Capture KPIs from Game Servers on Google Cloud Platform

A.

For capturing multiple GBs of real-time key performance indicators (KPIs) from game servers running on Google Cloud Platform and monitoring them with low latency, the recommended approach is to output custom metrics to Stackdriver from the game servers, and create a Dashboard in Stackdriver Monitoring Console to view them. Therefore, option B is the correct answer.

Here's a more detailed explanation of each option and why option B is the best choice:

A. Store time-series data from the game servers in Google Bigtable, and view it using Google Data Studio: While Bigtable is a highly scalable NoSQL database designed for handling large amounts of data, it is not optimized for real-time analysis and monitoring. Google Data Studio is a reporting and visualization tool that can be used to create reports and dashboards, but it is not designed for real-time monitoring.

B. Output custom metrics to Stackdriver from the game servers, and create a Dashboard in Stackdriver Monitoring Console to view them: Stackdriver is a powerful monitoring, logging, and diagnostics solution offered by Google Cloud Platform. It provides real-time monitoring of metrics, logs, and events across your cloud infrastructure. Custom metrics can be used to track specific KPIs and output them to Stackdriver. Stackdriver Monitoring Console provides a customizable dashboard that can display real-time metrics and alerts for quick analysis and response.

C. Schedule BigQuery load jobs to ingest analytics files uploaded to Cloud Storage every ten minutes, and visualize the results in Google Data Studio: BigQuery is a fully managed data warehouse that allows you to run SQL queries against large datasets in real-time. It is designed for data analysis and not for real-time monitoring. Uploading data to Cloud Storage every ten minutes is also not suitable for real-time monitoring.

D. Insert the KPIs into Cloud Datastore entities, and run ad hoc analysis and visualizations of them in Cloud Datalab: Cloud Datastore is a NoSQL document database that can be used to store and manage data. However, it is not optimized for real-time monitoring. Cloud Datalab is a web-based interactive tool for analyzing large datasets using Python, SQL, and JavaScript. While it can be used for ad hoc analysis and visualizations, it is not designed for real-time monitoring.

In summary, for capturing multiple GBs of aggregate real-time KPIs from game servers running on Google Cloud Platform and monitoring them with low latency, the best option is to output custom metrics to Stackdriver from the game servers, and create a Dashboard in Stackdriver Monitoring Console to view them. This approach provides real-time monitoring, custom alerting, and centralized visibility across your cloud infrastructure.