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Free Google Cloud Architect Professional Exam Braindumps (page: 16)

Page 15 of 68
PDF with 278 Questions
View Related Case Study

For this question, refer to the Mountkirk Games case study. You need to analyze and define the technical architecture for the database workloads for your company, Mountkirk Games. Considering the business and technical requirements, what should you do?

  1. Use Cloud SQL for time series data, and use Cloud Bigtable for historical data queries.
  2. Use Cloud SQL to replace MySQL, and use Cloud Spanner for historical data queries.
  3. Use Cloud Bigtable to replace MySQL, and use BigQuery for historical data queries.
  4. Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use BigQuery for historical data queries.

Answer(s): D

Explanation:

https://cloud.google.com/bigtable/docs/schema-design-time-series



View Related Case Study

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?

  1. Cloud Bigtable
  2. Cloud Spanner
  3. BigQuery
  4. Cloud Datastore

Answer(s): A

Explanation:

https://cloud.google.com/blog/products/databases/getting-started-with-time-series-trend- predictions-using-gcp



View Related Case Study

For this question, refer to the Mountkirk Games case study. You are in charge of the new Game Backend Platform architecture. The game communicates with the backend over a REST API.

You want to follow Google-recommended practices. How should you design the backend?

  1. Create an instance template for the backend. For every region, deploy it on a multi-zone managed instance group. Use an L4 load balancer.
  2. Create an instance template for the backend. For every region, deploy it on a single-zone managed instance group. Use an L4 load balancer.
  3. Create an instance template for the backend. For every region, deploy it on a multi-zone managed instance group. Use an L7 load balancer.
  4. Create an instance template for the backend. For every region, deploy it on a single-zone managed instance group. Use an L7 load balancer.

Answer(s): C

Explanation:

https://cloud.google.com/solutions/gaming/cloud-game-infrastructure#dedicated_game_server 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.



View Related Case Study

You need to optimize batch file transfers into Cloud Storage for Mountkirk Games' new Google Cloud solution.
The batch files contain game statistics that need to be staged in Cloud Storage and be processed by an extract transform load (ETL) tool.
What should you do?

  1. Use gsutil to batch move files in sequence.
  2. Use gsutil to batch copy the files in parallel.
  3. Use gsutil to extract the files as the first part of ETL.
  4. Use gsutil to load the files as the last part of ETL.

Answer(s): B


Reference:

https://cloud.google.com/storage/docs/gsutil/commands/cp






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