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Google Professional-Cloud-Architect Exam Syllabus Topics:

Section	Objectives
Topic 1: Manage and provision the solution infrastructure	- Automate infrastructure deployment - Provision compute, storage, and network resources
Topic 2: Design and plan a cloud solution architecture	- Design Google Cloud solutions based on business requirements - Plan security and compliance requirements - Design for reliability, scalability, and availability
Topic 3: Manage implementations of cloud architecture	- Ensure solution reliability and operational excellence - Manage deployment and production systems
Topic 4: Analyze and optimize technical and business processes	- Optimize cost and resource usage - Monitor, log, and optimize system performance
Topic 5: Design for security and compliance	- Configure data protection and encryption - Implement identity and access management (IAM)

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q176-Q181):

NEW QUESTION # 176
Case Study: 9 - Helicopter Racing League
Company overview
Helicopter Racing League (HRL) is a global sports league for competitive helicopter racing. Each year HRL holds the world championship and several regional league competitions where teams compete to earn a spot in the world championship. HRL offers a paid service to stream the races all over the world with live telemetry and predictions throughout each race.
Solution concept
HRL wants to migrate their existing service to a new platform to expand their use of managed AI and ML services to facilitate race predictions. Additionally, as new fans engage with the sport, particularly in emerging regions, they want to move the serving of their content, both real-time and recorded, closer to their users.
Existing technical environment
HRL is a public cloud-first company; the core of their mission-critical applications runs on their current public cloud provider. Video recording and editing is performed at the race tracks, and the content is encoded and transcoded, where needed, in the cloud. Enterprise-grade connectivity and local compute is provided by truck-mounted mobile data centers. Their race prediction services are hosted exclusively on their existing public cloud provider. Their existing technical environment is as follows:
- Existing content is stored in an object storage service on their existing public cloud provider.
- Video encoding and transcoding is performed on VMs created for each job.
- Race predictions are performed using TensorFlow running on VMs in the current public cloud
provider.
Business requirements
HRL's owners want to expand their predictive capabilities and reduce latency for their viewers in emerging markets. Their requirements are:
- Support ability to expose the predictive models to partners.
- Increase predictive capabilities during and before races:
*Race results
*Mechanical failures
*Crowd sentiment
- Increase telemetry and create additional insights.
- Measure fan engagement with new predictions.
- Enhance global availability and quality of the broadcasts.
- Increase the number of concurrent viewers.
- Minimize operational complexity.
- Ensure compliance with regulations.
- Create a merchandising revenue stream.
Technical requirements
- Maintain or increase prediction throughput and accuracy.
- Reduce viewer latency.
- Increase transcoding performance.
- Create real-time analytics of viewer consumption patterns and engagement.
- Create a data mart to enable processing of large volumes of race data.
Executive statement
Our CEO, S. Hawke, wants to bring high-adrenaline racing to fans all around the world. We listen to our fans, and they want enhanced video streams that include predictions of events within the race (e.g., overtaking). Our current platform allows us to predict race outcomes but lacks the facility to support real-time predictions during races and the capacity to process season-long results.
For this question, refer to the Helicopter Racing League (HRL) case study. HRL is looking for a cost-effective approach for storing their race data such as telemetry. They want to keep all historical records, train models using only the previous season's data, and plan for data growth in terms of volume and information collected. You need to propose a data solution. Considering HRL business requirements and the goals expressed by CEO S. Hawke, what should you do?

A. Use BigQuery for its scalability and ability to add columns to a schema. Partition race data based on season.
B. Use Cloud Spanner for its scalability and ability to version schemas with zero downtime. Split race data using season as a primary key.
C. Use Cloud SQL for its ability to automatically manage storage increases and compatibility with MySQL.
Use separate database instances for each season.
D. Use Firestore for its scalable and flexible document-based database. Use collections to aggregate race data by season and event.

Answer: A

Explanation:
https://cloud.google.com/architecture/mobile-gaming-analysis-telemetry

NEW QUESTION # 177
Your company has decided to make a major revision of their API in order to create better experiences for their developers. They need to keep the old version of the API available and deployable, while allowing new customers and testers to try out the new API. They want to keep the same SSL and DNS records in place to serve both APIs. What should they do?

A. Configure a new load balancer for the new version of the API.
B. Have the old API forward traffic to the new API based on the path.
C. Use separate backend pools for each API path behind the load balancer.
D. Reconfigure old clients to use a new endpoint for the new API.

Answer: D

NEW QUESTION # 178
For this question, refer to the TerramEarth case study.
The TerramEarth development team wants to create an API to meet the company's business requirements. You want the development team to focus their development effort on business value versus creating a custom framework. Which method should they use?

A. Use Google Container Engine with a Tomcat container with the Swagger (Open API Specification) framework. Focus on an API for dealers and partners.
B. Use Google App Engine with the Swagger (open API Specification) framework. Focus on an API for the public.
C. Use Google Container Engine with a Django Python container. Focus on an API for the public.
D. Use Google App Engine with a JAX-RS Jersey Java-based framework. Focus on an API for the public.
E. Use Google App Engine with Google Cloud Endpoints. Focus on an API for dealers and partners.

Answer: E

Explanation:
Develop, deploy, protect and monitor your APIs with Google Cloud Endpoints. Using an Open API Specification or one of our API frameworks, Cloud Endpoints gives you the tools you need for every phase of API development.
From scenario:
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 to 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.
Reference:
https://cloud.google.com/endpoints/docs/openapi/about-cloud-endpoints?hl=en_US&_ga=2.21787131.-1712523161.1522785064
https://cloud.google.com/endpoints/docs/openapi/architecture-overview
https://cloud.google.com/storage/docs/gsutil/commands/test

NEW QUESTION # 179
Your company is moving 75 TB of data into Google Cloud. You want to use Cloud Storage and follow Googlerecommended practices. What should you do?

A. Install gsutil on each server that contains data. Use resumable transfers to upload the data into Cloud Storage.
B. Install gsutil on each server containing data. Use streaming transfers to upload the data into Cloud
C. Move your data onto a Transfer Appliance. Use a Transfer Appliance Rehydrator to decrypt the data into Cloud Storage.
D. Move your data onto a Transfer Appliance. Use Cloud Dataprep to decrypt the data into Cloud Storage.

Answer: C

Explanation:
Storage.
Explanation:
https://cloud.google.com/transfer-appliance/docs/2.0/faq

NEW QUESTION # 180
You have an outage in your Compute Engine managed instance group: all instance keep restarting after 5 seconds. You have a health check configured, but autoscaling is disabled. Your colleague, who is a Linux expert, offered to look into the issue. You need to make sure that he can access the VMs. What should you do?

A. Grant your colleague the IAM role of project Viewer
B. Perform a rolling restart on the instance group
C. Disable autoscaling for the instance group. Add his SSH key to the project-wide SSH Keys
D. Disable the health check for the instance group. Add his SSH key to the project-wide SSH keys

Answer: D

NEW QUESTION # 181
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