This template creates a job queue called `HighPriority` with two compute environments mapped to it. The compute environments are `C4OnDemand` and `M4Spot`. The job queue is enabled and has a priority of 1.

This template creates an AWS Batch job definition with the specified parameters. The example provided creates a job definition named 'nvidia-smi' of type 'container'. It includes container properties such as mount points, volumes, command, privileged access, job role ARN, readonly root filesystem, resource requirements, and the image to be used.

This template creates a managed compute environment called `C4OnDemand` that uses C4 On-Demand instances and a custom AMI. It specifies the maximum and minimum number of vCPUs, security group IDs, subnets, instance types, EC2 key pair, and desired number of vCPUs. The compute environment is enabled.

Creates an AWS Batch compute environment using EC2 instances with necessary roles and security settings.

Configures an AWS Batch compute environment using Fargate for serverless compute capabilities.

Sets the update policy for an AWS Batch compute environment to manage job execution and updates.

Defines a Batch Job for a container with specific resource requirements, volumes, environment variables, mount points, and ulimits.

Configures a Batch Job Definition for multiple nodes, specifying container properties for each node.

Defines a Batch Job using EKS properties, including pod properties and metadata.

Sets up a Batch Job Definition with Fargate platform capabilities, including IAM roles and policies for task execution.

Creates a basic AWS Batch job queue with two compute environments ordered by priority.

Configures an AWS Batch job queue with a fair share scheduling policy, including share distribution settings.

Creates an AWS Batch Scheduling Policy with fair share policy settings and tags.

This template demonstrates how to tag an ECS cluster that is implicitly created by an AWS Batch Compute Environment using the aws_ecs_tag resource.