Professional-Cloud-Architect시험패스인증덤프자료 & Professional-Cloud-Architect최신시험공부자료
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2026 PassTIP 최신 Professional-Cloud-Architect PDF 버전 시험 문제집과 Professional-Cloud-Architect 시험 문제 및 답변 무료 공유: https://drive.google.com/open?id=1HBcVkU296an7z6LB45qoZ5NpjG7wAsIS
영어가 서툴러 국제승인 인기 IT인증자격증 필수시험 과목인Google인증 Professional-Cloud-Architect시험에 도전할 엄두도 낼수 없다구요? 이런 생각은 이글을 보는 순간 버리세요. Google인증 Professional-Cloud-Architect시험을 패스하려면PassTIP가 고객님의 곁을 지켜드립니다. PassTIP의Google인증 Professional-Cloud-Architect덤프는 Google인증 Professional-Cloud-Architect시험패스 특효약입니다. 영어가 서툴러고 덤프범위안의 문제만 기억하면 되기에 영어로 인한 문제는 걱정하지 않으셔도 됩니다.
PassTIP 의 Google인증 Professional-Cloud-Architect시험에 도전장을 던지셨나요? 현황에 만족하지 않고 열심히 하는 모습에 박수를 보내드립니다. Google인증 Professional-Cloud-Architect시험을 학원등록하지 않고 많은 공부자료 필요없이PassTIP 에서 제공해드리는 Google인증 Professional-Cloud-Architect덤프만으로도 가능합니다. 수많은 분들이 검증한Google인증 Professional-Cloud-Architect덤프는 시장에서 가장 최신버전입니다.가격도 친근하구요.
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시험패스 가능한 Professional-Cloud-Architect시험패스 인증덤프자료 공부자료
학원다니면서 많은 지식을 장악한후Google Professional-Cloud-Architect시험보시는것도 좋지만 회사다니느랴 야근하랴 시간이 부족한 분들은Google Professional-Cloud-Architect덤프만 있으면 엄청난 학원수강료 필요없이 20~30시간의 독학만으로도Google Professional-Cloud-Architect시험패스가 충분합니다. 또한 취업생분들은 우선 자격증으로 취업문을 두드리고 일하면서 실무를 익혀가는방법도 좋지 않을가 생각됩니다.
Google Professional-Cloud-Architect 시험은 후보자의 구글 클라우드 플랫폼 솔루션을 디자인하고 구현할 수 있는 능력을 검증하는 자격증 시험입니다. 이 시험은 구글 클라우드 플랫폼을 사용하여 클라우드 솔루션을 디자인, 개발 및 관리하는 전문가를 대상으로합니다. 이 시험은 또한 클라우드 아키텍처 전문 지식을 검증하고 클라우드 컴퓨팅에서 경력을 쌓고자하는 개인에게 적합합니다.
최신 Google Cloud Certified Professional-Cloud-Architect 무료샘플문제 (Q97-Q102):
질문 # 97
You are working with a data warehousing team that performs data analysis. The team needs to process data from external partners, but the data contains personally identifiable information (PlI). You need to process and store the data without storing any of the Pll data. What should you do?
- A. Create a Dataflow pipeline to retrieve the data from the external sources. As part of the pipeline use the Cloud Data Loss Prevention (Cloud DLP) API to remove any Pll data Store the result in BigQuery
- B. Create a Dataflow pipeline to retrieve the data from the external sources. As part of the pipeline store all non-PII data in BigQuery and store all Pll data in a Cloud Storage bucket that has a retention policy set.
- C. Ask the external partners to upload an data on Cloud Storage Configure Bucket Lock for the bucket Create a Dataflow pipeline to read the data from the bucket As part of the pipeline, use the Cloud Data Loss Prevention (Cloud DIP) API to remove any Pll data Store the result in BigQuery
- D. Ask the external partners to import ail data in your BigQuery dataset Create a dataflow pipeline to copy the data into a new table As part of the Dataflow bucket skip all data in columns that have Pll data
정답:A
설명:
Explanation
Create a Dataflow pipeline to retrieve the data from the external sources, he did not specify the way he is going to create it, it might be a pub/sub or external table or whatever.
질문 # 98
Your company has an enterprise application running on Compute Engine that requires high availability and high performance. The application has been deployed on two instances in two zones in the same region in active-passive mode. The application writes data to a persistent disk.
In the case of a single zone outage, that data should be immediately made available to the other instance in the other zone. You want to maximize performance while minimizing downtime and data loss. What should you do?
- A. 1. Attach a persistent SSD disk to the first instance.
2. Create a snapshot every hour.
3. In case of a zone outage, recreate a persistent SSD disk in the second instance where data is coming from the created snapshot. - B. 1. Attach a regional SSD persistent disk to the first instance.
2. In case of a zone outage, force-attach the disk to the other instance. - C. 1. Attach a local SSD to the first instance disk.
2. Execute an rsync command every hour where the target is a persistent SSD disk attached to the second instance.
3. In case of a zone outage, use the second instance. - D. 1. Create a Cloud Storage bucket.
2. Mount the bucket into the first instance with gcs-fuse.
3. In case of a zone outage, mount the Cloud Storage bucket to the second instance with gcs- fuse.
정답:B
설명:
https://cloud.google.com/compute/docs/disks/repd-failover
질문 # 99
Your office is connected to GCP via a VPN connection. How can you increase the speed of your VPN connection, assuming that your office Internet is not the bottleneck?
- A. Submit request to increase bandwidth quota
- B. Apply for a dedicated interconnect option
- C. Create an additional VPN tunnel
- D. Enable high speed routing in your VPN settings
정답:C
설명:
A - Apply for a dedicated interconnect option. A dedicated interconnect will also increase speeds, however the question asked how to speed up your VPN connection, not create a new type of connection.
C (Correct answer) - Create an additional VPN tunnel. Each VPN tunnel has a max speed of 1.5 Gbps. However, you can create multiple VPN tunnels to increase bandwidth.
Answer B and D either are not applicable or feature doesn't not exist.
질문 # 100
Your organization requires that metrics from all applications be retained for 5 years for future analysis in possible legal proceedings. Which approach should you use?
- A. Configure Stackdriver Monitoring for all Projects with the default retention policies.
- B. Grant the security team access to the logs in each Project.
- C. Configure Stackdriver Monitoring for all Projects, and export to Google Cloud Storage.
- D. Configure Stackdriver Monitoring for all Projects, and export to BigQuery.
정답:C
설명:
Overview of storage classes, price, and use cases https://cloud.google.com/storage/docs/storage-classes Why export logs? https://cloud.google.com/logging/docs/export/ StackDriver Quotas and Limits for Monitoring https://cloud.google.com/monitoring/quotas The BigQuery pricing. https://cloud.google.com/bigquery/pricing
질문 # 101
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
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. Have your engineers inspect the data for patterns, and then create an algorithm with rules that make operational adjustments automatically.
- B. 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.
- C. Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud Messaging (GCM) to make operational adjustments automatically.
- D. Capture all operating data, train machine learning models that identify ideal operations, and run locally to make operational adjustments automatically.
정답:B
설명:
https://cloud.google.com/customers/ocado/
질문 # 102
......
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