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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.

Submitted by eva_at· Mar 30, 2026Designing and planning a cloud solution architecture

Question

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 integration. Historically, they have used cloud providers to lease physical servers. Due to the unexpected popularity of some of their games, they have had problems scaling their global audience, application servers, MySQL databases, and analytics tools. Their current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting. Solution Concept Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL database. Business Requirements Increase to a global footprint. Improve uptime - downtime is loss of players. Increase efficiency of the cloud resources we use. Reduce latency to all customers. Technical Requirements Requirements for Game Backend Platform Dynamically scale up or down based on game activity. Connect to a transactional database service to manage user profiles and game state. Store game activity in a timeseries database service for future analysis. As the system scales, ensure that data is not lost due to processing backlogs. Run hardened Linux distro. Requirements for Game Analytics Platform Dynamically scale up or down based on game activity Process incoming data on the fly directly from the game servers Process data that arrives late because of slow mobile networks Allow queries to access at least 10 TB of historical data Process files that are regularly uploaded by users' mobile devices Executive Statement Our last successful game did not scale well with our previous cloud provider, resulting in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the game to target users. Additionally, our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers. 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?

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)
  • A
    13% (4)
  • B
    23% (7)
  • C
    3% (1)
  • D
    60% (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.

AUse Cloud SQL for time series data, and use Cloud Bigtable for historical data queries.

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.

BUse Cloud SQL to replace MySQL, and use Cloud Spanner for historical data queries.

Cloud SQL is not designed for the write throughput required by streaming game metrics, and Cloud Spanner is not an analytics engine.

CUse Cloud Bigtable to replace MySQL, and use BigQuery for historical data queries.

While Bigtable and BigQuery are correct components, this option omits the transactional layer (Cloud Spanner) needed for game session state management.

DUse Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and useCorrect

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

Topics

#Cloud Bigtable#Cloud Spanner#BigQuery#database selection

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