Creates a new Amazon ECS cluster. By default, your account receives a default cluster when you launch your first container instance. However, you can create your own cluster with a unique name with the CreateCluster action.

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

You can optionally specify a deployment configuration for your service. During a deployment (which is triggered by changing the task definition of a service with an UpdateService operation), the service scheduler uses the minimumHealthyPercent and maximumPercent parameters to determine the deployment strategy.

If the minimumHealthyPercent is below 100%, the scheduler can ignore the desiredCount temporarily during a deployment. For example, if your service has a desiredCount of four tasks, a minimumHealthyPercent of 50% allows the scheduler to stop two existing tasks before starting two new tasks. Tasks for services that do not use a load balancer are considered healthy if they are in the RUNNING state; tasks for services that do use a load balancer are considered healthy if they are in the RUNNING state and the container instance it is hosted on is reported as healthy by the load balancer. The default value for minimumHealthyPercent is 50% in the console and 100% for the AWS CLI, the AWS SDKs, and the APIs.

The maximumPercent parameter represents an upper limit on the number of running tasks during a deployment, which enables you to define the deployment batch size. For example, if your service has a desiredCount of four tasks, a maximumPercent value of 200% starts four new tasks before stopping the four older tasks (provided that the cluster resources required to do this are available). The default value for maximumPercent is 200%.

When the service scheduler launches new tasks, it attempts to balance them across the Availability Zones in your cluster with 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).
• Sort the valid container instances by the fewest number of running tasks for this service in the same Availability Zone as the instance. 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.

Deletes the specified cluster. You must deregister all container instances from this cluster before you may delete it. You can list the container instances in a cluster with ListContainerInstances and deregister them with DeregisterContainerInstance.

Deletes a specified service within a cluster. You can delete a service if you have no running tasks in it and the desired task count is zero. If the service is actively maintaining tasks, you cannot delete it, and you must update the service to a desired task count of zero. For more information, see UpdateService.

Deregisters an Amazon ECS container instance from the specified cluster. This instance is no longer available to run tasks.

If you intend to use the container instance for some other purpose after deregistration, you should stop all of the tasks running on the container instance before deregistration to avoid any orphaned tasks from consuming resources.

Deregistering a container instance removes the instance from a cluster, but it does not terminate the EC2 instance; if you are finished using the instance, be sure to terminate it in the Amazon EC2 console to stop billing.

Deregisters the specified task definition by family and revision. Upon deregistration, the task definition is marked as INACTIVE. Existing tasks and services that reference an INACTIVE task definition continue to run without disruption. Existing services that reference an INACTIVE task definition can still scale up or down by modifying the service’s desired count.

You cannot use an INACTIVE task definition to run new tasks or create new services, and you cannot update an existing service to reference an INACTIVE task definition (although there may be up to a 10 minute window following deregistration where these restrictions have not yet taken effect).

Describes one or more of your clusters.

Describes Amazon EC2 Container Service container instances. Returns metadata about registered and remaining resources on each container instance requested.

Describes the specified services running in your cluster.

Describes a task definition. You can specify a family and revision to find information about a specific task definition, or you can simply specify the family to find the latest ACTIVE revision in that family.

Describes a specified task or tasks.

poll for updates.

Returns a list of existing clusters.

Returns a list of container instances in a specified cluster.

Lists the services that are running in a specified cluster.

Returns a list of task definition families that are registered to your account (which may include task definition families that no longer have any ACTIVE task definitions). You can filter the results with the familyPrefix parameter.

Returns a list of task definitions that are registered to your account. You can filter the results by family name with the familyPrefix parameter or by status with the status parameter.

Returns a list of tasks for a specified cluster. You can filter the results by family name, by a particular container instance, or by the desired status of the task with the family, containerInstance, and desiredStatus parameters.

becomes available to place containers on.

Registers a new task definition from the supplied family and containerDefinitions. Optionally, you can add data volumes to your containers with the volumes parameter. For more information about task definition parameters and defaults, see Amazon ECS Task Definitions in the Amazon EC2 Container Service Developer Guide.

Start a task using random placement and the default Amazon ECS scheduler. To use your own scheduler or place a task on a specific container instance, use StartTask instead.

Starts a new task from the specified task definition on the specified container instance or instances. To use the default Amazon ECS scheduler to place your task, use RunTask instead.

Stops a running task.

When StopTask is called on a task, the equivalent of docker stop is issued to the containers running in the task. This results in a SIGTERM and a 30-second timeout, after which SIGKILL is sent and the containers are forcibly stopped. If the container handles the SIGTERM gracefully and exits within 30 seconds from receiving it, no SIGKILL is sent.

Updates the Amazon ECS container agent on a specified container instance. Updating the Amazon ECS container agent does not interrupt running tasks or services on the container instance. The process for updating the agent differs depending on whether your container instance was launched with the Amazon ECS-optimized AMI or another operating system.

UpdateContainerAgent requires the Amazon ECS-optimized AMI or Amazon Linux with the ecs-init service installed and running. For help updating the Amazon ECS container agent on other operating systems, see Manually Updating the Amazon ECS Container Agent in the Amazon EC2 Container Service Developer Guide.

Modifies the desired count, deployment configuration, or task definition used in a service.

You can add to or subtract from the number of instantiations of a task definition in a service by specifying the cluster that the service is running in and a new desiredCount parameter.

You can use UpdateService to modify your task definition and deploy a new version of your service.

You can also update the deployment configuration of a service. When a deployment is triggered by updating the task definition of a service, the service scheduler uses the deployment configuration parameters, minimumHealthyPercent and maximumPercent, to determine the deployment strategy.

If the minimumHealthyPercent is below 100%, the scheduler can ignore the desiredCount temporarily during a deployment. For example, if your service has a desiredCount of four tasks, a minimumHealthyPercent of 50% allows the scheduler to stop two existing tasks before starting two new tasks. Tasks for services that do not use a load balancer are considered healthy if they are in the RUNNING state; tasks for services that do use a load balancer are considered healthy if they are in the RUNNING state and the container instance it is hosted on is reported as healthy by the load balancer.

The maximumPercent parameter represents an upper limit on the number of running tasks during a deployment, which enables you to define the deployment batch size. For example, if your service has a desiredCount of four tasks, a maximumPercent value of 200% starts four new tasks before stopping the four older tasks (provided that the cluster resources required to do this are available).

When UpdateService stops a task during a deployment, the equivalent of docker stop is issued to the containers running in the task. This results in a SIGTERM and a 30-second timeout, after which SIGKILL is sent and the containers are forcibly stopped. If the container handles the SIGTERM gracefully and exits within 30 seconds from receiving it, no SIGKILL is sent.

When the service scheduler launches new tasks, it attempts to balance them across the Availability Zones in your cluster with 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).
• Sort the valid container instances by the fewest number of running tasks for this service in the same Availability Zone as the instance. 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.