updateService (original) (raw)

Modifies the parameters of a service.

On March 21, 2024, a change was made to resolve the task definition revision before authorization. When a task definition revision is not specified, authorization will occur using the latest revision of a task definition.

For services using the rolling update (ECS) you can update the desired count, deployment configuration, network configuration, load balancers, service registries, enable ECS managed tags option, propagate tags option, task placement constraints and strategies, and task definition. When you update any of these parameters, Amazon ECS starts new tasks with the new configuration.

You can attach Amazon EBS volumes to Amazon ECS tasks by configuring the volume when starting or running a task, or when creating or updating a service. For more infomation, see Amazon EBS volumes in the Amazon Elastic Container Service Developer Guide. You can update your volume configurations and trigger a new deployment. volumeConfigurations is only supported for REPLICA service and not DAEMON service. If you leave volumeConfigurations``null, it doesn't trigger a new deployment. For more infomation on volumes, see Amazon EBS volumes in the Amazon Elastic Container Service Developer Guide.

For services using the blue/green (CODE_DEPLOY) deployment controller, only the desired count, deployment configuration, health check grace period, task placement constraints and strategies, enable ECS managed tags option, and propagate tags can be updated using this API. If the network configuration, platform version, task definition, or load balancer need to be updated, create a new CodeDeploy deployment. For more information, see CreateDeployment in the CodeDeploy API Reference.

For services using an external deployment controller, you can update only the desired count, task placement constraints and strategies, health check grace period, enable ECS managed tags option, and propagate tags option, using this API. If the launch type, load balancer, network configuration, platform version, or task definition need to be updated, create a new task set For more information, see CreateTaskSet.

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.

If you have updated the container image of your application, you can create a new task definition with that image and deploy it to your service. The service scheduler uses the minimum healthy percent and maximum percent parameters (in the service's deployment configuration) to determine the deployment strategy.

If your updated Docker image uses the same tag as what is in the existing task definition for your service (for example, my_image:latest), you don't need to create a new revision of your task definition. You can update the service using the forceNewDeployment option. The new tasks launched by the deployment pull the current image/tag combination from your repository when they start.

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 minimumHealthyPercent is below 100%, the scheduler can ignore desiredCount temporarily during a deployment. For example, if desiredCount is four tasks, a minimum of 50% allows the scheduler to stop two existing tasks before starting two new tasks. Tasks for services that don't use a load balancer are considered healthy if they're in the RUNNING state. Tasks for services that use a load balancer are considered healthy if they're in the RUNNING state and are reported as healthy by the load balancer.
The maximumPercent parameter represents an upper limit on the number of running tasks during a deployment. You can use it to define the deployment batch size. For example, if desiredCount is four tasks, a maximum 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 this, 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 determines task placement 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.
By default, the service scheduler attempts to balance tasks across Availability Zones in this manner even though you can choose a different placement strategy.
- 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.

When the service scheduler stops running tasks, it attempts to maintain balance across the Availability Zones in your cluster using the following logic:

Sort the container instances by the largest 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 two, container instances in either zone B or C are considered optimal for termination.
Stop the task on a container instance in an optimal Availability Zone (based on the previous steps), favoring container instances with the largest number of running tasks for this service.

Samples


fun main() { 
   //sampleStart 
   // This example updates the desired count of the my http service service to 10.
val resp = ecsClient.updateService {
    service = "my-http-service"
    desiredCount = 10
} 
   //sampleEnd
}


fun main() { 
   //sampleStart 
   // This example updates the my http service service to use the amazon ecs sample task definition.
val resp = ecsClient.updateService {
    service = "my-http-service"
    taskDefinition = "amazon-ecs-sample"
} 
   //sampleEnd
}