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GAMESEC06-BP02 Use artificial intelligence and machine learning tools to automate aspects of your infrastructure protection strategy - Games Industry Lens
Implementation guidance

GAMESEC06-BP02 Use artificial intelligence and machine learning tools to automate aspects of your infrastructure protection strategy

Amazon Lookout for Metrics uses machine learning to automatically detect and diagnose anomalies in your business and operational data and monitors the metrics that are most important to your businesses with greater speed and accuracy. The service also makes it straightforward to diagnose the root cause of anomalies, such as a sudden dip in revenue, logins, transactions, or retention. It does not require game developers to have ML experience to set up and can connect to popular data sources including Amazon S3, Amazon CloudWatch, Amazon RDS, Amazon Redshift, as well as many SaaS applications. For example, you can integrate Amazon Lookout for Metrics with the Game Analytics Pipeline and other data sources to begin analyzing behavior to detect anomalies.

Level of risk exposed if this best practice is not established: High

Implementation guidance

Alternatively, you may choose to build, train, and host a custom machine learning model using Amazon SageMaker AI AI to address use cases such as content moderation, toxicity detection, cheat detection, fraud detection, and more.

Customer example

AnyCompany Games uses Amazon Lookout for Metrics to automatically detect unusual patterns in server performance, player login attempts, or transaction volumes that could indicate threats from bad actors. Additionally, they have used Amazon SageMaker AI to develop custom machine learning models that continually analyze network traffic patterns and player behavior to help identify coordinated threats, such as bot networks that are attempting to exploit their virtual economy.

This automated approach allows their security team to focus on investigating and responding to genuine threats rather than manually monitoring thousands of metrics, while making sure that emerging threat patterns are detected and addressed before they can significantly impact game availability or player safety.

Implementation steps

  • Use Amazon Lookout for Metrics to help automatically detect and diagnose anomalies in key business and operational data

  • Integrate Amazon Lookout for Metrics with data sources like the Game Analytics Pipeline, Amazon S3, or CloudWatch to monitor metrics such as revenue, logins, and retention.

  • Use Amazon SageMaker AI to build, train, and host custom machine learning models for advanced use cases like cheat detection, fraud prevention, and content moderation.