Amazon ECS services
You can use an Amazon ECS service to run and maintain a specified number of instances of a task definition simultaneously in an Amazon ECS cluster. If one of your tasks fails or stops, the Amazon ECS service scheduler launches another instance of your task definition to replace it. This helps maintain your desired number of tasks in the service.
You can also optionally run your service behind a load balancer. The load balancer distributes traffic across the tasks that are associated with the service.
We recommend that you use the service scheduler for long running stateless services and applications. The service scheduler ensures that the scheduling strategy that you specify is followed and reschedules tasks when a task fails. For example, if the underlying infrastructure fails, the service scheduler reschedules a task. You can use task placement strategies and constraints to customize how the scheduler places and terminates tasks. If a task in a service stops, the scheduler launches a new task to replace it. This process continues until your service reaches your desired number of tasks based on the scheduling strategy that the service uses. The scheduling strategy of the service is also referred to as the service type.
The service scheduler also replaces tasks determined to be unhealthy after a container health check or a load balancer target group health check fails. This replacement depends on the maximumPercent
and desiredCount
service definition parameters.
If a task is marked unhealthy, the service scheduler will first start a replacement task. Then, the following happens.
If the replacement task has a health status of
HEALTHY
, the service scheduler stops the unhealthy taskIf the replacement task has a health status of
UNHEALTHY
, the scheduler will stop either the unhealthy replacement task or the existing unhealthy task to get the total task count to equaldesiredCount
.
If the maximumPercent
parameter limits the scheduler from starting a replacement task first, the scheduler will stop an unhealthy task one at a time at random to free up capacity, and then start a replacement task.
The start and stop process continues until all unhealthy tasks are replaced with healthy tasks. Once all unhealthy tasks have been replaced and only healthy tasks are running, if the total task count exceeds the desiredCount
, healthy tasks are stopped at random until the total task count equals desiredCount
. For more information about maximumPercent
and desiredCount
, see Service definition parameters.
The service scheduler includes logic that throttles how often tasks are restarted if
tasks repeatedly fail to start. If a task is stopped without having entered a
RUNNING
state, the service scheduler starts to slow down the launch
attempts and sends out a service event message. This behavior prevents unnecessary
resources from being used for failed tasks before you can resolve the issue. After the
service is updated, the service scheduler resumes normal scheduling behavior. For more
information, see Amazon ECS service throttle logic and Viewing Amazon ECS service event messages.
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 Replica strategy. -
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, there is no need to specify a desired number of tasks, a task placement strategy, or use Service Auto Scaling policies. For more information, see Daemon strategy.Note
Fargate tasks do not support the
DAEMON
scheduling strategy.
Daemon strategy
The daemon scheduling strategy deploys exactly one task on each active container instance that meets all of the task placement constraints specified in your cluster. The service scheduler evaluates the task placement constraints for running tasks, and stops tasks that don't meet the placement constraints. When you use this strategy, you don't need to specify a desired number of tasks, a task placement strategy, or use Service Auto Scaling policies.
Amazon ECS reserves container instance compute resources including CPU, memory, and network interfaces for the daemon tasks. When you launch a daemon service on a cluster with other replica services, Amazon ECS prioritizes the daemon task. This means that the daemon task is the first task to launch on the instances and the last task to stop after all replica tasks are stopped. . This strategy ensures that resources aren't used by pending replica tasks and are available for the daemon tasks.
The daemon service scheduler doesn't place any tasks on instances that have a
DRAINING
status. If a container instance transitions to a
DRAINING
status, the daemon tasks on it are stopped. The service
scheduler also monitors when new container instances are added to your cluster and
adds the daemon tasks to them.
When you specify a deployment configuration, the value for the
maximumPercent
parameter must be 100
(specified as a
percentage), which is the default value used if not set. The default value for the
minimumHealthyPercent
parameter is 0
(specified as a
percentage).
You must restart the service when you change the placement constraints for the daemon service. Amazon ECS dynamically updates the resources that are reserved on qualifying instances for the daemon task. For existing instances, the scheduler tries to place the task on the instance.
A new deployment starts when there is a change to the task size or container resource reservation in the task definition. A new deployment also starts when updating a service or setting a different revision of the task definition. Amazon ECS picks up the updated CPU and memory reservations for the daemon, and then blocks that capacity for the daemon task.
If there are insufficient resources for either of the above cases, the following happens:
-
The task placement fails.
-
A CloudWatch event is generated.
-
Amazon ECS continues to try and schedule the task on the instance by waiting for resources to become available.
-
Amazon ECS frees up any reserved instances that no longer meet the placement constraint criteria and stops the corresponding daemon tasks.
The daemon scheduling strategy can be used in the following cases:
-
Running application containers
-
Running support containers for logging, monitoring and tracing tasks
Tasks using the Fargate launch type or the CODE_DEPLOY
or EXTERNAL
deployment controller types don't support the daemon
scheduling strategy.
When the service scheduler stops running tasks, it attempts to maintain balance across the Availability Zones in your cluster. The scheduler uses the following logic:
-
If a placement strategy is defined, use that strategy to select which tasks to terminate. For example, if a service has an Availability Zone spread strategy defined, a task is selected that leaves the remaining tasks with the best spread.
-
If no placement strategy is defined, use the following logic to maintain balance across the Availability Zones in your cluster:
-
Sort the valid container instances. Give priority to instances that have the largest 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 two running service task, 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.
-
Replica strategy
The replica scheduling strategy places and maintains the desired number of tasks in your cluster.
For a service that runs tasks on Fargate, when the service scheduler launches new tasks or stops running tasks, the service scheduler uses a best attempt to maintain a balance across Availability Zones. You don't need to specify task placement strategies or constraints.
When you create a service that runs tasks on EC2 instances, you can optionally specify task placement strategies and constraints to customize task placement decisions. If no task placement strategies or constraints are specified, then by default the service scheduler spreads the tasks across Availability Zones. The service scheduler uses the following logic:
-
Determines which of the container instances in your cluster can support your service's task definition (for example, required CPU, memory, ports, and container instance attributes).
-
Determines which container instances satisfy any placement constraints that are defined for the service.
-
When you have a replica service that depends on a daemon service (for example, a daemon log router task that needs to be running before tasks can use logging), create a task placement constraint that ensures that the daemon service tasks get placed on the EC2 instance prior to the replica service tasks. For more information, see Example Amazon ECS task placement constraints.
-
When there's a defined placement strategy, use that strategy to select an instance from the remaining candidates.
-
When there's no defined placement strategy, use the following logic to balance tasks across the Availability Zones in your cluster:
-
Sorts the valid container instances. Gives 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.
-
Places the new service task on a valid container instance in an optimal Availability Zone based on the previous steps. Favors container instances with the fewest number of running tasks for this service.
-
We recommend that you use the service rebalacing feature when you use the REPLICA
strategy because it helps ensure high availability for you service.