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.

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 EC2 Container Service Developer Guide.

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.