Free PDF 2025 First-grade Google Professional-Cloud-Architect: Google Certified Professional - Cloud Architect (GCP) Relevant Answers
Free PDF 2025 First-grade Google Professional-Cloud-Architect: Google Certified Professional - Cloud Architect (GCP) Relevant Answers
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At the Prep4sureExam, we strive to provide our customers with updated and real Google Professional-Cloud-Architect exam questions. We are committed to helping our students reach their goals and advance their careers through comprehensive, convenient, and cost-effective Prepare for your Google Certified Professional - Cloud Architect (GCP) (Professional-Cloud-Architect) exam preparation material.
Passing the Google Professional-Cloud-Architect Certification Exam can help cloud architects to demonstrate their expertise and enhance their career prospects. Google Certified Professional - Cloud Architect (GCP) certification is recognized globally and can open up new opportunities in cloud architecture and design, as well as increase the earning potential of certified professionals.
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Additionally, students can take multiple Professional-Cloud-Architect exam questions, helping them to check and improve their performance. Three formats are prepared in such a way that by using them, candidates will feel confident and crack the Google Certified Professional - Cloud Architect (GCP) (Professional-Cloud-Architect) actual exam. These three formats suit different preparation styles of Professional-Cloud-Architect test takers.
Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q237-Q242):
NEW QUESTION # 237
Your company wants to try out the cloud with low risk. They want to archive approximately 100 TB of their log data to the cloud and test the analytics features available to them there, while also retaining that data as a long- term disaster recovery backup.
Which two steps should you take? Choose 2 answers.
- A. Load logs into Google Cloud SQL
- B. Insert logs into Google Cloud Bigtable
- C. Load logs into Google BigQuery
- D. Upload log files into Google Cloud Storage
- E. Import logs into Google Stackdriver
Answer: C,D
NEW QUESTION # 238
Case Study: 5 - Dress4win
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a website and mobile application. The company also cultivates an active social network that connects their users with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a freemium app model. The application has grown from a few servers in the founder's garage to several hundred servers and appliances in a collocated data center. However, the capacity of their infrastructure is now insufficient for the application's rapid growth. Because of this growth and the company's desire to innovate faster.
Dress4Win is committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4win is moving their development and test environments. They are also building a disaster recovery site, because their current infrastructure is at a single location. They are not sure which components of their architecture they can migrate as is and which components they need to change before migrating them.
Existing Technical Environment
The Dress4win application is served out of a single data center location. All servers run Ubuntu LTS v16.04.
Databases:
MySQL. 1 server for user data, inventory, static data:
- MySQL 5.8
- 8 core CPUs
- 128 GB of RAM
- 2x 5 TB HDD (RAID 1)
Redis 3 server cluster for metadata, social graph, caching. Each server is:
- Redis 3.2
- 4 core CPUs
- 32GB of RAM
Compute:
40 Web Application servers providing micro-services based APIs and static content.
- Tomcat - Java
- Nginx
- 4 core CPUs
- 32 GB of RAM
20 Apache Hadoop/Spark servers:
- Data analysis
- Real-time trending calculations
- 8 core CPUS
- 128 GB of RAM
- 4x 5 TB HDD (RAID 1)
3 RabbitMQ servers for messaging, social notifications, and events:
- 8 core CPUs
- 32GB of RAM
Miscellaneous servers:
- Jenkins, monitoring, bastion hosts, security scanners
- 8 core CPUs
- 32GB of RAM
Storage appliances:
iSCSI for VM hosts
Fiber channel SAN - MySQL databases
- 1 PB total storage; 400 TB available
NAS - image storage, logs, backups
- 100 TB total storage; 35 TB available
Business Requirements
Build a reliable and reproducible environment with scaled parity of production.
Improve security by defining and adhering to a set of security and Identity and Access
Management (IAM) best practices for cloud.
Improve business agility and speed of innovation through rapid provisioning of new resources.
Analyze and optimize architecture for performance in the cloud.
Technical Requirements
Easily create non-production environment in the cloud.
Implement an automation framework for provisioning resources in cloud.
Implement a continuous deployment process for deploying applications to the on-premises
datacenter or cloud.
Support failover of the production environment to cloud during an emergency.
Encrypt data on the wire and at rest.
Support multiple private connections between the production data center and cloud
environment.
Executive Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a competitor could use a public cloud platform to offset their up-front investment and free them to focus on developing better features. Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total cost of ownership (TCO) analysis over the next 5 years for a public cloud strategy achieves a cost reduction between 30% and 50% over our current model.
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. 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.
- B. 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.
- C. 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.
- D. 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.
Answer: A
NEW QUESTION # 239
Case Study: 3 - JencoMart Case Study
Company Overview
JencoMart is a global retailer with over 10,000 stores in 16 countries. The stores carry a range of goods, such as groceries, tires, and jewelry. One of the company's core values is excellent customer service. In addition, they recently introduced an environmental policy to reduce their carbon output by 50% over the next 5 years.
Company Background
JencoMart started as a general store in 1931, and has grown into one of the world's leading brands known for great value and customer service. Over time, the company transitioned from only physical stores to a stores and online hybrid model, with 25% of sales online. Currently, JencoMart has little presence in Asia, but considers that market key for future growth.
Solution Concept
JencoMart wants to migrate several critical applications to the cloud but has not completed a technical review to determine their suitability for the cloud and the engineering required for migration. They currently host all of these applications on infrastructure that is at its end of life and is no longer supported.
Existing Technical Environment
JencoMart hosts all of its applications in 4 data centers: 3 in North American and 1 in Europe, most applications are dual-homed.
JencoMart understands the dependencies and resource usage metrics of their on-premises architecture.
Application Customer loyalty portal
LAMP (Linux, Apache, MySQL and PHP) application served from the two JencoMart-owned U.S.
data centers.
Database
* Oracle Database stores user profiles
structure
* PostgreSQL database stores user credentials
-homed in US West
Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:
* 20 machines in US East Coast, each machine has:
-core CPU
Storage
* Access to shared 100 TB SAN in each location
* Tape backup every week
Business Requirements
* Optimize for capacity during peak periods and value during off-peak periods
* Guarantee service availably and support
* Reduce on-premises footprint and associated financial and environmental impact.
* Move to outsourcing model to avoid large upfront costs associated with infrastructure purchase
* Expand services into Asia.
Technical Requirements
* Assess key application for cloud suitability.
* Modify application for the cloud.
* Move applications to a new infrastructure.
* Leverage managed services wherever feasible
* Sunset 20% of capacity in existing data centers
* Decrease latency in Asia
CEO Statement
JencoMart will continue to develop personal relationships with our customers as more people access the web. The future of our retail business is in the global market and the connection between online and in-store experiences. As a large global company, we also have a responsibility to the environment through 'green' initiatives and polices.
CTO Statement
The challenges of operating data centers prevents focus on key technologies critical to our long- term success. Migrating our data services to a public cloud infrastructure will allow us to focus on big data and machine learning to improve our service customers.
CFO Statement
Since its founding JencoMart has invested heavily in our data services infrastructure. However, because of changing market trends, we need to outsource our infrastructure to ensure our long- term success. This model will allow us to respond to increasing customer demand during peak and reduce costs.
For this question, refer to the JencoMart case study.
JencoMart has built a version of their application on Google Cloud Platform that serves traffic to Asia. You want to measure success against their business and technical goals. Which metrics should you track?
- A. Total visits and average latency for users in Asia
- B. Latency difference between US and Asia
- C. The number of character sets present in the database
- D. Error rates for requests from Asia
- E. Total visits, error rates, and latency from Asia
Answer: A
Explanation:
From scenario:
Business Requirements include: Expand services into Asia
Technical Requirements include: Decrease latency in Asia
NEW QUESTION # 240
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 data. You want to help them find a solution that meets their needs, what should you do?
- A. Direct them to download and install the Google StackDriver logging agent.
- B. Help them upgrade their current tool to take advantage of any new features.
- C. Help them define their requirements and assess viable logging tools.
- D. Send them a list of online resources about logging best practices.
Answer: A
Explanation:
The Stackdriver Logging agent streams logs from your VM instances and from selected third party software packages to Stackdriver Logging. Using the agent is optional but we recommend it. The agent runs under both Linux and Microsoft Windows.
Note: Stackdriver Logging allows you to store, search, analyze, monitor, and alert on log data and events from Google Cloud Platform and Amazon Web Services (AWS). Our API also allows ingestion of any custom log data from any source. Stackdriver Logging is a fully managed service that performs at scale and can ingest application and system log data from thousands of VMs.
Even better, you can analyze all that log data in real time.
References: https://cloud.google.com/logging/docs/agent/installation
https://medium.com/google-cloud/hidden-super-powers-of-stackdriver-logging-ca110dae7e74
NEW QUESTION # 241
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 Cloud Dataproc to run Apache Hadoop jobs to process each test
- C. Google Compute Engine managed instance groups with auto-scaling
- D. Google Compute Engine unmanaged instance groups and Network Load Balancer
Answer: C
Explanation:
Explanation/Reference:
Explanation:
Google Compute Engine enables users to launch virtual machines (VMs) on demand. VMs can be launched from the standard images or custom images created by users.
Managed instance groups offer autoscaling capabilities that allow you to automatically add or remove instances from a managed instance group based on increases or decreases in load. Autoscaling helps your applications gracefully handle increases in traffic and reduces cost when the need for resources is lower.
Incorrect Answers:
B: There is no mention of incoming IP data traffic for the custom C++ applications.
C: Apache Hadoop is not fit for testing C++ applications. Apache Hadoop is an open-source software framework used for distributed storage and processing of datasets of big data using the MapReduce programming model.
D: Google App Engine is intended to be used for web applications.
Google App Engine (often referred to as GAE or simply App Engine) is a web framework and cloud computing platform for developing and hosting web applications in Google-managed data centers.
References: https://cloud.google.com/compute/docs/autoscaler/
NEW QUESTION # 242
......
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