# Guidance for Game Analytics Pipeline on AWS

## Overview

This Guidance demonstrates how to implement a comprehensive game analytics solution that empowers developers to make data-driven decisions throughout their game's lifecycle. By deploying a modular, serverless analytics pipeline, development teams can efficiently collect and analyze both real-time and batch telemetry data from game clients and backend services. Using AWS CDK or Terraform, teams can easily deploy and manage this cost-effective serverless architecture that scales with usage, making it ideal for everything from early playtesting to full production deployment. With multi-region deployment flexibility and an option for future integration with AI/ML, the pipeline enables teams to quickly transform raw gameplay data into actionable insights, helping create more engaging player experiences while optimizing development resources.

## How it works

These technical details feature an architecture diagram to illustrate how to effectively use this solution. The architecture diagram shows the key components and their interactions, providing an overview of the architecture's structure and functionality step-by-step.

[Download the architecture diagram](https://d1.awsstatic.com/onedam/marketing-channels/website/aws/en_US/solutions/approved/documents/architecture-diagrams/game-analytics-pipeline-on-aws.pdf)

![Architecture diagram](/images/solutions/game-analytics-pipeline-on-aws/images/game-analytics-pipeline-on-aws-1.png)

1. **Step 1**: The Game Analytics Pipeline Guidance can accept data from any HTTP/HTTPS REST based sources, such as Game Clients, Game Servers, or Backend services.
1. **Step 2**: A serverless, managed API backend infrastructure using Amazon API Gateway, AWS Lambda, and Amazon DynamoDB authenticates and either sends events or performs administrative tasks.
1. **Step 3**: An optional real-time analytics option using Amazon Kinesis Data Streams, Amazon Managed Service for Apache Flink, and Amazon OpenSearch Service deploys realtime ingest, processing, and dashboards.
1. **Step 4**: Deploy the guidance using a Data Lake to batch events using Amazon Data Firehose, store in Parquet format in Amazon Simple Storage Service (Amazon S3) with Hive or Iceberg tables, process data with AWS Glue, and query the data with Amazon Athena.
1. **Step 5**: When deploying the guidance using a Data Warehouse, ingest events from Amazon Kinesis Data Streams into Amazon Redshift in a serverless configuration. Amazon Redshift will include processing and querying capabilities for the data.
## Deploy with confidence

Everything you need to launch this Guidance in your account is right here.

- **Let's make it happen**: Ready to deploy? Review the sample code on GitHub for detailed deployment instructions to deploy as-is or customize to fit your needs.

[Go to sample code](https://github.com/aws-solutions-library-samples/guidance-for-game-analytics-pipeline-on-aws)


[Read usage guidelines](/solutions/guidance-disclaimers/)