Solusi untuk Game

This Guidance demonstrates betting and gaming setups that deliver video and data streams at low latencies using Amazon Interactive Video Service (Amazon IVS).

This Guidance demonstrates how to build an event-driven, serverless sportsbook application to help sports-betting operators handle spiky, seasonal traffic.

This Guidance demonstrates how to set up a fully managed, distributed load testing solution in a quick and cost-effective manner using AWS services and Locust, an open-source load testing tool.

This Guidance demonstrates how you can unlock insights and respond to game player behavior using natural language and generative business intelligence.

Men-deploy solusi yang menyediakan produk dan layanan yang dibutuhkan untuk mengotomatiskan pengujian beban aplikasi.

This Guidance demonstrates how developers can build applications on mobile iOS and Apple Vision Pro in the AWS Cloud using Unity—a widely-used game engine and development platform where developers can create immersive 2D and 3D interactive experiences.

This Guidance shows how your developers can build a real-time analytics pipeline that uses AI to deliver effective marketing offers during game sessions. By using gaming-machine and shuffler data to update machine learning (ML) models in real time, this pipeline predicts the best offers for individual customers. The analytics pipeline then returns these findings to your gaming machines and applications so that you can promote offers based on each user’s customer profile.

This Guidance allows you to personalize the betting and gaming app experience, increasing patron engagement and retention through automated, pre-built machine learning (ML) algorithms.

This Guidance demonstrates how to install and configure Perforce Helix Core, a popular version management tool for game developers, on AWS.

This Guidance helps you programmatically identify and manage 2D and 3D assets involved in the production of video games.

This Guidance demonstrates how game developers can moderate user-generated content (UGC) to ensure appropriate and safe player interactions.

This guidance helps game owners, game admins, and LiveOps admins to automate the process for building an end-to-end machine learning (ML) pipeline, that takes labeled player data and automatically builds, trains, tunes and deploys the best ML model for predicting player behavior, and gaining player insights.