PCAGCP2025 최신 문제 업데이트

Google Professional Cloud Architect

Cloud Pass는 GCP PCA(Google Professional Cloud Architect) 시험 대비를 위한 실전 문제 풀이 앱입니다.

최신 시험 경향을 반영한 실제처럼 구성된 문제, 정확한 정답, 명확한 개념 설명을 제공합니다. 인터넷에 떠도는 검증되지 않은 GCP PCA 덤프 대신, Cloud Pass에서는 최근 출제 경향 기반의 연습 문제와 상세 해설을 통해 효율적으로 학습하고 점수를 끌어올릴 수 있습니다. 또한 Google Professional Cloud Architect(PCA)뿐만 아니라 AWS · GCP 자격증 24종을 한 앱에서 모두 학습할 수 있어 클라우드 자격증을 준비하는 수험생에게 최적화되어 있습니다.

📘199개의 문제를 앱에서 풀어보세요

⭐ 실제 사용자들의 PCA 합격 후기

Cloud Pass로 합격한 사용자들의 생생한 경험

Very similar to the real exam

2025-11-21

Many of the scenario patterns I saw on Cloud Pass showed up in the actual PCA exam. The explanations were detailed, which helped strengthen my weak areas. I’ll definitely use this app again for other GCP exams.

E**********

학습 기간: 1 month

합격!

2025-11-19

실제 시험 문제하고 유사했던게 15개 이상 나온거 같아요! 굿굿

김

김**

학습 기간: 1 month

합격했어요

2025-11-17

앱 너무 좋네요

박

박**

학습 기간: 1 month

I passed!

2025-11-15

These questions forced me to deeply understand GCP networking, IAM, storage trade-offs, and high-availability design. After a month of consistent practice, I finally passed my PCA exam. Amazing app!

D***********

학습 기간: 2 weeks

Passed on My First Attempt

2025-11-08

I passed on the first try. The practice questions were tough but very close to the real exam. The explanations helped me understand why each answer was correct. Highly recommended.

M*********

학습 기간: 1 month

Clear Explanations and Great Coverage

2025-11-07

The practice questions covered all key PCA domains: IAM, VPC design, hybrid connectivity, storage planning, and reliability. The explanations were concise and easy to understand. Great app for serious learners.

O***********

학습 기간: 1 month

📝 199개의 시험 문제

2025 최신 업데이트된 문제들을 확인해보세요

Question 1

A global logistics firm operates 650 smart loading bays across 8 distribution centers on 3 continents, and each bay has a beam-break sensor that reports its state once per second; each event contains only a sensor ID and several discrete status flags, and analysts must correlate this data with driver account records, scheduled dock assignments, and warehouse location metadata to run join-heavy queries and produce operational reports; which database type should you use?

Question 2

A ticketing company needs to expose a public HTTPS webhook API written in Go 1.20 that is idle most of the day but can surge from ~0 to 10,000 requests per minute within 90 seconds when major sales go live; the service must maintain at least 99.95% availability during spikes, support request timeouts up to 60 seconds, auto-scale without pre-provisioning capacity, and minimize operational overhead by avoiding server, cluster, or OS management—what deployment approach should you recommend?

Question 3

Your media analytics firm stores 150 TB of sensitive video feature vectors on regional SSD persistent disks attached to a Dataproc cluster in us-central1. For regulatory reasons, you must be able to rotate the encryption key protecting the data at rest on these disks at least every 90 days without manually re-encrypting data or changing Spark jobs. Pipelines must continue to run with minimal operational overhead and no plaintext copies written to intermediate storage. You want to follow Google-recommended practices for security. What should you do?

Question 4

Cinemetrix, a media analytics firm, enabled Google Workspace (domain: cinemetrix.com) last week and created a Google Cloud Organization; they currently have 85 projects across 6 folders. The security office now mandates that, effective immediately, no principals from outside cinemetrix.com may be granted any IAM role on any project, folder, or resource within the Organization. The control must be enforced centrally at the Organization level, automatically apply to newly created projects, work without custom scripts or periodic jobs, take effect within 30 minutes, and must not break existing or future service-account-based workloads. What should you do?

Question 5

Your retail analytics team needs to run 40 legacy Hadoop MapReduce jobs on Google Cloud for weekly batch processing without changing any job code or deployment scripts; they want to minimize both compute cost and infrastructure management effort; each batch runs 3–6 hours and the pipelines can tolerate up to 20% worker loss without failing. What should you do?