PROFESSIONAL-CLOUD-ARCHITECT · Question #98
Case Study: 7 - Mountkirk Games Company Overview Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of their games using some server-side…
The correct answer is D. Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use. Mountkirk Games needs a multi-tier storage strategy for time series game metrics, transactional game data, and historical analytics queries at global scale.
Question
Options
- AUse Cloud SQL for time series data, and use Cloud Bigtable for historical data queries.
- BUse Cloud SQL to replace MySQL, and use Cloud Spanner for historical data queries.
- CUse Cloud Bigtable to replace MySQL, and use BigQuery for historical data queries.
- DUse Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use
How the community answered
(30 responses)- A13% (4)
- B23% (7)
- C3% (1)
- D60% (18)
Why each option
Mountkirk Games needs a multi-tier storage strategy for time series game metrics, transactional game data, and historical analytics queries at global scale.
Cloud SQL is a relational database unsuitable for high-throughput time series writes, and Bigtable is not designed for historical analytical queries the way BigQuery is.
Cloud SQL is not designed for the write throughput required by streaming game metrics, and Cloud Spanner is not an analytics engine.
While Bigtable and BigQuery are correct components, this option omits the transactional layer (Cloud Spanner) needed for game session state management.
Cloud Bigtable is purpose-built for high-throughput time series and IoT/gaming metrics; Cloud Spanner provides globally distributed, strongly consistent transactional storage for game session state; BigQuery is optimized for petabyte-scale analytical queries over historical data, making this the correct three-tier architecture.
Concept tested: GCP storage tier selection for gaming workloads
Source: https://cloud.google.com/bigtable/docs/overview
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