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Bot Client Implementation for testing the Unity deployment

This additional component is designed to help test the Unity deployment option by running headless client bots on AWS Fargate, a fully managed serverless platform for running containerized applications.

Setup

You need to have the backend, GameLift resources and client all set up and deployed first.

  1. Make sure you have Docker installed and running on your system
  2. Make sure you have AWS CLI configured on your system
  3. Set your AWS Account ID in configuration.sh
  4. Open the UnityProject and configure bots by selecting Gamelift -> SetAsBotClientBuild. You can test run a bot locally.
  5. Build the bot client by selecting Gamelift -> BuildLinuxBotClient. Select the folder UnityBotCLient/Build as the output folder
  6. Run ./buildSetupAndRunBots.sh to start the bots. Modify the script if you want to change the bot count. Each Fargate Task will run 4 bots, so the default configuration 10 will run 40 bots on a continuous fashion as a Fargate Service, until you terminate them. The script will
  • Create an ECR repository
  • Build the container from your prebuilt binary and push it to the repository
  • Deploy the stack gamelift-example-bot-resources.yaml that creates a VPC, ECS Cluster and an ECS Service that hots your bots. Each Task in the service runs 4 bots and you can configure the amount of Tasks in the script.
  1. When you're done, run ./destroyBots.sh to destroy the whole infrastructure for the bots

The bots will be deployed to your defined home region but you could easily modify the script to deploy the stack to multiple regions to better test latency-based matchmaking and multi-region fleets.

Note for MacOS M1 development machines

If you're building the containers on an ARM-based Mac, please use the following build command instead in the ./buildSetupAndRunBots.sh script:

docker buildx build ./Build/ --platform=linux/amd64 -t $accountid.dkr.ecr.$region.amazonaws.com/gamelift-example-bot-client:$build_id

This will build an x86 version of the Docker container so it will run correctly on AWS Fargate.