paws.compute (version 0.1.0)

ecs_create_service: Runs and maintains a desired number of tasks from a specified task definition

Description

Runs and maintains a desired number of tasks from a specified task definition. If the number of tasks running in a service drops below the desiredCount, Amazon ECS spawns another copy of the task in the specified cluster. To update an existing service, see UpdateService.

Usage

ecs_create_service(cluster, serviceName, taskDefinition, loadBalancers,
  serviceRegistries, desiredCount, clientToken, launchType,
  platformVersion, role, deploymentConfiguration, placementConstraints,
  placementStrategy, networkConfiguration, healthCheckGracePeriodSeconds,
  schedulingStrategy, deploymentController, tags, enableECSManagedTags,
  propagateTags)

Arguments

cluster

The short name or full Amazon Resource Name (ARN) of the cluster on which to run your service. If you do not specify a cluster, the default cluster is assumed.

serviceName

[required] The name of your service. Up to 255 letters (uppercase and lowercase), numbers, hyphens, and underscores are allowed. Service names must be unique within a cluster, but you can have similarly named services in multiple clusters within a Region or across multiple Regions.

taskDefinition

The family and revision (family:revision) or full ARN of the task definition to run in your service. If a revision is not specified, the latest ACTIVE revision is used.

A task definition must be specified if the service is using the ECS deployment controller.

loadBalancers

A load balancer object representing the load balancer to use with your service.

If the service is using the ECS deployment controller, you are limited to one load balancer or target group.

If the service is using the CODE_DEPLOY deployment controller, the service is required to use either an Application Load Balancer or Network Load Balancer. When creating an AWS CodeDeploy deployment group, you specify two target groups (referred to as a targetGroupPair). During a deployment, AWS CodeDeploy determines which task set in your service has the status PRIMARY and associates one target group with it, and then associates the other target group with the replacement task set. The load balancer can also have up to two listeners: a required listener for production traffic and an optional listener that allows you perform validation tests with Lambda functions before routing production traffic to it.

After you create a service using the ECS deployment controller, the load balancer name or target group ARN, container name, and container port specified in the service definition are immutable. If you are using the CODE_DEPLOY deployment controller, these values can be changed when updating the service.

For Classic Load Balancers, this object must contain the load balancer name, the container name (as it appears in a container definition), and the container port to access from the load balancer. When a task from this service is placed on a container instance, the container instance is registered with the load balancer specified here.

For Application Load Balancers and Network Load Balancers, this object must contain the load balancer target group ARN, the container name (as it appears in a container definition), and the container port to access from the load balancer. When a task from this service is placed on a container instance, the container instance and port combination is registered as a target in the target group specified here.

Services with tasks that use the awsvpc network mode (for example, those with the Fargate launch type) only support Application Load Balancers and Network Load Balancers. Classic Load Balancers are not supported. Also, when you create any target groups for these services, you must choose ip as the target type, not instance, because tasks that use the awsvpc network mode are associated with an elastic network interface, not an Amazon EC2 instance.

serviceRegistries

The details of the service discovery registries to assign to this service. For more information, see Service Discovery.

Service discovery is supported for Fargate tasks if you are using platform version v1.1.0 or later. For more information, see AWS Fargate Platform Versions.

desiredCount

The number of instantiations of the specified task definition to place and keep running on your cluster.

clientToken

Unique, case-sensitive identifier that you provide to ensure the idempotency of the request. Up to 32 ASCII characters are allowed.

launchType

The launch type on which to run your service. For more information, see Amazon ECS Launch Types in the Amazon Elastic Container Service Developer Guide.

platformVersion

The platform version that your tasks in the service are running on. A platform version is specified only for tasks using the Fargate launch type. If one isn't specified, the LATEST platform version is used by default. For more information, see AWS Fargate Platform Versions in the Amazon Elastic Container Service Developer Guide.

role

The name or full Amazon Resource Name (ARN) of the IAM role that allows Amazon ECS to make calls to your load balancer on your behalf. This parameter is only permitted if you are using a load balancer with your service and your task definition does not use the awsvpc network mode. If you specify the role parameter, you must also specify a load balancer object with the loadBalancers parameter.

If your account has already created the Amazon ECS service-linked role, that role is used by default for your service unless you specify a role here. The service-linked role is required if your task definition uses the awsvpc network mode, in which case you should not specify a role here. For more information, see Using Service-Linked Roles for Amazon ECS in the Amazon Elastic Container Service Developer Guide.

If your specified role has a path other than /, then you must either specify the full role ARN (this is recommended) or prefix the role name with the path. For example, if a role with the name bar has a path of /foo/ then you would specify /foo/bar as the role name. For more information, see Friendly Names and Paths in the IAM User Guide.

deploymentConfiguration

Optional deployment parameters that control how many tasks run during the deployment and the ordering of stopping and starting tasks.

placementConstraints

An array of placement constraint objects to use for tasks in your service. You can specify a maximum of 10 constraints per task (this limit includes constraints in the task definition and those specified at runtime).

placementStrategy

The placement strategy objects to use for tasks in your service. You can specify a maximum of five strategy rules per service.

networkConfiguration

The network configuration for the service. This parameter is required for task definitions that use the awsvpc network mode to receive their own elastic network interface, and it is not supported for other network modes. For more information, see Task Networking in the Amazon Elastic Container Service Developer Guide.

healthCheckGracePeriodSeconds

The period of time, in seconds, that the Amazon ECS service scheduler should ignore unhealthy Elastic Load Balancing target health checks after a task has first started. This is only valid if your service is configured to use a load balancer. If your service's tasks take a while to start and respond to Elastic Load Balancing health checks, you can specify a health check grace period of up to 2,147,483,647 seconds. During that time, the ECS service scheduler ignores health check status. This grace period can prevent the ECS service scheduler from marking tasks as unhealthy and stopping them before they have time to come up.

schedulingStrategy

The scheduling strategy to use for the service. For more information, see Services.

There are two service scheduler strategies available:

  • REPLICA-The replica scheduling strategy places and maintains the desired number of tasks across your cluster. By default, the service scheduler spreads tasks across Availability Zones. You can use task placement strategies and constraints to customize task placement decisions. This scheduler strategy is required if the service is using the CODE_DEPLOY or EXTERNAL deployment controller types.

  • DAEMON-The daemon scheduling strategy deploys exactly one task on each active container instance that meets all of the task placement constraints that you specify in your cluster. When you're using this strategy, you don't need to specify a desired number of tasks, a task placement strategy, or use Service Auto Scaling policies.

    Tasks using the Fargate launch type or the CODE_DEPLOY or EXTERNAL deployment controller types don't support the DAEMON scheduling strategy.

deploymentController

The deployment controller to use for the service.

tags

The metadata that you apply to the service to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. When a service is deleted, the tags are deleted as well. Tag keys can have a maximum character length of 128 characters, and tag values can have a maximum length of 256 characters.

enableECSManagedTags

Specifies whether to enable Amazon ECS managed tags for the tasks within the service. For more information, see Tagging Your Amazon ECS Resources in the Amazon Elastic Container Service Developer Guide.

propagateTags

Specifies whether to propagate the tags from the task definition or the service to the tasks in the service. If no value is specified, the tags are not propagated. Tags can only be propagated to the tasks within the service during service creation. To add tags to a task after service creation, use the TagResource API action.

Request syntax

svc$create_service(
  cluster = "string",
  serviceName = "string",
  taskDefinition = "string",
  loadBalancers = list(
    list(
      targetGroupArn = "string",
      loadBalancerName = "string",
      containerName = "string",
      containerPort = 123
    )
  ),
  serviceRegistries = list(
    list(
      registryArn = "string",
      port = 123,
      containerName = "string",
      containerPort = 123
    )
  ),
  desiredCount = 123,
  clientToken = "string",
  launchType = "EC2"|"FARGATE",
  platformVersion = "string",
  role = "string",
  deploymentConfiguration = list(
    maximumPercent = 123,
    minimumHealthyPercent = 123
  ),
  placementConstraints = list(
    list(
      type = "distinctInstance"|"memberOf",
      expression = "string"
    )
  ),
  placementStrategy = list(
    list(
      type = "random"|"spread"|"binpack",
      field = "string"
    )
  ),
  networkConfiguration = list(
    awsvpcConfiguration = list(
      subnets = list(
        "string"
      ),
      securityGroups = list(
        "string"
      ),
      assignPublicIp = "ENABLED"|"DISABLED"
    )
  ),
  healthCheckGracePeriodSeconds = 123,
  schedulingStrategy = "REPLICA"|"DAEMON",
  deploymentController = list(
    type = "ECS"|"CODE_DEPLOY"|"EXTERNAL"
  ),
  tags = list(
    list(
      key = "string",
      value = "string"
    )
  ),
  enableECSManagedTags = TRUE|FALSE,
  propagateTags = "TASK_DEFINITION"|"SERVICE"
)

Details

In addition to maintaining the desired count of tasks in your service, you can optionally run your service behind a load balancer. The load balancer distributes traffic across the tasks that are associated with the service. For more information, see Service Load Balancing in the Amazon Elastic Container Service Developer Guide.

Tasks for services that do not use a load balancer are considered healthy if they're in the RUNNING state. Tasks for services that do use a load balancer are considered healthy if they're in the RUNNING state and the container instance that they're hosted on is reported as healthy by the load balancer.

There are two service scheduler strategies available:

  • REPLICA - The replica scheduling strategy places and maintains the desired number of tasks across your cluster. By default, the service scheduler spreads tasks across Availability Zones. You can use task placement strategies and constraints to customize task placement decisions. For more information, see Service Scheduler Concepts in the Amazon Elastic Container Service Developer Guide.

  • DAEMON - The daemon scheduling strategy deploys exactly one task on each active container instance that meets all of the task placement constraints that you specify in your cluster. When using this strategy, you don't need to specify a desired number of tasks, a task placement strategy, or use Service Auto Scaling policies. For more information, see Service Scheduler Concepts in the Amazon Elastic Container Service Developer Guide.

You can optionally specify a deployment configuration for your service. The deployment is triggered by changing properties, such as the task definition or the desired count of a service, with an UpdateService operation. The default value for a replica service for minimumHealthyPercent is 100%. The default value for a daemon service for minimumHealthyPercent is 0%.

If a service is using the ECS deployment controller, the minimum healthy percent represents a lower limit on the number of tasks in a service that must remain in the RUNNING state during a deployment, as a percentage of the desired number of tasks (rounded up to the nearest integer), and while any container instances are in the DRAINING state if the service contains tasks using the EC2 launch type. This parameter enables you to deploy without using additional cluster capacity. For example, if your service has a desired number of four tasks and a minimum healthy percent of 50%, the scheduler might stop two existing tasks to free up cluster capacity before starting two new tasks. Tasks for services that do not use a load balancer are considered healthy if they're in the RUNNING state. Tasks for services that do use a load balancer are considered healthy if they're in the RUNNING state and they're reported as healthy by the load balancer. The default value for minimum healthy percent is 100%.

If a service is using the ECS deployment controller, the maximum percent parameter represents an upper limit on the number of tasks in a service that are allowed in the RUNNING or PENDING state during a deployment, as a percentage of the desired number of tasks (rounded down to the nearest integer), and while any container instances are in the DRAINING state if the service contains tasks using the EC2 launch type. This parameter enables you to define the deployment batch size. For example, if your service has a desired number of four tasks and a maximum percent value of 200%, the scheduler may start four new tasks before stopping the four older tasks (provided that the cluster resources required to do this are available). The default value for maximum percent is 200%.

If a service is using either the CODE_DEPLOY or EXTERNAL deployment controller types and tasks that use the EC2 launch type, the minimum healthy percent and maximum percent values are used only to define the lower and upper limit on the number of the tasks in the service that remain in the RUNNING state while the container instances are in the DRAINING state. If the tasks in the service use the Fargate launch type, the minimum healthy percent and maximum percent values aren't used, although they're currently visible when describing your service.

When creating a service that uses the EXTERNAL deployment controller, you can specify only parameters that aren't controlled at the task set level. The only required parameter is the service name. You control your services using the CreateTaskSet operation. For more information, see Amazon ECS Deployment Types in the Amazon Elastic Container Service Developer Guide.

When the service scheduler launches new tasks, it determines task placement in your cluster using the following logic:

  • Determine which of the container instances in your cluster can support your service's task definition (for example, they have the required CPU, memory, ports, and container instance attributes).

  • By default, the service scheduler attempts to balance tasks across Availability Zones in this manner (although you can choose a different placement strategy) with the placementStrategy parameter):

  • Sort the valid container instances, giving priority to instances that have the fewest number of running tasks for this service in their respective Availability Zone. For example, if zone A has one running service task and zones B and C each have zero, valid container instances in either zone B or C are considered optimal for placement.

  • Place the new service task on a valid container instance in an optimal Availability Zone (based on the previous steps), favoring container instances with the fewest number of running tasks for this service.

Examples

Run this code
# NOT RUN {
# This example creates a service in your default region called
# ``ecs-simple-service``. The service uses the ``hello_world`` task
# definition and it maintains 10 copies of that task.
# }
# NOT RUN {
svc$create_service(
  desiredCount = 10L,
  serviceName = "ecs-simple-service",
  taskDefinition = "hello_world"
)
# }
# NOT RUN {
# This example creates a service in your default region called
# ``ecs-simple-service-elb``. The service uses the ``ecs-demo`` task
# definition and it maintains 10 copies of that task. You must reference
# an existing load balancer in the same region by its name.
# }
# NOT RUN {
svc$create_service(
  desiredCount = 10L,
  loadBalancers = list(
    list(
      containerName = "simple-app",
      containerPort = 80L,
      loadBalancerName = "EC2Contai-EcsElast-15DCDAURT3ZO2"
    )
  ),
  role = "ecsServiceRole",
  serviceName = "ecs-simple-service-elb",
  taskDefinition = "console-sample-app-static"
)
# }
# NOT RUN {
# }

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