloud Pub/Sub, and Cloud Dataflow

正解：C

解説：
Ingest millions of streaming events per second from anywhere in the world with Cloud Pub/Sub, powered by Google's unique, high-speed private network. Process the streams with Cloud Dataflow to ensure reliable, exactly-once, low-latency data transformation. Stream the transformed data into BigQuery, the cloud-native data warehousing service, for immediate analysis via SQL or popular visualization tools.
From scenario: They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics.
Requirements for Game Analytics Platform
1. Dynamically scale up or down based on game activity
2. Process incoming data on the fly directly from the game servers
3. Process data that arrives late because of slow mobile networks
4. Allow SQL queries to access at least 10 TB of historical data
5. Process files that are regularly uploaded by users' mobile devices
6. Use only fully managed services
References: https://cloud.google.com/solutions/big-data/stream-analytics/


質問 # 180
Your company acquired a healthcare startup and must retain its customers' medical information for up to 4 more years, depending on when it was created. Your corporate policy is to securely retain this data, and then delete it as soon as regulations allow.
Which approach should you take?

  • A. Store the data in Google Drive and manually delete records as they expire.
  • B. Anonymize the data using the Cloud Data Loss Prevention API and store it indefinitely.
  • C. Store the data using the Cloud Storage and use lifecycle management to delete files when they expire.
  • D. Store the data in Cloud Storage and run a nightly batch script that deletes all expired datA.

正解：C

解説：
Reference:
https://cloud.google.com/storage/docs/lifecycle


質問 # 181
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 snapshot of the existing disk. Create a custom image from the snapshot. Create an autoscaled managed instance group from the custom image.
  • B. 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.
  • C. 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.
  • 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

解説：
Reference:
https://cloud.google.com/compute/docs/instance-templates/create-instance-templates


質問 # 182
You are using a single Cloud SQL instance to serve your application from a specific zone. You want to introduce high availability. What should you do?

  • A. Create a failover replica instance in a different region
  • B. Create a failover replica instance in the same region, but in a different zone
  • C. Create a read replica instance in the same region, but in a different zone
  • D. Create a read replica instance in a different region

正解：A


質問 # 183
For this question, refer to the Dress4Win case study.
At Dress4Win, an operations engineer wants to create a tow-cost solution to remotely archive copies of database backup files. The database files are compressed tar files stored in their current data center. How should he proceed?

  • A. Create a cron script using gsutil to copy the files to a Coldline Storage bucket.
  • B. Create a Cloud Storage Transfer Service job to copy the files to a Regional Storage bucket.
  • C. Create a Cloud Storage Transfer Service Job to copy the files to a Coldline Storage bucket.
  • D. Create a cron script using gsutil to copy the files to a Regional Storage bucket.

正解：A

解説：
Follow these rules of thumb when deciding whether to use gsutil or Storage Transfer Service:
* When transferring data from an on-premises location, use gsutil.
* When transferring data from another cloud storage provider, use Storage Transfer Service.
* Otherwise, evaluate both tools with respect to your specific scenario.
Use this guidance as a starting point. The specific details of your transfer scenario will also help you determine which tool is more appropriate


質問 # 184
You have an application that makes HTTP requests to Cloud Storage. Occasionally the requests fail with HTTP status codes of 5xx and 429.
How should you handle these types of errors?

  • A. Make sure the Cloud Storage bucket is multi-regional for geo-redundancy.
  • B. Monitor https://status.cloud.google.com/feed.atom and only make requests if Cloud Storage is not reporting an incident.
  • C. Use gRPC instead of HTTP for better performance.
  • D. Implement retry logic using a truncated exponential backoff strategy.

正解：D

解説：
Explanation/Reference: https://cloud.google.com/storage/docs/json_api/v1/status-codes


質問 # 185
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 Spanner
  • C. Cloud Datastore
  • D. Cloud Bigtable

正解：D

解説：
Explanation/Reference:
TerramEarth, A
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.
Company background
TerramEarth was 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, Terram Earth 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 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.
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 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. 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.


質問 # 186
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 host in Google Cloud Machine Learning (ML) Platform to make operational adjustments automatically
  • B. Capture all operating data, train machine learning models that identify ideal operations, and run locally 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. Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud Messaging (GCM) to make operational adjustments automatically

正解：A

解説：
Explanation/Reference: 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 # 187
Your customer is moving an existing corporate application to Google Cloud Platform from an on-premises data center. The business owners require minimal user disruption. There are strict security team requirements for storing passwords. What authentication strategy should they use?

  • A. Provision users in Google using the Google Cloud Directory Sync tool.
  • B. Use G Suite Password Sync to replicate passwords into Google.
  • C. Ask users to set their Google password to match their corporate password.
  • D. Federate authentication via SAML 2.0 to the existing Identity Provider.

正解：D

解説：
Explanation
https://cloud.google.com/solutions/authenticating-corporate-users-in-a-hybrid-environment


質問 # 188
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. Use a load testing tool to simulate the expected number of concurrent users and total requests to your application, and inspect the results.
  • B. 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.
  • C. Use Cloud Debugger in the development environment to understand the latency between the different microservices.
  • D. 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.

正解：A


質問 # 189
For this question, refer to the Dress4Win case study.
Dress4Win has end-to-end tests covering 100% of their endpoints. They want to ensure that the move to the cloud does not introduce any new bugs. Which additional testing methods should the developers employ to prevent an outage?

  • A. They should enable Google Stackdriver Debugger on the application code to show errors in the code.
  • B. They should add additional unit tests and production scale load tests on their cloud staging environment.
  • C. They should run the end-to-end tests in the cloud staging environment to determine if the code is working as intended.
  • D. They should add canary tests so developers can measure how much of an impact the new release causes to latency.

正解：B


質問 # 190
You have an application that makes HTTP requests to Cloud Storage. Occasionally the requests fail with HTTP status codes of 5xx and 429.
How should you handle these types of errors?

  • A. Make sure the Cloud Storage bucket is multi-regional for geo-redundancy.
  • B. Use gRPC instead of HTTP for better performance.
  • C. Monitor https://status.cloud.google.com/feed.atom and only make requests if Cloud Storage is not reporting
  • D. Implement retry logic using a truncated exponential backoff strategy.

正解：B

解説：
an incident.
Reference:
Reference https://cloud.google.com/storage/docs/json_api/v1/status-codes


質問 # 191
For this question, refer to the TerramEarth case study.
TerramEarth plans to connect all 20 million vehicles in the field to the cloud. This increases the volume to 20 million 600 byte records a second for 40 TB an hour. How should you design the data ingestion?

  • A. Vehicles write data directly to Google Cloud Pub/Sub.
  • B. Vehicles write data directly to GCS.
  • C. Vehicles stream data directly to Google BigQuery.
  • D. Vehicles continue to write data using the existing system (FTP).

正解：A

解説：
Explanation: Scale to hundreds of millions of messages per second and pay only for the resources you use. There are no partitions or local instances to manage, reducing operational overhead. Data is automatically and intelligently distributed across data centers over our unique, high-speed private network.
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.
https://cloud.google.com/pubsub/


質問 # 192
......


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