Allocation strategies - AWS Batch

Allocation strategies

When a managed compute environment is created, AWS Batch selects instance types from the instanceTypes specified that best fit the needs of the jobs. The allocation strategy defines behavior when AWS Batch needs additional capacity. This parameter isn't applicable to jobs running on Fargate resources, and shouldn't be specified. For more information, see Allocation strategies.

BEST_FIT (default)

AWS Batch selects an instance type that best fits the needs of the jobs with a preference for the lowest-cost instance type. If additional instances of the selected instance type aren't available, AWS Batch waits for the additional instances to be available. If there aren't enough instances available, or if the user is hitting Amazon EC2 service limits then additional jobs don't run until currently running jobs have completed. This allocation strategy keeps costs lower but can limit scaling. If you're using Spot Fleets with BEST_FIT then the Spot Fleet IAM Role must be specified.

BEST_FIT_PROGRESSIVE

AWS Batch selects additional instance types that are large enough to meet the requirements of the jobs in the queue. It has a preference for instance types with a lower cost for each unit vCPU. If additional instances of the previously selected instance types aren't available, AWS Batch selects new instance types.

SPOT_CAPACITY_OPTIMIZED

AWS Batch selects one or more instance types that are large enough to meet the requirements of the jobs in the queue, with a preference for instance types that are less likely to be interrupted. This allocation strategy is only available for Spot Instance compute resources.

With both BEST_FIT_PROGRESSIVE and SPOT_CAPACITY_OPTIMIZED strategies, AWS Batch might need to exceed maxvCpus to meet your capacity requirements. In this event, AWS Batch never exceeds maxvCpus by more than a single instance.