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NEW QUESTION 33 For this question, refer to the Mountkirk Games case study. Mountkirk Games wants you to design their new testing strategy. How should the test coverage differ from their existing backends on the other platforms?

• A. Tests should scale well beyond the prior approaches.
• B. Tests should be applied after the release is in the production environment.
• C. Unit tests are no longer required, only end-to-end tests.
• D. Tests should include directly testing the Google Cloud Platform (GCP) infrastructure.

Answer: A Explanation: Explanation From Scenario: A few of their games were more popular than expected, and they had problems scaling their application servers, MySQL databases, and analytics tools. Requirements for Game Analytics Platform include: Dynamically scale up or down based on game activity   NEW QUESTION 34 A lead software engineer tells you that his new application design uses websockets and HTTP sessions that are not distributed across the web servers. You want to help him ensure his application will run property on Google Cloud Platform. What should you do?

• A. Help the engineer to convert his websocket code to use HTTP streaming.
• B. Meet with the cloud operations team and the engineer to discuss load balancer options.
• C. Help the engineer redesign the application to use a distributed user session service that does not rely on websockets and HTTP sessions.
• D. Review the encryption requirements for websocket connections with the security team.

Answer: B   NEW QUESTION 35 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 Server Uptime and Error Rate as service level indicators.
• B. Create Request Latency and Error Rate as service level indicators.
• C. Create CPU Utilization and Request Latency as service level indicators.
• D. Create GKE CPU Utilization and Memory Utilization as service level indicators.

Answer: C Explanation: 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.   NEW QUESTION 36 You want to create a private connection between your instances on Compute Engine and your on-premises data center. You require a connection of at least 20 Gbps. You want to follow Google-recommended practices. How should you set up the connection?

• A. Create a VPC and connect it to your on-premises data center using Dedicated Interconnect.
• B. Create a Cloud Content Delivery Network (Cloud CDN) and connect it to your on-premises datacenter using a single Cloud VPN.
• C. Create a VPC and connect it to your on-premises data center using a single Cloud VPN.
• D. Create a Cloud Content Delivery Network (Cloud CDN) and connect it to your on-premises data center using Dedicated Interconnect.

Answer: A Explanation: Reference: https://cloud.google.com/compute/docs/instances/connecting-advanced   NEW QUESTION 37 ......