Game Developer Resources

GAMES

In this lab, you learn how to build a multiplayer, turn-based game using Amazon DynamoDB and Amazon Simple Notification Service (Amazon SNS). Amazon DynamoDB is a fully-managed, NoSQL database that provides lightning-fast performance at any scale. Amazon SNS is a high-volume messaging service that allows for pub/sub functionality as well as messaging directly to SMS, email, or mobile applications.

GAMES

In this lab, you learn how to build an inventory system for a game application using Amazon Aurora Serverless. Amazon Aurora is a highly performant, cloud-native relational database offering from AWS that offers both MySQL-compatible and PostgreSQL-compatible editions. The Serverless offering of the Aurora database provides on-demand automatic scaling capabilities and the Data API, a fast, secure method for accessing your database over HTTP.

GAMES

In this lab, you learn advanced data modeling patterns in Amazon DynamoDB. When using DynamoDB, it is important to consider how you will access your data (your access patterns) before you model your data. We walk through an example multiplayer game, discuss the access patterns in the game, and show how to design a DynamoDB table to handle the access patterns by using secondary indexes and transactions.

DIGITAL | 90 MINUTES

This course introduces the AWS for Games portfolio of technical products and solutions, and their benefits to game developers. Learners will explore the four solutions offered by AWS for Games: Compute, Database, Analytics, and Machine Learning, and how these solutions enable game development across different genres and platforms using AWS for Games managed and unmanaged services.

DIGITAL | 90 MINUTES

This self-paced course is a fundamental introduction to building games on AWS using Amazon Lumberyard. In this course, you will learn about Amazon Lumberyard features and explore various AWS solutions that can be integrated into games built with it.

DIGITAL | 90 MINUTES

This course describes game server hosting options on AWS. It identifies key technical and business requirements that influence selecting a game server hosting solution. The course describes AWS Game Server hosting solutions including Amazon GameLift, FleetIQ Game Server Groups, container-based solutions using Amazon ECS, Amazon EKS, and AWS Fargate, and solutions based on Amazon EC2 and AWS core services.

DIGITAL | 2 HOURS

This course provides an in-depth look at Amazon GameLift, beginning with its features of infrastructure and session management, game session placement, and matchmaking. It then explores the challenges with hosting, managing, and scaling a multiplayer game, and how GameLift can address those challenges. Finally, it discusses solution design decisions that will impact matchmaking and the costs associated with hosting game servers.

SELF-PACED LAB | 90 MINUTES

In this lab, you will learn how to use Amazon GameLift to load a game build and create a fleet with a single instance in it. You will first start game sessions directly from the session management system. You will then add a game session placement queue and use the game session placement system to start and place games into sessions.

DIGITAL | 3.5 HOURS

In this self-paced course, you learn about the process for planning data analysis solutions and the various data analytics processes that are involved. This course takes you through five key factors that indicate the need for specific AWS services in collecting, processing, analyzing, and presenting your data.

DIGITAL | 1 HOUR

This course addresses the use of analytics in gaming use cases. Learners will explore the benefit of analytics and how insights can be used to improve game design, increase efficiency of game operations, and inform financial and strategic decisions. Learners will see different sources and types of game data to use for business intelligence and how an analytics pipeline can be used to translate game data to answers.

DIGITAL | 90 MINUTES

This course addresses how to create an analytics pipeline for game development use cases. Learners will explore common approaches for implementing batch and near-real-time analytics and see how they can attain different speeds of insights through a comprehensive analytics solution. Learners will also see how a pipeline can be expanded as their needs change or evolve.