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Google Professional-Cloud-Architect 시험은 GCP를 사용하여 견고하고 안전하며 확장 가능한 클라우드 아키텍처 솔루션을 설계, 개발 및 관리하는 개인의 능력을 검증하는 Google에서 제공하는 자격증 시험입니다. 시험 형식은 객관식과 시나리오 기반 문제로 구성되며, 후보자들은 클라우드 컴퓨팅 개념과 GCP 서비스 및 도구에 대한 강력한 이해력이 필요합니다. 이 자격증을 취득하면 GCP에 대한 전문 지식을 증명하며 특히 클라우드 아키텍트, 클라우드 엔지니어 및 솔루션 아키텍트에게 매우 가치 있습니다.

최신 Google Cloud Certified Professional-Cloud-Architect 무료샘플문제 (Q67-Q72):

질문 # 67
You are planning to migrate your on-premises compute and SAP workloads to Google Cloud.
You want to follow Google-recommended practices to quickly create a cost estimate for running these workloads in Google Cloud. What should you do?

A. Gather data about your current environment, and leverage Google Cloud Migration Center to generate a cost estimate.
B. Use the Google Cloud pricing calculator, and input the estimated resource to generate a cost estimate.
C. Engage with a Google Cloud partner to perform a comprehensive assessment and provide a customized cost estimate.
D. Leverage Cloud Asset Inventory to gather data and generate a cost estimate.

정답：A

설명：
Google Cloud Migration Center is the recommended tool for quickly estimating migration costs. It allows you to collect on-premises infrastructure data, analyze workload characteristics, and generate automated cost estimates for running those workloads (including SAP) on Google Cloud. This approach provides accurate, data-driven insights aligned with Google best practices.

질문 # 68
You have an application that will run on Compute Engine. You need to design an architecture that takes into account a disaster recovery plan that requires your application to fail over to another region in case of a regional outage. What should you do?

A. Deploy the application on two Compute Engine instance groups, each in separate project and a different region. Use the first instance group to server traffic, and use the HTTP load balancing service to fail over to the standby instance in case of a disaster.
B. Deploy the application on a Compute Engine instance. Use the instance to serve traffic, and use the HTTP load balancing service to fail over to an instance on your premises in case of a disaster.
C. Deploy the application on two Compute Engine instances in the same project but in a different region.
Use the first instance to serve traffic, and use the HTTP load balancing service to fail over to the standby instance in case of a disaster.
D. Deploy the application on two Compute Engine instance groups, each in the same project but in a different region. Use the first instance group to serve traffic, and use the HTTP load balancing service to fail over to the standby instance group in case of a disaster.

정답：B

질문 # 69
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.

정답：C

설명：
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.

질문 # 70
You are building a continuous deployment pipeline for a project stored in a Git source repository and want to ensure that code changes can be verified before deploying to production. What should you do?

A. Use Spinnaker to deploy builds to production using the red/black deployment strategy so that changes can easily be rolled back.
B. Use Spinnaker to deploy builds to production and run tests on production deployments.
C. Use Jenkins to monitor tags in the repository. Deploy staging tags to a staging environment for testing.
After testing, tag the repository for production and deploy that to the production environment.
D. Use Jenkins to build the staging branches and the master branch. Build and deploy changes to production for 10% of users before doing a complete rollout.

정답：C

설명：
The tagging is a best practice that is recommended on Jenkins/Spinnaker to deploy the right code and prevent accidentally (or intentionally) push of wrong code to production environments.
https://stackify.com/continuous-delivery-git-jenkins/

질문 # 71
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 A
B. Option C
C. Option B
D. Option D

정답：A

설명：
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/

질문 # 72
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