# Memory and vCPU considerations for AWS Batch on Amazon EKS In AWS Batch on Amazon EKS, you can specify the resources that are made available to a container. For example, you can specify `requests` or `limits` values for vCPU and memory resources. The following are constraints for specifying vCPU resources: + At least one vCPU `requests` or `limits` value must be specified. + One vCPU unit is equivalent to one physical or virtual core. + The vCPU value must be entered in whole numbers or in increments of 0.25. + The smallest valid vCPU value is 0.25. + If both are specified, the `requests` value must be less than or equal to the `limits` value. This way, you can configure both soft and hard vCPU configurations. + vCPU values can't be specified in milliCPU form. For example, `100m` isn't a valid value. + AWS Batch uses the `requests` value for scaling decisions. If a `requests` value isn't specified, the `limits` value is copied to the `requests` value. The following are constraints for specifying memory resources: + At least one memory `requests` or `limits` value must be specified. + Memory values must be in mebibytes (MiBs). + If both are specified, the `requests` value must be equal to the `limits` value. + AWS Batch uses the `requests` value for scaling decisions. If a `requests` value is not specified, the `limits` value is copied to the `requests` value. The following are constraints for specifying GPU resources: + If both are specified, the `requests` value must be equal to the `limits` value. + AWS Batch uses the `requests` value for scaling decisions. If a `requests` value isn't specified, the `limits` value is copied to the `requests` value. ## Example: job definitions The following AWS Batch on Amazon EKS job definition configures soft vCPU shares. This lets AWS Batch on Amazon EKS use all of the vCPU capacity for the instance type. However, if there are other jobs running, the job is allocated a maximum of `2` vCPUs. Memory is limited to 2 GB. ``` { "jobDefinitionName": "MyJobOnEks_Sleep", "type": "container", "eksProperties": { "podProperties": { "containers": [ { "image": "public.ecr.aws/amazonlinux/amazonlinux:2", "command": ["sleep", "60"], "resources": { "requests": { "cpu": "2", "memory": "2048Mi" } } } ] } } } ``` The following AWS Batch on Amazon EKS job definition has a `request` value of `1` and allocates a maximum of `4` vCPUs to the job. ``` { "jobDefinitionName": "MyJobOnEks_Sleep", "type": "container", "eksProperties": { "podProperties": { "containers": [ { "image": "public.ecr.aws/amazonlinux/amazonlinux:2", "command": ["sleep", "60"], "resources": { "requests": { "cpu": "1" }, "limits": { "cpu": "4", "memory": "2048Mi" } } } ] } } } ``` The following AWS Batch on Amazon EKS job definition sets a vCPU `limits` value of `1` and a memory `limits` value of 1 GB. ``` { "jobDefinitionName": "MyJobOnEks_Sleep", "type": "container", "eksProperties": { "podProperties": { "containers": [ { "image": "public.ecr.aws/amazonlinux/amazonlinux:2", "command": ["sleep", "60"], "resources": { "limits": { "cpu": "1", "memory": "1024Mi" } } } ] } } } ``` When AWS Batch translates an AWS Batch on Amazon EKS job into an Amazon EKS pod, AWS Batch copies the`limits` value to the `requests` value. This is if a `requests` value isn't specified. When you submit the preceding example job definition, the pod `spec` is as follows. ``` apiVersion: v1 kind: Pod ... spec: ... containers: - command: - sleep - 60 image: public.ecr.aws/amazonlinux/amazonlinux:2 resources: limits: cpu: 1 memory: 1024Mi requests: cpu: 1 memory: 1024Mi ... ``` ## Node CPU and memory reservations AWS Batch relies on the default logic of the `bootstrap.sh` file for vCPU and memory reservations. For more information about the `bootstrap.sh` file, see [bootstrap.sh](https://github.com/awslabs/amazon-eks-ami/blob/main/templates/al2/runtime/bootstrap.sh). When you size your vCPU and memory resources, consider the examples that follow. **Note** If no instances are running, vCPU and memory reservations can initially affect AWS Batch scaling logic and decision making. After the instances are running, AWS Batch adjusts the initial allocations. ## Example: Node CPU reservation The CPU reservation value is calculated in millicores using the total number of vCPUs that are available to the instance. | vCPU number | Percentage reserved | | --- | --- | | 1 | 6% | | 2 | 1% | | 3-4 | 0.5% | | 4 and above | 0.25% | Using the preceding values, the following is true: + The CPU reservation value for a `c5.large` instance with 2 vCPUs is 70 m. This is calculated in the following way: *(1\$160) \$1 (1\$110) = 70 m*. + The CPU reservation value for a `c5.24xlarge` instance with 96 vCPUs is 310 m. This is calculated in the following way: (1\$160) \$1 (1\$110) \$1 (2\$15) \$1 (92\$12.5) = 310 m. In this example, there are 1930 (calculated 2000-70) millicore vCPU units available to run jobs on a `c5.large` instance. Suppose your job requires `2` (2\$11000 m) vCPU units, the job doesn't fit on a single `c5.large` instance. However, a job that requires `1.75` vCPU units fits. ## Example: Node memory reservation The memory reservation value is calculated in mebibytes using the following: + The instance capacity in mebibytes. For example, an 8 GB instance is 7,748 MiB. + The `kubeReserved` value. The `kubeReserved` value is the amount of memory to reserve for system daemons. The `kubeReserved` value is calculated in the following way: *((11 \$1 maximum number of pods that is supported by the instance type) \$1 255)*. For information about the maximum number of pods that's supported by an instance type, see [eni-max-pods.txt](https://github.com/awslabs/amazon-eks-ami/blob/main/nodeadm/internal/kubelet/eni-max-pods.txt) + The `HardEvictionLimit` value. When available memory falls below the `HardEvictionLimit` value, the instance attempts to evict pods. The formula to calculate the allocatable memory is as follows: (*instance\$1capacity\$1in\$1MiB*) - (11 \$1 (*maximum\$1number\$1of\$1pods*)) - 255 - (*`HardEvictionLimit` value.*)). A `c5.large` instance supports up to 29 pods. For an 8 GB `c5.large` instance with a `HardEvictionLimit` value of 100 MiB, the allocatable memory is 7074 MiB. This is calculated in the following way: *(7748 - (11 \$1 29) -255 -100) = 7074 MiB*. In this example, an 8,192 MiB job doesn't fit on this instance even though it's an 8 gibibyte (GiB) instance. ## DaemonSets When you use DaemonSets, consider the following: + If no AWS Batch on Amazon EKS instances are running, DaemonSets can initially affect AWS Batch scaling logic and decision making. AWS Batch initially allocates 0.5 vCPU units and 500 MiB for expected DaemonSets. After the instances are running, AWS Batch adjusts the initial allocations. + If a DaemonSet defines vCPU or memory limits, AWS Batch on Amazon EKS jobs have fewer resources. We recommend that you keep the number of DaemonSets that are assigned to AWS Batch jobs as low as possible.