Modifies the parameters of a service.
ecs_update_service(cluster, service, desiredCount, taskDefinition,
deploymentConfiguration, networkConfiguration, platformVersion,
forceNewDeployment, healthCheckGracePeriodSeconds)The short name or full Amazon Resource Name (ARN) of the cluster that your service is running on. If you do not specify a cluster, the default cluster is assumed.
[required] The name of the service to update.
The number of instantiations of the task to place and keep running in your service.
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. If you modify the task definition with
UpdateService, Amazon ECS spawns a task with the new version of the
task definition and then stops an old task after the new version is
running.
Optional deployment parameters that control how many tasks run during the deployment and the ordering of stopping and starting tasks.
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.
Updating a service to add a subnet to a list of existing subnets does not trigger a service deployment. For example, if your network configuration change is to keep the existing subnets and simply add another subnet to the network configuration, this does not trigger a new service deployment.
The platform version on which your tasks in the service are running. A
platform version is only specified for tasks using the Fargate launch
type. If one is not 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.
Whether to force a new deployment of the service. Deployments are not
forced by default. You can use this option to trigger a new deployment
with no service definition changes. For example, you can update a
service's tasks to use a newer Docker image with the same image/tag
combination (my_image:latest) or to roll Fargate tasks onto a newer
platform version.
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 1,800 seconds. During that time, the ECS service scheduler ignores the Elastic Load Balancing 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.
svc$update_service(
cluster = "string",
service = "string",
desiredCount = 123,
taskDefinition = "string",
deploymentConfiguration = list(
maximumPercent = 123,
minimumHealthyPercent = 123
),
networkConfiguration = list(
awsvpcConfiguration = list(
subnets = list(
"string"
),
securityGroups = list(
"string"
),
assignPublicIp = "ENABLED"|"DISABLED"
)
),
platformVersion = "string",
forceNewDeployment = TRUE|FALSE,
healthCheckGracePeriodSeconds = 123
)
For services using the rolling update (ECS) deployment controller, the
desired count, deployment configuration, network configuration, or task
definition used can be updated.
For services using the blue/green (CODE_DEPLOY) deployment controller,
only the desired count, deployment configuration, and health check grace
period can be updated using this API. If the network configuration,
platform version, or task definition need to be updated, a new AWS
CodeDeploy deployment should be created. For more information, see
CreateDeployment
in the AWS CodeDeploy API Reference.
For services using an external deployment controller, you can update only the desired count and health check grace period using this API. If the launch type, load balancer, network configuration, platform version, or task definition need to be updated, you should 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 Docker 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 do not 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 do not use a load balancer are considered healthy if
they are in the RUNNING state. Tasks for services that use a load
balancer are considered healthy if they are in the RUNNING state
and the container instance they are 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 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 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 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 (although 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.
# NOT RUN {
# This example updates the my-http-service service to use the
# amazon-ecs-sample task definition.
# }
# NOT RUN {
svc$update_service(
service = "my-http-service",
taskDefinition = "amazon-ecs-sample"
)
# }
# NOT RUN {
# This example updates the desired count of the my-http-service service to
# 10.
# }
# NOT RUN {
svc$update_service(
desiredCount = 10L,
service = "my-http-service"
)
# }
# NOT RUN {
# }
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