LATEST GOOGLE CERTIFIED PROFESSIONAL - CLOUD ARCHITECT (GCP) PASS REVIEW & PROFESSIONAL-CLOUD-ARCHITECT GETFREEDUMPS STUDY MATERIALS

Latest Google Certified Professional - Cloud Architect (GCP) pass review & Professional-Cloud-Architect getfreedumps study materials

Latest Google Certified Professional - Cloud Architect (GCP) pass review & Professional-Cloud-Architect getfreedumps study materials

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Candidates who successfully pass the Google Professional-Cloud-Architect Certification Exam can showcase their expertise in GCP and demonstrate their ability to design and implement cloud-based solutions using GCP. This credential can help IT professionals stand out in the job market, increase their earning potential, and open up new career opportunities. Additionally, Google offers a range of other certification programs, including the Associate Cloud Engineer, Professional Data Engineer, and Professional Cloud Developer, among others, which can further enhance an individual's cloud computing skills and marketability.

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To be eligible for the Google Professional-Cloud-Architect certification exam, candidates must have at least three years of industry experience, including one year of designing and managing solutions using GCP. They should also have a strong understanding of GCP services, infrastructure, and security. Professional-Cloud-Architect exam tests the candidates' knowledge and skills in various areas, including designing and planning a GCP solution, managing and provisioning GCP resources, and optimizing GCP performance and cost.

To become a Google Certified Professional - Cloud Architect, candidates must pass the GCP certification exam. Professional-Cloud-Architect Exam consists of multiple-choice questions and is delivered online. Candidates have two hours to complete the exam, and they must score at least 70% to pass. Professional-Cloud-Architect exam fee is $200 USD, and it is recommended that candidates have at least three years of industry experience before taking the exam.

Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q211-Q216):

NEW QUESTION # 211
You are building a continuous deployment pipeline for a project stored in a Git source repository and want to ensure that code changes can be verified deploying to production. What should you do?

  • A. Use Jenkins to build the staging branches and the master branch. Build and deploy changes to production for 10% of users before doing a complete rollout.
  • B. Use Spinnaker to deploy builds to production and run tests on production deployments.
  • C. Use Jenkins to monitor tags in the repository. Deploy staging tags to a staging environment for testing.
  • D. Use Spinnaker to deploy builds to production using the red/black deployment strategy so that changes can easily be rolled back.

Answer: C

Explanation:
After testing, tag the repository for production and deploy that to the production environment.
Reference:
README.md


NEW QUESTION # 212
You are using a single Cloud SQL instance to serve your application from a specific zone. You want to introduce high availability. What should you do?

  • A. Create a read replica instance in the same region, but in a different zone
  • B. Create a failover replica instance in the same region, but in a different zone
  • C. Create a failover replica instance in a different region
  • D. Create a read replica instance in a different region

Answer: B

Explanation:
Explanation
https://cloud.google.com/sql/docs/mysql/high-availability


NEW QUESTION # 213
For this question, refer to the Mountkirk Games case study. Mountkirk Games wants you to design a way to test the analytics platform's resilience to changes in mobile network latency. What should you do?

  • A. Create an opt-in beta of the game that runs on players' mobile devices and collects response times from analytics endpoints running in Google Cloud Platform regions all over the world.
  • B. Add the ability to introduce a random amount of delay before beginning to process analytics files uploaded from mobile devices.
  • C. Deploy failure injection software to the game analytics platform that can inject additional latency to mobile client analytics traffic.
  • D. Build a test client that can be run from a mobile phone emulator on a Compute Engine virtual machine, and run multiple copies in Google Cloud Platform regions all over the world to generate realistic traffic.

Answer: A

Explanation:
Topic 8, Mountkrik Games Case 3
Company overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They have recently started expanding to other platforms after successfully migrating their on-premises environments to Google Cloud.
Their most recent endeavor is to create a retro-style first-person shooter (FPS) game that allows hundreds of simultaneous players to join a geo-specific digital arena from multiple platforms and locations. A real-time digital banner will display a global leaderboard of all the top players across every active arena.
Solution concept
Mountkirk Games is building a new multiplayer game that they expect to be very popular. They plan to deploy the game's backend on Google Kubernetes Engine so they can scale rapidly and use Google's global load balancer to route players to the closest regional game arenas. In order to keep the global leader board in sync, they plan to use a multi-region Spanner cluster.
Existing technical environment
The existing environment was recently migrated to Google Cloud, and five games came across using lift-and-shift virtual machine migrations, with a few minor exceptions. Each new game exists in an isolated Google Cloud project nested below a folder that maintains most of the permissions and network policies. Legacy games with low traffic have been consolidated into a single project. There are also separate environments for development and testing.
Business requirements
Support multiple gaming platforms.
Support multiple regions.
Support rapid iteration of game features.
Minimize latency.
Optimize for dynamic scaling.
Use managed services and pooled resources.
Minimize costs.
Technical requirements
Dynamically scale based on game activity.
Publish scoring data on a near real-time global leaderboard.
Store game activity logs in structured files for future analysis.
Use GPU processing to render graphics server-side for multi-platform support.
Support eventual migration of legacy games to this new platform.
Executive statement
Our last game was the first time we used Google Cloud, and it was a tremendous success. We were able to analyze player behavior and game telemetry in ways that we never could before. This success allowed us to bet on a full migration to the cloud and to start building all-new games using cloud-native design principles. Our new game is our most ambitious to date and will open up doors for us to support more gaming platforms beyond mobile. Latency is our top priority, although cost management is the next most important challenge. As with our first cloud-based game, we have grown to expect the cloud to enable advanced analytics capabilities so we can rapidly iterate on our deployments of bug fixes and new functionality.


NEW QUESTION # 214
Case Study: 2 - TerramEarth Case Study
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries: About
80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in 100 countries. Their mission is to build products that make their customers more productive.
Company Background
TerramEarth formed in 1946, when several small, family owned companies combined to retool after World War II. The company cares about their employees and customers and considers them to be extended members of their family.
TerramEarth is proud of their ability to innovate on their core products and find new markets as their customers' needs change. For the past 20 years trends in the industry have been largely toward increasing productivity by using larger vehicles with a human operator.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second.
Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced.
The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second, with 22 hours of operation per day.
TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment

TerramEarth's existing architecture is composed of Linux-based systems that reside in a data center. These systems gzip CSV files from the field and upload via FTP, transform and aggregate them, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
- Decrease unplanned vehicle downtime to less than 1 week, without
increasing the cost of carrying surplus inventory
- Support the dealer network with more data on how their customers use
their equipment IP better position new products and services.
- Have the ability to partner with different companies-especially with
seed and fertilizer suppliers in the fast-growing agricultural
business-to create compelling joint offerings for their customers
CEO Statement
We have been successful in capitalizing on the trend toward larger vehicles to increase the productivity of our customers. Technological change is occurring rapidly and TerramEarth has taken advantage of connected devices technology to provide our customers with better services, such as our intelligent farming equipment. With this technology, we have been able to increase farmers' yields by 25%, by using past trends to adjust how our vehicles operate. These advances have led to the rapid growth of our agricultural product line, which we expect will generate 50% of our revenues by 2020.
CTO Statement
Our competitive advantage has always been in the manufacturing process with our ability to build better vehicles for tower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. Unfortunately, our CEO doesn't take technology obsolescence seriously and he considers the many new companies in our industry to be niche players. My goals are to build our skills while addressing immediate market needs through incremental innovations.
For this question, refer to the TerramEarth case study. To speed up data retrieval, more vehicles will be upgraded to cellular connections and be able to transmit data to the ETL process. The current FTP process is error-prone and restarts the data transfer from the start of the file when connections fail, which happens often. You want to improve the reliability of the solution and minimize data transfer time on the cellular connections. What should you do?

  • A. Use multiple Google Container Engine clusters running FTP servers located in different regions.
    Save the data to Multi-Regional buckets in us, eu, and asia. Run the ETL process using the data in the bucket.
  • B. Use one Google Container Engine cluster of FTP servers. Save the data to a Multi-Regional bucket. Run the ETL process using data in the bucket.
  • C. Directly transfer the files to different Google Cloud Multi-Regional Storage bucket locations in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process using the data in the bucket.
  • D. Directly transfer the files to a different Google Cloud Regional Storage bucket location in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process to retrieve the data from each Regional bucket.

Answer: D


NEW QUESTION # 215
For this question, refer to the JencoMart case study.
The JencoMart security team requires that all Google Cloud Platform infrastructure is deployed using a least privilege model with separation of duties for administration between production and development resources. What Google domain and project structure should you recommend?

  • A. Create two G Suite accounts to manage users: one for development/test/staging and one for production. Each account should contain one project for every application.
  • B. Create a single G Suite account to manage users with each stage of each application in its own project.
  • C. Create a single G Suite account to manage users with one project for the development/test/staging environment and one project for the production environment.
  • D. Create two G Suite accounts to manage users: one with a single project for all development applications and one with a single project for all production applications.

Answer: A

Explanation:
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations#projects-and- access


NEW QUESTION # 216
......

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