For this question, refer to the Mountkirk Games case study. Which managed storage option meets Mountkirk's technical requirement for storing game activity in a time series database service?
Correct Answer: A
https://cloud.google.com/blog/products/databases/getting-started-with-time-series-trend-predictions-using-gcp Topic 9, Mountkrik Games 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.
Question 137
You need to design a solution for global load balancing based on the URL path being requested. You need to ensure operations reliability and end-to-end in-transit encryption based on Google best practices. What should you do?
One of your primary business objectives is being able to trust the data stored in your application. You want to log all changes to the application data. How can you design your logging system to verify authenticity of your logs?
Correct Answer: B
Question 139
For this question, refer to the TerramEarth case study. TerramEarth's CTO wants to use the raw data from connected vehicles to help identify approximately when a vehicle in the development team to focus their failure. You want to allow analysts to centrally query the vehicle data. Which architecture should you recommend? A) B) C) D)
Correct Answer: A
Explanation https://cloud.google.com/solutions/iot/ https://cloud.google.com/solutions/designing-connected-vehicle-platform https://cloud.google.com/solutions/designing-connected-vehicle-platform#data_ingestion http://www.eweek.com/big-data-and-analytics/google-touts-value-of-cloud-iot-core-for-analyzing-connected-car https://cloud.google.com/solutions/iot/ The push endpoint can be a load balancer. A container cluster can be used. Cloud Pub/Sub for Stream Analytics References: https://cloud.google.com/pubsub/ https://cloud.google.com/solutions/iot/ https://cloud.google.com/solutions/designing-connected-vehicle-platform https://cloud.google.com/solutions/designing-connected-vehicle-platform#data_ingestion http://www.eweek.com/big-data-and-analytics/google-touts-value-of-cloud-iot-core-for-analyzing-connected-car https://cloud.google.com/solutions/iot/
Question 140
Your company is planning to perform a lift and shift migration of their Linux RHEL 6.5+ virtual machines. The virtual machines are running in an on-premises VMware environment. You want to migrate them to Compute Engine following Google-recommended practices. What should you do?
Correct Answer: C
The framework illustrated in the preceding diagram has four phases: *Assess. In this phase, you assess your source environment, assess the workloads that you want to migrate to Google Cloud, and assess which VMs support each workload. *Plan. In this phase, you create the basic infrastructure for Migrate for Compute Engine, such as provisioning the resource hierarchy and setting up network access. *Deploy. In this phase, you migrate the VMs from the source environment to Compute Engine. *Optimize. In this phase, you begin to take advantage of the cloud technologies and capabilities. Reference: https://cloud.google.com/architecture/migrating-vms-migrate-for-compute-engine-getting-started
