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Before attending the exam for the Google Professional Cloud Architect certification, the individuals need to develop a good comprehension of its topics. The syllabus of the test is divided into five sections, each including several subtopics. The detailed outline of the exam domains can be viewed on the vendor’s website. A brief overview of the content is provided below:

Ensuring of Solution & Operations Reliability
To tackle the questions related to the last domain, the applicants are required to be conversant with monitoring/logging/profiling/alerting solutions. They should know how to perform deployment & release management as well as evaluate quality control measures. IN addition, the specialists must be able to assist with the support of deployed solutions.
Security & Compliance Design
The examinees will be evaluated based on their competency in designing for security, including such considerations as identity & access management (IAM), resource hierarchy, data security, separation of duties (SoD), security controls, remote access, as well as managing customer-managed encryption keys using Cloud Key Management Service. Another subtopic covered in this section is designing for compliance. This involves the knowledge of legislation, commercial, industry certifications, as well as audits.
Management & Provisioning of Solution Infrastructure
In the framework of this topic, the test takers will be asked to showcase their ability to configure network topologies, individual storage systems, as well as compute systems.

During the exam for the Google Professional Cloud Architect certification, some of the questions will refer you to a case study describing a fictitious business & solution concept. These case studies are designed to provide the students with additional context to help them choose the right answer(s). The candidates can review the examples of possible case studies in the official guide.

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Google Professional-Cloud-Architect (GCP) exam is a certification program designed to assess the skills and knowledge of professionals who want to work with Google Cloud Platform (GCP). Google Certified Professional - Cloud Architect (GCP) certification is intended to demonstrate that an individual has the expertise and experience to design, develop, and manage scalable, secure, and reliable cloud solutions using GCP technologies.

Google Professional-Cloud-Architect Certification is recognized globally and is highly valued by organizations that want to build and implement cloud solutions using Google Cloud Platform. It is an excellent way for professionals to showcase their expertise in cloud architecture and design and demonstrate their commitment to continuous learning and professional development.

Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q255-Q260):

NEW QUESTION # 255
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 Container Engine
C. Google Cloud Dataproc
D. Google Cloud Dataflow

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 # 256
You are working at a sports association whose members range in age from 8 to 30. The association collects a large amount of health data, such as sustained injuries. You are storing this data in BigQuery. Current legislation requires you to delete such information upon request of the subject. You want to design a solution that can accommodate such a request. What should you do?

A. Use a unique identifier for each individual. Upon a deletion request, delete all rows from BigQuery with this identifier.
B. Use a unique identifier for each individual. Upon a deletion request, overwrite the column with the unique identifier with a salted SHA256 of its value.
C. When ingesting new data in BigQuery, run the data through the Data Loss Prevention (DLP) API to identify any personal information. As part of the DLP scan, save the result to Data Catalog. Upon a deletion request, query Data Catalog to find the column with personal information.
D. Create a BigQuery view over the table that contains all data. Upon a deletion request, exclude the rows that affect the subject's data from this view. Use this view instead of the source table for all analysis tasks.

Answer: A

Explanation:
Current legislation requires you to delete "SUCH" information upon request of the subject. " So from that point of view the question is not to delete the entire user records but specific data related to personal health data. With DLP you can use InfoTypes and InfoType detectors to specifically scan for those entries and how to act upon them (link https://cloud.google.com/dlp/docs/concepts-infotypes)
https://cloud.google.com/dlp#section-6

NEW QUESTION # 257
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 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.
B. 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.
C. Use a versioning strategy for the APIs that increases the version number on every backward-incompatible change.
D. 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.

Answer: C

NEW QUESTION # 258
Your company has successfully migrated to the cloud and wants to analyze their data stream to optimize operations. They do not have any existing code for this analysis, so they are exploring all their options.
These options include a mix of batch and stream processing, as they are running some hourly jobs and live- processing some data as it comes in.
Which technology should they use for this?

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

Answer: B

Explanation:
Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes with equal reliability and expressiveness -- no more complex workarounds or compromises needed.
Reference: https://cloud.google.com/dataflow/

NEW QUESTION # 259
A development manager is building a new application. He asks you to review his requirements and identify what cloud technologies he can use to meet them. The application must:
1. Be based on open-source technology for cloud portability
2. Dynamically scale compute capacity based on demand
3. Support continuous software delivery
4. Run multiple segregated copies of the same application stack
5. Deploy application bundles using dynamic templates
6. Route network traffic to specific services based on URL
Which combination of technologies will meet all of his requirements?

A. Google Kubernetes Engine, Jenkins, and Helm
B. Google Kubernetes Engine and Cloud Load Balancing
C. Google Kubernetes Engine and Cloud Deployment Manager
D. Google Kubernetes Engine, Jenkins, and Cloud Load Balancing

Answer: D

Explanation:
Jenkins is an open-source automation server that lets you flexibly orchestrate your build, test, and deployment pipelines. Kubernetes Engine is a hosted version of Kubernetes, a powerful cluster manager and orchestration system for containers.
When you need to set up a continuous delivery (CD) pipeline, deploying Jenkins on Kubernetes Engine provides important benefits over a standard VM-based deployment Incorrect Answers:
A: Helm is a tool for managing Kubernetes charts. Charts are packages of pre-configured Kubernetes resources.
Use Helm to:
* Find and use popular software packaged as Kubernetes charts
* Share your own applications as Kubernetes charts
* Create reproducible builds of your Kubernetes applications
* Intelligently manage your Kubernetes manifest files
* Manage releases of Helm packages
Reference: https://cloud.google.com/solutions/jenkins-on-kubernetes-engine

NEW QUESTION # 260
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