AWS Batch now supports resource aware scheduling

AWS Batch now supports job scheduling that takes into account consumable resources (CRs) such as third-party license tokens, database access bandwidth, budgetary limits, and more. With resource aware scheduling you can set up sets of tokens representing these resources, which will then be consumed by the running AWS Batch jobs. This will help you reduce job failures and wasted compute time caused by missing or rate-limited resources, which in turn will improve utilization of infrastructure and reduce costs. You can create, manage, and monitor consumption of your CRs using AWS Batch Management Console or the new AWS Batch consumable resource APIs such as _CreateConsumableResource_, _DescribeConsumableResource_, _UpdateConsumableResource_, _DeleteConsumableResource_, and _ListJobsByConsumableResource_. Once you set up your consumable resources, you can associate up to 5 CRs with your AWS Batch jobs while creating or updating AWS Batch job definitions. For more information, see Consumable Resources page in the [AWS Batch User Guide](https://docs.aws.amazon.com/batch/latest/userguide/resource-aware-scheduling.html), [AWS Batch API Reference](https://docs.aws.amazon.com/batch/latest/APIReference/API%5FOperations.html), and our [AWS HPC Blog post](https://aws.amazon.com/blogs/hpc/how-to-use-rate-limited-resources-in-aws-batch-jobs-with-resource-aware-scheduling/). AWS Batch supports developers, scientists, and engineers in running efficient batch processing for ML model training, simulations, and analysis at any scale. Resource aware scheduling is available for all types of AWS Batch compute environments in any [AWS Region](https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/) where AWS Batch is available.