In today's fiercely competitive gaming industry, collecting and utilizing game data is crucial for creating successful games. Analyzing player data helps understand what makes games popular. This article provides a brief overview of AWS's solutions for the gaming industry, as shared on their official blog.
Game Analytics Pipeline (GAP) as the Backbone
In 2021, AWS introduced the Game Analytics Pipeline (GAP) to support game studios of all sizes, especially small studios lacking infrastructure and data analysts. GAP offers a serverless pipeline to automatically collect, store, and process game telemetry data and events.
Optimized GAP Architecture
The updated GAP solution enables users to deploy AWS services and updates via DataOps to meet game analytics needs. The DataOps CI/CD pipeline allows testing before production deployment. This modular system integrates other AWS features for real-time fraud detection, in-game purchase promotions, LiveOps automation with AIOps, and dynamic NPC dialogues with generative AI. GAP has also improved library dependencies, bug fixes, and ETL processing speed with AWS Glue. Users can now integrate the pipeline into their games or choose the type of analytics processing, enhancing data collection efficiency.
GAP Components
GAP comprises two main pipelines: the analytics pipeline and the DataOps CI/CD pipeline. In the analytics pipeline, data producers send telemetry and event data to the AWS cloud. Amazon Kinesis Data Streams captures streaming data, and Amazon Managed Service for Apache Flink processes it. Custom metrics can be published to Amazon CloudWatch, with Amazon SNS providing real-time alerts for data anomalies. Batch telemetry is processed with Amazon Data Firehose and stored in Amazon S3, followed by ETL processes using AWS Glue. Finally, Amazon Athena and Amazon QuickSight analyze and visualize the data.
By leveraging GAP, game studios can efficiently process and utilize game data, significantly improving data collection and analysis capabilities.(See Figure 1)
Figure 1
In the DataOps CI/CD pipeline, AWS CDK is used to build and test the infrastructure code, which is then combined with AWS CloudFormation. When code is committed to the AWS CodeCommit repository, the CI/CD pipeline is triggered. The compiled infrastructure assets are stored in Amazon ECR and Amazon S3. CloudFormation Stack is then used to deploy the infrastructure for QA system testing, and AWS CodeBuild executes automated tests to verify the infrastructure's health. Finally, the tested infrastructure is deployed to the PROD AWS account using CloudFormation Stack. (See Figure 2)
Figure 2
To further understand the architecture details, please visit the AWS official website for more information!
參考資料：
AWS 官方遊戲部落格 –〈Maximize Your Game Data Insights with the updated Game Analytics Pipeline〉