Allocation Strategies
When a managed compute environment is created, AWS Batch will select 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.
BEST_FIT-
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 are not available, AWS Batch will wait for the additional instances to be available. If there are not enough instances available, or if the user is hitting Amazon EC2 service limits then additional jobs will not be run until currently running jobs have completed. This allocation strategy keeps costs lower but can limit scaling.
BEST_FIT_PROGRESSIVE-
AWS Batch will select additional instance types that are large enough to meet the requirements of the jobs in the queue, with a preference for instance types with a lower cost per unit vCPU. If additional instances of the previously selected instance types are not available, AWS Batch will select new instance types.
SPOT_CAPACITY_OPTIMIZED-
AWS Batch will select 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 may
need to go above maxvCpus to meet your capacity requirements. In this event, AWS Batch will never go above
maxvCpus by more than a single instance.
