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Google Professional-Cloud-Architect Certification is designed for individuals who are seeking to demonstrate their expertise in designing, developing, and managing robust, secure, scalable, and highly available cloud solutions using Google Cloud Platform (GCP). Google Certified Professional - Cloud Architect (GCP) certification exam is ideal for cloud architects, solution architects, and IT professionals who work with GCP on a regular basis.

Managing Implementation

Interact with Google Cloud with the use of GCP SDK: this requires the test takers’ understanding of Google Cloud Shell and local installation.
Advice development and operation team to ensure the successful deployment of solutions: the areas of focus include application development; AIP best practices; data and system migration tool; testing framework;

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Preparation Process

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.

Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q298-Q303):

NEW QUESTION # 298
Your architecture calls for the centralized collection of all admin activity and VM system logs within your project. How should you collect these logs from both VMs and services?

A. All admin and VM system logs are automatically collected by Stackdriver.
B. Launch a custom syslogd compute instance and configure your GCP project and VMs to forward all logs to it.
C. Stackdriver automatically collects admin activity logs for most services. The Stackdriver Logging agent must be installed on each instance to collect system logs.
D. Install the Stackdriver Logging agent on a single compute instance and let it collect all audit and access logs for your environment.

Answer: C

Explanation:
Admin and event logs are configured by default. VM System logs require a logging agent to be configured.
https://cloud.google.com/logging/docs/agent/
https://cloud.google.com/logging/docs/agent/logging/installation#before_you_begin

NEW QUESTION # 299
For this question, refer to the Helicopter Racing League (HRL) case study. Your team is in charge of creating a payment card data vault for card numbers used to bill tens of thousands of viewers, merchandise consumers, and season ticket holders. You need to implement a custom card tokenization service that meets the following requirements:
* It must provide low latency at minimal cost.
* It must be able to identify duplicate credit cards and must not store plaintext card numbers.
* It should support annual key rotation.
Which storage approach should you adopt for your tokenization service?

A. Encrypt the card data with a deterministic algorithm stored in Firestore using Datastore mode.
B. Store the card data in Secret Manager after running a query to identify duplicates.
C. Encrypt the card data with a deterministic algorithm and shard it across multiple Memorystore instances.
D. Use column-level encryption to store the data in Cloud SQL.

Answer: A

Explanation:
Topic 10, EHR Health Care
Company overview
EHR Healthcare is a leading provider of electronic health record software to the medical industry. EHR Healthcare provides their software as a service to multi-national medical offices, hospitals, and insurance providers.
Solution concept
Due to rapid changes in the healthcare and insurance industry, EHR Healthcare's business has been growing exponentially year over year. They need to be able to scale their environment, adapt their disaster recovery plan, and roll out new continuous deployment capabilities to update their software at a fast pace. Google Cloud has been chosen to replace their current colocation facilities.
Existing technical environment
EHR's software is currently hosted in multiple colocation facilities. The lease on one of the data centers is about to expire.
Customer-facing applications are web-based, and many have recently been containerized to run on a group of Kubernetes clusters. Data is stored in a mixture of relational and NoSQL databases (MySQL, MS SQL Server, Redis, and MongoDB).
EHR is hosting several legacy file- and API-based integrations with insurance providers on-premises. These systems are scheduled to be replaced over the next several years. There is no plan to upgrade or move these systems at the current time.
Users are managed via Microsoft Active Directory. Monitoring is currently being done via various open source tools. Alerts are sent via email and are often ignored.
Business requirements
* On-board new insurance providers as quickly as possible.
* Provide a minimum 99.9% availability for all customer-facing systems.
* Provide centralized visibility and proactive action on system performance and usage.
* Increase ability to provide insights into healthcare trends.
* Reduce latency to all customers.
* Maintain regulatory compliance.
* Decrease infrastructure administration costs.
* Make predictions and generate reports on industry trends based on provider data.
Technical requirements
* Maintain legacy interfaces to insurance providers with connectivity to both on-premises systems and cloud providers.
* Provide a consistent way to manage customer-facing applications that are container-based.
* Provide a secure and high-performance connection between on-premises systems and Google Cloud.
* Provide consistent logging, log retention, monitoring, and alerting capabilities.
* Maintain and manage multiple container-based environments.
* Dynamically scale and provision new environments.
* Create interfaces to ingest and process data from new providers.
Executive statement
Our on-premises strategy has worked for years but has required a major investment of time and money in training our team on distinctly different systems, managing similar but separate environments, and responding to outages. Many of these outages have been a result of misconfigured systems, inadequate capacity to manage spikes in traffic, and inconsistent monitoring practices. We want to use Google Cloud to leverage a scalable, resilient platform that can span multiple environments seamlessly and provide a consistent and stable user experience that positions us for future growth.

NEW QUESTION # 300
You want to make a copy of a production Linux virtual machine in the US-Central region. You want to manage and replace the copy easily if there are changes on the production virtual machine. You will deploy the copy as a new instances in a different project in the US-East region. What steps must you take?

A. Create a snapshot of the root disk, create an image file in Google Cloud Storage from the snapshot, and create a new virtual machine instance in the US-East region using the image file for the root disk.
B. Create a snapshot of the root disk and select the snapshot as the root disk when you create a new virtual machine instance in the US-East region.
C. Use the Linux dd and netcat command to copy and stream the root disk contents to a new virtual machine instance in the US-East region.
D. Create an image file from the root disk with Linux dd command, create a new disk from the image file, and use it to create a new virtual machine instance in the US-East region

Answer: A

Explanation:
https://stackoverflow.com/questions/36441423/migrate-google-compute-engine-instance-to-a-different-region

NEW QUESTION # 301
Your company has a Google Cloud project that uses BigQuery for data warehousing. They have a VPN tunnel between the on-premises environment and Google Cloud that is configured with Cloud VPN. The security team wants to avoid data exfiltration by malicious insiders, compromised code, and accidental oversharing. What should they do?

A. Perform the following tasks:
1. Create a service account.
2. Give the BigQuery JobUser role and Storage Reader role to the service account.
3. Remove all other IAM access from the project.
B. Configure Private Google Access for on-premises only.
C. Configure VPC Service Controls and configure Private Google Access.
D. Configure Private Google Access.

Answer: C

Explanation:
Data exfiltration by malicious insiders or compromised code: VPC Service Controls complements network egress controls by preventing clients within those networks from accessing the resources of Google-managed services outside the perimeter.
https://cloud.google.com/vpc-service-controls/docs/overview

NEW QUESTION # 302
You are tasked with building an online analytical processing (OLAP) marketing analytics and reporting tool. This requires a relational database that can operate on hundreds of terabytes of data. What is the Google- recommended tool for such applications?

A. Cloud SQL, because it is a fully managed relational database
B. Cloud Spanner, because it is globally distributed
C. BigQuery, because it is designed for large-scale processing of tabular data
D. Cloud Firestore, because it offers real-time synchronization across devices

Answer: C

NEW QUESTION # 303
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