GOOGLE CERTIFIED PROFESSIONAL - CLOUD ARCHITECT (GCP) STUDY MATERIAL & PROFESSIONAL-CLOUD-ARCHITECT TORRENT PDF & GOOGLE CERTIFIED PROFESSIONAL - CLOUD ARCHITECT (GCP) TRAINING DUMPS

Google Certified Professional - Cloud Architect (GCP) study material & Professional-Cloud-Architect torrent pdf & Google Certified Professional - Cloud Architect (GCP) training dumps

Google Certified Professional - Cloud Architect (GCP) study material & Professional-Cloud-Architect torrent pdf & Google Certified Professional - Cloud Architect (GCP) training dumps

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Exam Domains Overview

The entire syllabus is based on six domains and each tries to educate the learner about various Google Cloud technologies. They are disclosed below in detail:

Section #1. Designing and strategy-making for the Cloud Solution Architecture

Designing a Google Cloud solution as per business and technical needs, handling the cost optimization, data movement, observability, and compliance are some of the most talked-about topics under this module.

The applicants should also demonstrate their expertise regarding the concepts like architecting the storage, network, and compute solutions or resources, multi-cloud or on-premises integration, and fulfilling & monitoring the compute needs of the platform products, picking-up right data processing and related technologies.

Google offers various learning resources and training programs to help candidates prepare for the GCP certification exam. These resources include online courses, hands-on labs, and practice exams. Professional-Cloud-Architect Exam is designed to be challenging, and candidates need to have a deep understanding of GCP technologies and architecture to pass.

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q113-Q118):

NEW QUESTION # 113
For this question, refer to the TerramEarth case study.
TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US. Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles.
You want to run this job on all the data. What is the most cost-effective way to run this job?

  • A. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a multi region bucket and use a Dataproc cluster to finish the job.
  • B. Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job.
  • C. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a regional bucket and use a Cloud Dataproc cluster .....
  • D. Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job.

Answer: A

Explanation:
Explanation
Storageguarantees 2 replicates which are geo diverse (100 miles apart) which can get better remote latency and availability.
More importantly, is that multiregional heavily leverages Edge caching and CDNs to provide the content to the end users.
All this redundancy and caching means that Multiregional comes with overhead to sync and ensure consistency between geo-diverse areas. As such, it's much better for write-once-read-many scenarios. This means frequently accessed (e.g. "hot" objects) around the world, such as website content, streaming videos, gaming or mobile applications.
References:
https://medium.com/google-cloud/google-cloud-storage-what-bucket-class-for-the-best-performance-5c847ac8f9


NEW QUESTION # 114
A lead software engineer tells you that his new application design uses websockets and HTTP sessions that are not distributed across the web servers. You want to help him ensure his application will run property on Google Cloud Platform. What should you do?

  • A. Help the engineer redesign the application to use a distributed user session service that does not rely on websockets and HTTP sessions.
  • B. Help the engineer to convert his websocket code to use HTTP streaming.
  • C. Meet with the cloud operations team and the engineer to discuss load balancer options.
  • D. Review the encryption requirements for websocket connections with the security team.

Answer: C

Explanation:
Google Cloud Platform (GCP) HTTP(S) load balancing provides global load balancing for HTTP(S) requests destined for your instances.
The HTTP(S) load balancer has native support for the WebSocket protocol.


NEW QUESTION # 115
You have developed an application using Cloud ML Engine that recognizes famous paintings from uploaded images. You want to test the application and allow specific people to upload images for the next 24 hours.
Not all users have a Google Account. How should you have users upload images?

  • A. Have users upload the images to Cloud Storage. Protect the bucket with a password that expires after
    24 hours.
  • B. Create an App Engine web application where users can upload images for the next 24 hours.
    Authenticate users via Cloud Identity.
  • C. Create an App Engine web application where users can upload images. Configure App Engine to disable the application after 24 hours. Authenticate users via Cloud Identity.
  • D. Have users upload the images to Cloud Storage using a signed URL that expires after 24 hours.

Answer: D


NEW QUESTION # 116
Your customer runs a web service used by e-commerce sites to offer product recommendations to users. The company has begun experimenting with a machine learning model on Google Cloud Platform to improve the quality of results.
What should the customer do to improve their model's results over time?

  • A. Export Cloud Machine Learning Engine performance metrics from Stackdriver to BigQuery, to be used to analyze the efficiency of the model.
  • B. Monitor Compute Engine announcements for availability of newer CPU architectures, and deploy the model to them as soon as they are available for additional performance.
  • C. Build a roadmap to move the machine learning model training from Cloud GPUs to Cloud TPUs, which offer better results.
  • D. Save a history of recommendations and results of the recommendations in BigQuery, to be used as training data.

Answer: D

Explanation:
Explanation
https://cloud.google.com/solutions/building-a-serverless-ml-model


NEW QUESTION # 117
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.

Answer: C

Explanation:
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/


NEW QUESTION # 118
......

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