Professional-Cloud-Architect試験の準備方法|真実的なProfessional-Cloud-Architect合格体験談試験|一番優秀なGoogle Certified Professional - Cloud Architect (GCP)最新受験攻略
最新受験攻略)
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Google Professional-Cloud-Architect Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|
| Managing and provisioning solution infrastructure | 15% | - Managing storage and data services
- 1. Cloud Storage, Filestore, Persistent Disk management
- 2. Database deployment, replication, and backup
- Configuring network topologies and connectivity
- 1. Load balancing and CDN configuration
- 2. VPC design, peering, and hybrid connectivity
- Provisioning and managing compute resources
- 1. Auto-scaling and resource management
- 2. VMs, GKE, App Engine, Cloud Run deployment and management
|
| Managing implementation | 12.5% | - Guiding development and deployment teams
- 1. Application and infrastructure deployment strategies
- 2. CI/CD pipelines and automation
- Testing and validating solutions
- 1. Disaster recovery and failover testing
- 2. Functional, performance, and security testing
- Using Google Cloud tools and APIs programmatically
- 1. Infrastructure as Code (Terraform, Deployment Manager)
- 2. Cloud SDK, Cloud Shell, and Cloud Code
|
| Analyzing and optimizing technical and business processes | 15% | - Optimizing cost and resource efficiency
- 1. Resource right-sizing and usage monitoring
- 2. Committed use discounts and pricing models
- Streamlining operational workflows
- 1. Change management and incident response
- 2. Stakeholder communication and alignment
- Improving reliability and performance
- 1. Latency reduction and throughput optimization
- 2. SLO, SLA, and error budgeting
|
| Designing for security and compliance | 17.5% | - Implementing identity and access management
- 1. IAM roles, permissions, and service accounts
- 2. Organizational policies and resource hierarchy
- Securing data and communications
- 1. Key management and secret security
- 2. Encryption at rest and in transit
- Enforcing compliance and governance
- 1. VPC Service Controls and security perimeters
- 2. Security controls, auditing, and logging
|
| Ensuring solution and operations excellence | 12.5% | - Implementing monitoring, logging, and observability
- 1. Alerting, dashboarding, and root cause analysis
- 2. Cloud Monitoring, Logging, and Error Reporting
- Planning for continuous improvement
- 1. Feedback loops and optimization cycles
- 2. Technology updates and architecture evolution
- Applying Well-Architected Framework principles
- 1. Operational excellence, reliability, security, cost, and performance pillars
|
| Designing and planning a cloud solution architecture | 25% | - Designing cloud solution infrastructure aligned with business requirements
- 1. Scalability, high availability, and fault tolerance design
- 2. Compliance and regulatory requirements consideration
- 3. Cost optimization strategies
- Planning cloud migration and hybrid/multi-cloud environments
- 1. Data transfer and synchronization
- 2. Interoperability and integration design
- 3. Migration planning and execution
- Evaluating and selecting Google Cloud services
- 1. Serverless and managed service adoption
- 2. Compute, storage, database, and networking service selection
|
>> Professional-Cloud-Architect合格体験談 <<
信頼的なProfessional-Cloud-Architect合格体験談一回合格-権威のあるProfessional-Cloud-Architect最新受験攻略
PassTest市場調査によると、Professional-Cloud-Architect試験の準備をしている多くの人が、試験に関する最新情報を入手したいことがわかっています。 すべての候補者の要件を満たすために、私たちはあなたを助けるためにそのような高品質のProfessional-Cloud-Architect学習資料をまとめました。 当社Googleの製品はお客様にとって非常に便利であり、Professional-Cloud-Architect試験問題よりも優れたGoogle Certified Professional - Cloud Architect (GCP)教材を見つけることはできないと考えられています。 私たちの学習教材を学ぶために数時間を費やすつもりなら、短時間で試験に合格します。 次に、Professional-Cloud-Architectテストの質問を紹介します。
Google Certified Professional - Cloud Architect (GCP) 認定 Professional-Cloud-Architect 試験問題 (Q249-Q254):
質問 # 249
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.
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:
https://cloud.google.com/solutions/data-lifecycle-cloud-platform
https://cloud.google.com/solutions/designing-connected-vehicle-platform
質問 # 250
You set up an autoscaling instance group to serve web traffic for an upcoming launch. After configuring the instance group as a backend service to an HTTP(S) load balancer, you notice that virtual machine (VM) instances are being terminated and re-launched every minute. The instances do not have a public IP address. You have verified the appropriate web response is coming from each instance using the curl command. You want to ensure the backend is configured correctly. What should you do?
- A. Assign a public IP to each instance and configure a firewall rule to allow the load balancer to reach the instance public IP.
- B. Create a tag on each instance with the name of the load balancer. Configure a firewall rule with the name of the load balancer as the source and the instance tag as the destination.
- C. Ensure that a firewall rule exists to allow load balancer health checks to reach the instances in the instance group.
- D. Ensure that a firewall rule exists to allow source traffic on HTTP/HTTPS to reach the load balancer.
正解:C
質問 # 251
A news feed web service has the following code running on Google App Engine. During peak load, users report that they can see news articles they already viewed.
What is the most likely cause of this problem?

- A. The session variable is being overwritten in Cloud Datastore
- B. The URL of the API needs to be modified to prevent caching
- C. The session variable is local to just a single instance
- D. The HTTP Expires header needs to be set to -1 stop caching
正解:C
質問 # 252
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 Bigtable
- B. Google Cloud Storage
- C. Google Cloud SQL
- D. Google cloud Datastore
正解:B
質問 # 253
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 continue to write data using the existing system (FTP)
- B. Vehicles write data directly to GCS
- C. Vehicles stream data directly to Google BigQuery
- D. Vehicles write data directly to Google Cloud Pub/Sub
正解:C
解説:
Streamed data is available for real-time analysis within a few seconds of the first streaming insertion into a table.
Instead of using a job to load data into BigQuery, you can choose to stream your data into BigQuery one record at a time by using the tabledata().insertAll() method. This approach enables querying data without the delay of running a load job.
Reference: https://cloud.google.com/bigquery/streaming-data-into-bigquery
質問 # 254
......
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