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Google Professional-Cloud-Architect Exam Training Exam | Braindump Professional-Cloud-Architect Pdf–100% free

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Google Professional-Cloud-Architect Exam is a certification for professionals who want to demonstrate their expertise in designing, developing, and managing solutions on the Google Cloud Platform. It is designed for individuals who have experience in cloud architecture and are looking to expand their skill set. Professional-Cloud-Architect exam tests candidates on their ability to design and manage solutions on GCP, as well as their understanding of cloud architecture principles.

To become a Google Certified Professional - Cloud Architect (GCP), candidates must pass the Professional-Cloud-Architect exam. Google Certified Professional - Cloud Architect (GCP) certification is intended for individuals who have a deep understanding of GCP services and the ability to design, develop, and manage robust, secure, and scalable solutions. Google Certified Professional - Cloud Architect (GCP) certification exam covers a wide range of topics, including cloud architecture, infrastructure, data storage, networking, security, and application development. Google Certified Professional - Cloud Architect (GCP) certification demonstrates that a professional has the skills and knowledge required to design and implement cloud solutions using GCP, which can lead to better job opportunities and higher salaries in the cloud computing industry.

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Free PDF 2025 Google Professional-Cloud-Architect: Updated Google Certified Professional - Cloud Architect (GCP) Exam Training

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q241-Q246):

NEW QUESTION # 241
For this question, refer to the Dress4Win case study. Dress4Win is expected to grow to 10 times its size in 1 year with a corresponding growth in data and traffic that mirrors the existing patterns of usage. The CIO has set the target of migrating production infrastructure to the cloud within the next 6 months. How will you configure the solution to scale for this growth without making major application changes and still maximize the ROI?

A. Migrate RabbitMQ to Cloud Pub/Sub, Hadoop to BigQuery, and NAS to Compute Engine with Persistent Disk storage. Deploy Tomcat, and deploy Nginx using Deployment Manager.
B. Migrate the web application layer to App Engine, and MySQL to Cloud Datastore, and NAS to Cloud Storage. Deploy RabbitMQ, and deploy Hadoop servers using Deployment Manager.
C. Implement managed instance groups for Tomcat and Nginx. Migrate MySQL to Cloud SQL, RabbitMQ to Cloud Pub/Sub, Hadoop to Cloud Dataproc, and NAS to Compute Engine with Persistent Disk storage.
D. Implement managed instance groups for the Tomcat and Nginx. Migrate MySQL to Cloud SQL, RabbitMQ to Cloud Pub/Sub, Hadoop to Cloud Dataproc, and NAS to Cloud Storage.

Answer: C

NEW QUESTION # 242
Your company's test suite is a custom C++ application that runs tests throughout each day on Linux virtual machines. The full test suite takes several hours to complete, running on a limited number of on premises servers reserved for testing. Your company wants to move the testing infrastructure to the cloud, to reduce the amount of time it takes to fully test a change to the system, while changing the tests as little as possible. Which cloud infrastructure should you recommend?

A. Google App Engine with Google Stackdriver for logging
B. Google Compute Engine managed instance groups with auto-scaling
C. Google Cloud Dataproc to run Apache Hadoop jobs to process each test
D. Google Compute Engine unmanaged instance groups and Network Load Balancer

Answer: B

Explanation:
Explanation: https://cloud.google.com/compute/docs/instance-groups/

NEW QUESTION # 243
Your company is forecasting a sharp increase in the number and size of Apache Spark and Hadoop jobs being run on your local datacenter You want to utilize the cloud to help you scale this upcoming demand with the least amount of operations work and code change. Which product should you use?

A. Google Compute Engine
B. Google Cloud Dataproc
C. Google Cloud Dataflow
D. Google Container Engine

Answer: B

Explanation:
Google Cloud Dataproc is a fast, easy-to-use, low-cost and fully managed service that lets you run the Apache Spark and Apache Hadoop ecosystem on Google Cloud Platform. Cloud Dataproc provisions big or small clusters rapidly, supports many popular job types, and is integrated with other Google Cloud Platform services, such as Google Cloud Storage and Stackdriver Logging, thus helping you reduce TCO.

NEW QUESTION # 244
Your company provides a recommendation engine for retail customers. You are providing retail customers with an API where they can submit a user ID and the API returns a list of recommendations for that user. You are responsible for the API lifecycle and want to ensure stability for your customers in case the API makes backward-incompatible changes. You want to follow Google-recommended practices. What should you do?

A. Create an automated process to generate API documentation, and update the public API documentation as part of the CI/CD process when deploying an update to the API.
B. Use a versioning strategy for the APIs that increases the version number on every backward-incompatible change.
C. Use a versioning strategy for the APIs that adds the suffix "DEPRECATED" to the current API version number on every backward-incompatible change. Use the current version number for the new API.
D. Create a distribution list of all customers to inform them of an upcoming backward-incompatible change at least one month before replacing the old API with the new API.

Answer: D

NEW QUESTION # 245
You write a Python script to connect to Google BigQuery from a Google Compute Engine virtual machine. The script is printing errors that it cannot connect to BigQuery. What should you do to fix the script?

A. Run your script on a new virtual machine with the BigQuery access scope enabled
B. Create a new service account with BigQuery access and execute your script with that user
C. Install the latest BigQuery API client library for Python
D. Install the bq component for gccloud with the command gcloud components install bq.

Answer: A

Explanation:
The error is most like caused by the access scope issue. When create new instance, you have the default Compute engine default service account but most serves access including BigQuery is not enable. Create an instance Most access are not enabled by default You have default service account but don't have the permission (scope) you can stop the instance, edit, change scope and restart it to enable the scope access. Of course, if you Run your script on a new virtual machine with the BigQuery access scope enabled, it also works
https://cloud.google.com/compute/docs/access/service-accounts

NEW QUESTION # 246
......

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