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| Certification Vendor: | Google Cloud |
|---|---|
| Exam Name: | Google Cloud Certified Professional Cloud Architect Exam |
| Exam Number: | Professional Cloud Architect |
| Exam Price: | $200 USD |
| Exam Duration: | 120 minutes |
| Exam Format: | Multiple choice, Multiple select, Case study-based questions |
| Passing Score: | Not publicly disclosed (scaled score; commonly reported passing threshold ~70%) |
| Certificate Validity Period: | 2 years |
| Available Languages: | English, Japanese, French, Spanish, Portuguese |
| Real Exam Qty: | Approximately 50–60 questions |
| Related Certifications: | Google Cloud Digital Leader Google Cloud Professional Data Engineer Google Cloud Professional Cloud Developer Google Cloud Associate Cloud Engineer Google Cloud Professional Cloud Security Engineer Google Cloud Professional Cloud Network Engineer |
| Recommended Training: | Coursera Google Cloud Professional Cloud Architect Training Google Cloud Skills Boost - Cloud Architect Learning Path |
| Exam Registration: | Google Cloud Certification Portal Professional Cloud Architect Exam Page |
| Sample Questions: | Google Professional-Cloud-Architect Sample Questions |
| Exam Way: | Online proctored or onsite test center exam |
| Pre Condition: | No formal prerequisites required, but Google recommends prior experience with Google Cloud and cloud architecture design. |
| Official Syllabus URL: | https://cloud.google.com/learn/certification/cloud-architect |
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There are no official requirements that the candidates for the Google Professional Cloud Architect certification need to satisfy. However, it is recommended that the applicants possess 3 or more years of industry experience, including at least 1 year of experience with designing and managing solutions using Google Cloud Platform. Their solid knowledge of the topics covered in the qualifying exam is also required.
The official website offers the candidates a wide range of training tools that they can use to build the required knowledge base for the qualifying test. The first step in your preparation must be a thorough review of the exam guide. This document contains a complete list of topics as well as case studies that may be included in the test. The familiarity with the exam topics will also help you assess the scope of work and structure the preparation process. Then, you can proceed with the Professional Cloud Architect learning path. This preparation option offers you online training, in-person classes, and hands-on labs to fully equip you for the upcoming certification exam. Besides that, the applicants can get an insight into the question formats and example content that may be covered in the test using the official sample questions. Additionally, the learners can enhance their knowledge of the exam topics by attending the dedicated webinar or exploring Google Cloud documentation.
NEW QUESTION # 56
An application development team believes their current logging tool will not meet their needs for their new cloud-based product. They want a bettor tool to capture errors and help them analyze their historical log dat a. You want to help them find a solution that meets their needs, what should you do?
Answer: D
Explanation:
Reference:
Help them define their requirements and assess viable logging tools. They know the requirements and the existing tools' problems. While it's true StackDriver Logging and Error Reporting possibly meet all their requirements, there might be other tools also meet their need. They need you to provide expertise to make assessment for new tools, specifically, logging tools that can "capture errors and help them analyze their historical log data".
References: https://cloud.google.com/logging/docs/agent/installation
NEW QUESTION # 57
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?
Answer: C
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.
References: https://cloud.google.com/dataproc/docs/resources/faq
NEW QUESTION # 58
You are working at an institution that processes medical data. You are migrating several workloads onto Google Cloud. Company policies require all workloads to run on physically separated hardware, and workloads from different clients must also be separated You created a sole-tenant node group and added a node for each client. You need to deploy the workloads on these dedicated hosts. What should you do?
Answer: C
Explanation:
Explanation
https://cloud.google.com/compute/docs/nodes/provisioning-sole-tenant-vms#provision_a_sole-tenant_vm
https://cloud.google.com/compute/docs/nodes/provisioning-sole-tenant-vms#gcloud_2 When you create a VM, you request sole-tenancy by specifying node affinity or anti-affinity, referencing one or more node affinity labels. You specify custom node affinity labels when you create a node template, and Compute Engine automatically includes some default affinity labels on each node. By specifying affinity when you create a VM, you can schedule VMs together on a specific node or nodes in a node group. By specifying anti-affinity when you create a VM, you can ensure that certain VMs are not scheduled together on the same node or nodes in a node group.
NEW QUESTION # 59
Your BigQuery project has several users. For audit purposes, you need to see how many queries each user ran in the last month.
Answer: D
Explanation:
https://cloud.google.com/bigquery/docs/access-control
NEW QUESTION # 60
You have been asked to select the storage system for the click-data of your company's large portfolio of websites. This data is streamed in from a custom website analytics package at a typical rate of 6,000 clicks per minute, with bursts of up to 8,500 clicks per second. It must been stored for future analysis by your data science and user experience teams. Which storage infrastructure should you choose?
Answer: C
Explanation:
Google Cloud Bigtable is a scalable, fully-managed NoSQL wide-column database that is suitable for both real-time access and analytics workloads.
Good for:
Low-latency read/write access
* High-throughput analytics
* Native time series support
* Common workloads:
IoT, finance, adtech
* Personalization, recommendations
* Monitoring
* Geospatial datasets
* Graphs
* Incorrect Answers:
C: Google Cloud Storage is a scalable, fully-managed, highly reliable, and cost-efficient object / blob store.
Is good for:
Images, pictures, and videos
* Objects and blobs
* Unstructured data
* D: Google Cloud Datastore is a scalable, fully-managed NoSQL document database for your web and mobile applications.
Is good for:
Semi-structured application data
* Hierarchical data
* Durable key-value data
* Common workloads:
* User profiles
* Product catalogs
* Game state
* References: https://cloud.google.com/storage-options/
NEW QUESTION # 61
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