AWS::Batch::ComputeEnvironment
The AWS::Batch::ComputeEnvironment
resource defines your AWS Batch compute environment. You can
define MANAGED
or UNMANAGED
compute environments. MANAGED
compute environments
can use Amazon EC2 or AWS Fargate resources. UNMANAGED
compute environments can only use EC2 resources.
For more information, see Compute
Environments in the AWS Batch User Guide.
In a managed compute environment, AWS Batch manages the capacity and instance types of the compute resources within the environment. This is based on the compute resource specification that you define or the launch template that you specify when you create the compute environment. You can choose either to use EC2 On-Demand Instances and EC2 Spot Instances, or to use Fargate and Fargate Spot capacity in your managed compute environment. You can optionally set a maximum price so that Spot Instances only launch when the Spot Instance price is below a specified percentage of the On-Demand price.
Multi-node parallel jobs are not supported on Spot Instances.
In an unmanaged compute environment, you can manage your own EC2 compute resources and have a lot of flexibility with how you configure your compute resources. For example, you can use custom AMI. However, you need to verify that your AMI meets the Amazon ECS container instance AMI specification. For more information, see container instance AMIs in the Amazon Elastic Container Service Developer Guide. After you have created your unmanaged compute environment, you can use the DescribeComputeEnvironments operation to find the Amazon ECS cluster that is associated with it. Then, manually launch your container instances into that Amazon ECS cluster. For more information, see Launching an Amazon ECS container instance in the Amazon Elastic Container Service Developer Guide.
AWS Batch doesn't upgrade the AMIs in a compute environment after it's created. For example, it doesn't update the AMIs when a newer version of the Amazon ECS optimized AMI is available. Therefore, you're responsible for the management of the guest operating system (including updates and security patches) and any additional application software or utilities that you install on the compute resources. To use a new AMI for your AWS Batch jobs, complete these steps:
-
Create a new compute environment with the new AMI.
-
Add the compute environment to an existing job queue.
-
Remove the earlier compute environment from your job queue.
-
Delete the earlier compute environment.
Syntax
To declare this entity in your AWS CloudFormation template, use the following syntax:
JSON
{ "Type" : "AWS::Batch::ComputeEnvironment", "Properties" : { "ComputeEnvironmentName" :
String
, "ComputeResources" :ComputeResources
, "ServiceRole" :String
, "State" :String
, "Tags" :Json
, "Type" :String
} }
YAML
Type: AWS::Batch::ComputeEnvironment Properties: ComputeEnvironmentName:
String
ComputeResources:ComputeResources
ServiceRole:String
State:String
Tags:Json
Type:String
Properties
ComputeEnvironmentName
-
The name for your compute environment. Up to 128 letters (uppercase and lowercase), numbers, hyphens, and underscores are allowed.
Required: No
Type: String
Update requires: Replacement
ComputeResources
-
The ComputeResources property type specifies details of the compute resources managed by the compute environment. This parameter is required for managed compute environments. For more information, see Compute Environments in the AWS Batch User Guide.
Required: No
Type: ComputeResources
Update requires: No interruption
ServiceRole
-
The full Amazon Resource Name (ARN) of the IAM role that allows AWS Batch to make calls to other AWS services on your behalf. For more information, see AWS Batch service IAM role in the AWS Batch User Guide.
If your specified role has a path other than
/
, then you must specify either the full role ARN (recommended) or prefix the role name with the path.Note Depending on how you created your AWS Batch service role, its ARN might contain the
service-role
path prefix. When you only specify the name of the service role, AWS Batch assumes that your ARN doesn't use theservice-role
path prefix. Because of this, we recommend that you specify the full ARN of your service role when you create compute environments.Required: Yes
Type: String
Update requires: No interruption
State
-
The state of the compute environment. If the state is
ENABLED
, then the compute environment accepts jobs from a queue and can scale out automatically based on queues.If the state is
ENABLED
, then the AWS Batch scheduler can attempt to place jobs from an associated job queue on the compute resources within the environment. If the compute environment is managed, then it can scale its instances out or in automatically, based on the job queue demand.If the state is
DISABLED
, then the AWS Batch scheduler doesn't attempt to place jobs within the environment. Jobs in aSTARTING
orRUNNING
state continue to progress normally. Managed compute environments in theDISABLED
state don't scale out. However, they scale in tominvCpus
value after instances become idle.Required: No
Type: String
Allowed values:
DISABLED | ENABLED
Update requires: No interruption
Tags
-
The tags applied to the compute environment.
Required: No
Type: Json
Update requires: Replacement
Type
-
The type of the compute environment:
MANAGED
orUNMANAGED
. For more information, see Compute Environments in the AWS Batch User Guide.Required: Yes
Type: String
Allowed values:
MANAGED | UNMANAGED
Update requires: Replacement
Return values
Ref
When you pass the logical ID of this resource to the intrinsic Ref
function, Ref
returns the compute environment ARN, such as
arn:aws:batch:us-east-1:555555555555:compute-environment/M4OnDemand
.
For more information about using the Ref
function, see Ref.
Examples
Managed Compute Environment
The following example creates a managed compute environment called C4OnDemand
that uses C4
On-Demand instances and a custom AMI.
JSON
{ "ComputeEnvironment": { "Type": "AWS::Batch::ComputeEnvironment", "Properties": { "Type": "MANAGED", "ServiceRole": "arn:aws:iam::111122223333:role/service-role/AWSBatchServiceRole", "ComputeEnvironmentName": "C4OnDemand", "ComputeResources": { "MaxvCpus": 128, "SecurityGroupIds": [ "sg-abcd1234" ], "Type": "EC2", "Subnets": [ "subnet-aaaaaaaa", "subnet-bbbbbbbb", "subnet-cccccccc" ], "MinvCpus": 0, "ImageId": "ami-a1b2c3d4", "InstanceRole": "ecsInstanceRole", "InstanceTypes": [ "c4.large", "c4.xlarge", "c4.2xlarge", "c4.4xlarge", "c4.8xlarge" ], "Ec2KeyPair": "id_rsa", "Tags": { "Name": "Batch Instance - C4OnDemand" }, "DesiredvCpus": 48 }, "State": "ENABLED" } } }
YAML
ComputeEnvironment: Type: AWS::Batch::ComputeEnvironment Properties: Type: MANAGED ServiceRole: arn:aws:iam::111122223333:role/service-role/AWSBatchServiceRole ComputeEnvironmentName: C4OnDemand ComputeResources: MaxvCpus: 128 SecurityGroupIds: - sg-abcd1234 Type: EC2 Subnets: - subnet-aaaaaaaa - subnet-bbbbbbbb - subnet-cccccccc MinvCpus: 0 ImageId: ami-a1b2c3d4 InstanceRole: ecsInstanceRole InstanceTypes: - c4.large - c4.xlarge - c4.2xlarge - c4.4xlarge - c4.8xlarge Ec2KeyPair: id_rsa Tags: {"Name" : "Batch Instance - C4OnDemand"} DesiredvCpus: 48 State: ENABLED
See also
-
Compute Environments in the AWS Batch User Guide.