Compute resource memory management
When the Amazon ECS container agent registers a compute resource into a compute environment, the agent must determine
how much memory the compute resource has available to reserve for your jobs. Because of platform memory overhead and
memory occupied by the system kernel, this number is different than the installed memory amount for Amazon EC2 instances.
For example, an m4.large instance has 8 GiB of installed memory. However, this doesn't always translate
to exactly 8192 MiB of memory available for jobs when the compute resource registers.
Suppose that you specify 8192 MiB for the job, and none of your compute resources have 8192 MiB or greater of memory available to satisfy this requirement. Then, the job can't be placed in your compute environment. If you're using a managed compute environment, AWS Batch must launch a larger instance type to accommodate the request.
The default AWS Batch compute resource AMI also reserves 32 MiB of memory for the Amazon ECS container agent and other critical system processes. This memory isn't available for job allocation. For more information, see Reserve system memory.
The Amazon ECS container agent uses the Docker ReadMemInfo() function to query the total memory available
to the operating system. Linux provides command line utilities to determine the total memory.
Example - Determine Linux total memory
The free command returns the total memory that's recognized by the operating system.
$free -b
The following is example output for an m4.large instance that's running the Amazon ECS-optimized Amazon Linux AMI.
total used free shared buffers cached Mem:8373026816348180480 8024846336 90112 25534464 205418496 -/+ buffers/cache: 117227520 8255799296
This instance has 8373026816 bytes of total memory. This means that there's 7985 MiB available for tasks.
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