Free Access Google.Professional-Cloud-Architect.v2022-04-27.q264 Practice Test (Page 21)

Question 96

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.Error rates for requests from Asia

B.Latency difference between US and Asia

C.Total visits and average latency for users in Asia

D.The number of character sets present in the database

E.Total visits, error rates, and latency from Asia

Question 97

For this question, refer to the Dress4Win case study.
You want to ensure Dress4Win's sales and tax records remain available for infrequent viewing by auditors for at least 10 years. Cost optimization is your top priority. Which cloud services should you choose?

A.Google Cloud Storage Coldline to store the data, and gsutil to access the data.

B.Google Cloud Storage Nearline to store the data, and gsutil to access the data.

C.Google Bigtabte with US or EU as location to store the data, and gcloud to access the data.

D.BigQuery to store the data, and a web server cluster in a managed instance group to access the data. Google Cloud SQL mirrored across two distinct regions to store the data, and a Redis cluster in a managed instance group to access the data.

Question 98

You have deployed an application to Kubernetes Engine, and are using the Cloud SQL proxy container to make the Cloud SQL database available to the services running on Kubernetes. You are notified that the application is reporting database connection issues. Your company policies require a post-mortem. What should you do?

A.Validate that the Service Account used by the Cloud SQL proxy container still has the Cloud Build Editor role.

B.Use gcloud sql instances restart.

C.In the GCP Console, navigate to Stackdriver Logging. Consult logs for Kubernetes Engine and Cloud SQL.

D.In the GCP Console, navigate to Cloud SQL. Restore the latest backup. Use kubectl to restart all pods.

Question 99

You need to reduce the number of unplanned rollbacks of erroneous production deployments in your company's web hosting platform. Improvement to the QA/Test processes accomplished an 80% reduction. Which additional two approaches can you take to further reduce the rollbacks? Choose 2 answers

A.Reduce the platform's dependency on relational database systems.

B.Fragment the monolithic platform into microservices.

C.Replace the platform's relational database systems with a NoSQL database.

D.Replace the QA environment with canary releases.

E.Introduce a green-blue deployment model.

Question 100

Your development teams release new versions of games running on Google Kubernetes Engine (GKE) daily.
You want to create service level indicators (SLIs) to evaluate the quality of the new versions from the user's perspective. What should you do?

A.Create CPU Utilization and Request Latency as service level indicators.

B.Create GKE CPU Utilization and Memory Utilization as service level indicators.

C.Create Request Latency and Error Rate as service level indicators.

D.Create Server Uptime and Error Rate as service level indicators.

Correct Answer: A

Topic 8, Helicopter Racing League Case
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.

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Question 96

Question 97

Question 98

Question 99

Question 100

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