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Google Google Cloud Architect Professional Exam Prep Course (Premium File)
AI-Powered Google Cloud Certified - Professional Cloud Architect Exam - Pass on Your First Try

Last updated on May 28, 2026

Google Cloud Architect Professional Practice Exam
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Google Cloud Architect Professional Package
Premium File (PDF): 340 Questions
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Duration & Delievery: Self Paced
Last Updated: 28-May-2026
Free Updates: 60 Days
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All Google Cloud Certified - Professional Cloud Architect certification learning material, study guide, training courses are created by a team of Google training experts. The Study Guide and .EXM training software files contain relevant Google Cloud Certified - Professional Cloud Architect content, labs, practice questions and explanation. This Google Cloud Architect Professional exam guide and training courses is based on the latest exam outlines available!

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Google Cloud Certified - Professional Cloud Architect Study package designed to help you confidently pass your exam.

The Google Cloud Architect Professional Exam Prep Features:

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Preparing and Passing the Google Cloud Architect Professional Exam

The Google Cloud Architect Professional Exam is a prestigious certification offered by Google that validates an individual's expertise in designing, managing, and implementing solutions on the Google Cloud Platform. This article will guide you through the process of preparing for and successfully passing the exam, providing you with actionable tips and up-to-date information.

Understanding the Exam

The Google Cloud Architect Professional Exam is designed to assess your knowledge and skills in various areas related to cloud architecture. It evaluates your ability to design, plan, and implement solutions using Google Cloud technologies and services. It also tests your understanding of best practices for security, scalability, and reliability.

Exam Details

  • Exam Name: Google Cloud Architect - Professional
  • Exam Code: GCP-CA
  • Duration: 2 hours
  • Format: Multiple choice and multiple select
  • Passing Score: 70%
  • Registration Fee: $200

Preparing for the Exam

1. Review the Exam Guide

Start your preparation by thoroughly reviewing the official Google Cloud Architect Professional Exam Guide. This guide provides detailed information about the topics covered in the exam, including the knowledge and skills you need to demonstrate.

2. Gain Hands-on Experience

One of the key aspects of the exam is practical experience with Google Cloud Platform. Ensure you have hands-on experience with various Google Cloud services, such as Compute Engine, App Engine, BigQuery, Cloud Storage, and Networking. Practice implementing solutions and solving real-world scenarios to strengthen your skills.

3. Study Relevant Documentation

Google provides comprehensive documentation and whitepapers on its website. Familiarize yourself with the latest documentation related to the exam topics, paying special attention to architectural patterns, best practices, and recommended solutions.

4. Explore Google Cloud Training

Google offers a range of training resources, including online courses, tutorials, and hands-on labs. Take advantage of these resources to deepen your understanding of Google Cloud Platform and enhance your practical skills. The official Google Cloud Training website is an excellent starting point for accessing these resources.

5. Join Study Groups and Forums

Engage with the Google Cloud community by participating in study groups and online forums. Discussing exam-related topics with peers and experts can provide valuable insights, tips, and clarification on complex concepts. The Google Cloud Community website and relevant social media groups can be great places to connect with fellow learners.

6. Take Practice Tests

Practice tests are essential for assessing your knowledge and identifying areas where you need further improvement. Google offers official practice exams that simulate the format and difficulty level of the actual exam. Taking these practice tests will help you familiarize yourself with the exam structure and boost your confidence.

Tips for Exam Success

1. Understand the Exam Domains

The Google Cloud Architect Professional Exam focuses on specific domains, such as designing and planning a cloud solution architecture, managing and provisioning the cloud infrastructure, and optimizing technical and business processes. Ensure you have a solid understanding of each domain and its associated topics.

2. Emphasize Real-world Scenarios

While studying, try to relate the concepts and technologies to real-world scenarios. Understanding how different services and features can be applied to solve practical problems will not only help you answer exam questions but also reinforce your understanding of the Google Cloud Platform.

3. Pay Attention to Security and Compliance

Security and compliance are critical aspects of cloud architecture. Make sure you have a good grasp of Google Cloud's security features, data protection mechanisms, and compliance standards. Familiarize yourself with best practices for securing cloud environments and data handling.

4. Time Management

The Google Cloud Architect Professional Exam is time-constrained, so effective time management is crucial. During practice tests, practice answering questions within the allotted time to improve your speed and accuracy. Avoid spending too much time on difficult questions, and mark them for review to revisit later if time permits.

5. Read Questions Carefully

Read each exam question carefully to understand what is being asked. Sometimes questions contain additional information that may influence your answer or provide hints. Pay attention to keywords and any specific requirements mentioned in the question.

6. Review and Revise

Before the exam, dedicate time to review and revise all the exam topics. Focus on areas where you feel less confident and reinforce your understanding through additional study materials. Make use of the official documentation, whitepapers, and any other relevant resources to solidify your knowledge.

By following these tips and dedicating sufficient time and effort to your preparation, you can increase your chances of passing the Google Cloud Architect Professional Exam and earning this prestigious certification.

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VirtuLearn AI

Question 17:

  • Correct answer: A Anomaly Detector.

  • Why: Anomaly Detector is designed to identify unusual values in time-series data. Your scenario has 100 machines × 50 sensors, generating minute-by-minute data, totaling 5,000 time-series. Anomaly Detector can process each time-series (or batches of series) to flag deviations that may indicate potential failures, which is exactly what you need for predictive maintenance.

  • Why not the others:
- Cognitive Search is for indexing and querying content, not for detecting anomalies in time-series data. - Form Recognizer extracts data from forms, not time-series sensor data. - Custom Vision analyzes images, not numeric sensor streams.
  • Practical note: with 5,000 time series, you’d typically run anomaly detection per series (potentially in parallel) and aggregate results to identify which machines/sensors warrant attention.

Singapore, Singapore

VirtuLearn AI

Question 12:

  • Correct answers: A, B, F.

  • Why:
- A. The index size will increase. Enabling CMK encryption adds encryption metadata and key management data, which increases index size. - B. Query times will increase. Encryption/decryption overhead and key retrieval can slow queries. - F. Azure Key Vault is required. CMK means you store/manage keys in Key Vault; it’s a billable, required service for CMK.
  • Why the other options are incorrect:
- C (self-signed X.509 certificate required) is not a requirement for CMK. - D (index size will decrease) and E (query times will decrease) contradict the expected impact of CMK.

Singapore, Singapore

VirtuLearn AI

GIF also we are using ?

  • No, GIF is not supported for Form Recognizer input. The allowed formats are JPG, PNG, PDF (text or scanned), or TIFF.
  • If you have GIFs, convert them to one of the supported formats (e.g., convert to JPG/PNG or PDF) before training or uploading.
  • Also ensure each file is under 50 MB and, when possible, use text-embedded PDFs to reduce errors.

Singapore, Singapore

VirtuLearn AI

Question 11:

  • Correct answers: A, C, F.

  • Why:
- Form Recognizer accepts documents in these formats: JPG, PNG, PDF (text or scanned), or TIFF. (TIFF is sometimes used in archival/scanned docs.) - Text-embedded PDFs are preferred because they minimize character extraction and location errors. - Training data must be under 50 MB per file.
  • So A, C, and F are the three files that meet these input requirements; the other options (B, D, E) likely fail one of the criteria (wrong format or too large). If you want, describe the formats of A, C, and F to confirm they meet all three criteria.

Singapore, Singapore

VirtuLearn AI

Question 10:
The correct answer is B: A new query key was generated.
Explanation:

  • The REST call to:
POST .../regenerateKey?api-version=2017-04-18 with body {"keyName": "Key2"} regenerates the specified account key.
  • Since you specified Key2, only the secondary key is regenerated; the primary key (Key1) remains unchanged.
  • This operation updates the Cognitive Services account keys within Azure, not anything in Azure Key Vault.
  • “Query key” refers to the key used to authorize API requests to the service (subscription key), so regenerating Key2 yields a new value for that key.

Singapore, Singapore

VirtuLearn AI

Why pull first, its create is first is it
Yes. The sequence is correct because you need a base image first.

  • Step 1: Pull the base container image (Anomaly Detector) to have a starting point.
  • Step 2: Create a Dockerfile to capture the exact changes you want (reproducible build).
  • Step 3: Build and push the customized image to Azure Container Registry (ACR).
  • Step 4: Distribute a docker run script to deploy the container on devices.

Why not start with the Dockerfile? You need the base image to reference in the FROM line, and you can only push a built image to ACR, not an unbuilt modification.

Singapore, Singapore

VirtuLearn AI

Question 5:

  • In Azure Resource Manager (ARM) REST APIs, creating or updating a resource is done with a PUT request to the resource’s exact URL (idempotent operation). This means you can repeatedly call the same PUT and it will create the resource if it doesn’t exist or update it if it does.
  • POST is used to create resources under a collection (without a predefined name), which would generate a new resource id each time and is not suitable when you need a single, known resource name and a single endpoint/key to consolidate billing and access.
  • For Question 5, you’re creating a new resource at a specific path (with a known resource name) to provide a single key/endpoint for multiple services. Therefore, PUT is the correct method.

If you’d like, I can outline the exact REST call structure (URL, headers, and body) for creating the Cognitive Services/related resource using PUT.

Singapore, Singapore

Smila Vincent

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Singapore, Singapore

VirtuLearn AI

Question 62:

  • Correct answer: D. Implement Jenkins on Compute Engine virtual machines.

  • Why this is the best choice:
- Since the app runs on GCP, hosting Jenkins on Compute Engine VMs keeps the CI/CD infrastructure in the same cloud environment, simplifying access to GCP services and credentials. - It reduces operational toil compared to managing Jenkins on local workstations or on-prem Kubernetes. - Cloud Functions cannot host a full Jenkins server (they’re serverless and not suited for long-running CI/CD tasks). - Using the Google Compute Engine plugin (google-compute-engine) lets Jenkins provision and manage GCE resources for build agents, enabling scalable, cloud-native pipelines.
  • How this supports security and streamline releases:
- Use GCP IAM/service accounts for least-privilege access, encrypt artifacts at rest, and place Jenkins behind private networking or IAP/VPN as needed. - Centralize credentials and secrets in Jenkins’ credentials store or Cloud KMS-backed solutions. - Automate deployments to GCP resources (App Engine, GKE, Cloud Run, Compute) via pipelines.
  • Why other options are less suitable:
- Local workstations: not scalable or secure for team CI/CD. - On-prem Kubernetes: adds management burden and detaches from GCP as the hosting environment. - Cloud Functions: not appropriate for a persistent Jenkins server.

Zionsville, United States

VirtuLearn AI

Establish if the solution satisfies the requirements. Your company has a Microsoft SQL Server Always On availability group configured on their Azure virtual machines (VMs). You need to configure an Azure internal load balancer as a listener for the availability group. Solution: You enable Floating IP. Does the solution meet the goal?

  • Yes.

  • Explanation: When using an Azure internal load balancer as a listener for a SQL Server Always On availability group, you must enable the Floating IP feature. This allows the internal listener IP to float to the active primary replica, ensuring the listener remains reachable and client connections are redirected correctly after failover. The Floating IP setting is required for stable listener behavior in AG configurations.

Johannesburg, South Africa