Starts a new task using the specified task definition.
You can allow Amazon ECS to place tasks for you, or you can customize how Amazon ECS places tasks using placement constraints and placement strategies. For more information, see Scheduling Tasks in the Amazon Elastic Container Service Developer Guide.
Alternatively, you can use start_task to use your
own scheduler or place tasks manually on specific container instances.
The Amazon ECS API follows an eventual consistency model, due to the distributed nature of the system supporting the API. This means that the result of an API command you run that affects your Amazon ECS resources might not be immediately visible to all subsequent commands you run. Keep this in mind when you carry out an API command that immediately follows a previous API command.
To manage eventual consistency, you can do the following:
Confirm the state of the resource before you run a command to modify it. Run the DescribeTasks command using an exponential backoff algorithm to ensure that you allow enough time for the previous command to propagate through the system. To do this, run the DescribeTasks command repeatedly, starting with a couple of seconds of wait time and increasing gradually up to five minutes of wait time.
Add wait time between subsequent commands, even if the DescribeTasks command returns an accurate response. Apply an exponential backoff algorithm starting with a couple of seconds of wait time, and increase gradually up to about five minutes of wait time.
ecs_run_task(capacityProviderStrategy, cluster, count,
enableECSManagedTags, group, launchType, networkConfiguration,
overrides, placementConstraints, placementStrategy, platformVersion,
propagateTags, referenceId, startedBy, tags, taskDefinition)A list with the following syntax:
list(
tasks = list(
list(
attachments = list(
list(
id = "string",
type = "string",
status = "string",
details = list(
list(
name = "string",
value = "string"
)
)
)
),
attributes = list(
list(
name = "string",
value = "string",
targetType = "container-instance",
targetId = "string"
)
),
availabilityZone = "string",
capacityProviderName = "string",
clusterArn = "string",
connectivity = "CONNECTED"|"DISCONNECTED",
connectivityAt = as.POSIXct(
"2015-01-01"
),
containerInstanceArn = "string",
containers = list(
list(
containerArn = "string",
taskArn = "string",
name = "string",
image = "string",
imageDigest = "string",
runtimeId = "string",
lastStatus = "string",
exitCode = 123,
reason = "string",
networkBindings = list(
list(
bindIP = "string",
containerPort = 123,
hostPort = 123,
protocol = "tcp"|"udp"
)
),
networkInterfaces = list(
list(
attachmentId = "string",
privateIpv4Address = "string",
ipv6Address = "string"
)
),
healthStatus = "HEALTHY"|"UNHEALTHY"|"UNKNOWN",
cpu = "string",
memory = "string",
memoryReservation = "string",
gpuIds = list(
"string"
)
)
),
cpu = "string",
createdAt = as.POSIXct(
"2015-01-01"
),
desiredStatus = "string",
executionStoppedAt = as.POSIXct(
"2015-01-01"
),
group = "string",
healthStatus = "HEALTHY"|"UNHEALTHY"|"UNKNOWN",
inferenceAccelerators = list(
list(
deviceName = "string",
deviceType = "string"
)
),
lastStatus = "string",
launchType = "EC2"|"FARGATE",
memory = "string",
overrides = list(
containerOverrides = list(
list(
name = "string",
command = list(
"string"
),
environment = list(
list(
name = "string",
value = "string"
)
),
environmentFiles = list(
list(
value = "string",
type = "s3"
)
),
cpu = 123,
memory = 123,
memoryReservation = 123,
resourceRequirements = list(
list(
value = "string",
type = "GPU"|"InferenceAccelerator"
)
)
)
),
cpu = "string",
inferenceAcceleratorOverrides = list(
list(
deviceName = "string",
deviceType = "string"
)
),
executionRoleArn = "string",
memory = "string",
taskRoleArn = "string"
),
platformVersion = "string",
pullStartedAt = as.POSIXct(
"2015-01-01"
),
pullStoppedAt = as.POSIXct(
"2015-01-01"
),
startedAt = as.POSIXct(
"2015-01-01"
),
startedBy = "string",
stopCode = "TaskFailedToStart"|"EssentialContainerExited"|"UserInitiated",
stoppedAt = as.POSIXct(
"2015-01-01"
),
stoppedReason = "string",
stoppingAt = as.POSIXct(
"2015-01-01"
),
tags = list(
list(
key = "string",
value = "string"
)
),
taskArn = "string",
taskDefinitionArn = "string",
version = 123
)
),
failures = list(
list(
arn = "string",
reason = "string",
detail = "string"
)
)
)
The capacity provider strategy to use for the task.
A capacity provider strategy consists of one or more capacity providers
along with the base and weight to assign to them. A capacity
provider must be associated with the cluster to be used in a capacity
provider strategy. The
put_cluster_capacity_providers
API is used to associate a capacity provider with a cluster. Only
capacity providers with an ACTIVE or UPDATING status can be used.
If a capacityProviderStrategy is specified, the launchType parameter
must be omitted. If no capacityProviderStrategy or launchType is
specified, the defaultCapacityProviderStrategy for the cluster is
used.
If specifying a capacity provider that uses an Auto Scaling group, the
capacity provider must already be created. New capacity providers can be
created with the
create_capacity_provider API
operation.
To use a AWS Fargate capacity provider, specify either the FARGATE or
FARGATE_SPOT capacity providers. The AWS Fargate capacity providers
are available to all accounts and only need to be associated with a
cluster to be used.
The
put_cluster_capacity_providers
API operation is used to update the list of available capacity providers
for a cluster after the cluster is created.
The short name or full Amazon Resource Name (ARN) of the cluster on which to run your task. If you do not specify a cluster, the default cluster is assumed.
The number of instantiations of the specified task to place on your cluster. You can specify up to 10 tasks per call.
Specifies whether to enable Amazon ECS managed tags for the task. For more information, see Tagging Your Amazon ECS Resources in the Amazon Elastic Container Service Developer Guide.
The name of the task group to associate with the task. The default value is the family name of the task definition (for example, family:my-family-name).
The launch type on which to run your task. For more information, see Amazon ECS Launch Types in the Amazon Elastic Container Service Developer Guide.
If a launchType is specified, the capacityProviderStrategy parameter
must be omitted.
The network configuration for the task. 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.
A list of container overrides in JSON format that specify the name of a
container in the specified task definition and the overrides it should
receive. You can override the default command for a container (that is
specified in the task definition or Docker image) with a command
override. You can also override existing environment variables (that are
specified in the task definition or Docker image) on a container or add
new environment variables to it with an environment override.
A total of 8192 characters are allowed for overrides. This limit includes the JSON formatting characters of the override structure.
An array of placement constraint objects to use for the task. You can specify up to 10 constraints per task (including constraints in the task definition and those specified at runtime).
The placement strategy objects to use for the task. You can specify a maximum of five strategy rules per task.
The platform version the task should run. 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.
Specifies whether to propagate the tags from the task definition to the
task. If no value is specified, the tags are not propagated. Tags can
only be propagated to the task during task creation. To add tags to a
task after task creation, use the tag_resource API
action.
An error will be received if you specify the SERVICE option when
running a task.
The reference ID to use for the task.
An optional tag specified when a task is started. For example, if you
automatically trigger a task to run a batch process job, you could apply
a unique identifier for that job to your task with the startedBy
parameter. You can then identify which tasks belong to that job by
filtering the results of a list_tasks call with the
startedBy value. Up to 36 letters (uppercase and lowercase), numbers,
hyphens, and underscores are allowed.
If a task is started by an Amazon ECS service, then the startedBy
parameter contains the deployment ID of the service that starts it.
The metadata that you apply to the task to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.
The following basic restrictions apply to tags:
Maximum number of tags per resource - 50
For each resource, each tag key must be unique, and each tag key can have only one value.
Maximum key length - 128 Unicode characters in UTF-8
Maximum value length - 256 Unicode characters in UTF-8
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
Tag keys and values are case-sensitive.
Do not use aws:, AWS:, or any upper or lowercase combination of
such as a prefix for either keys or values as it is reserved for AWS
use. You cannot edit or delete tag keys or values with this prefix.
Tags with this prefix do not count against your tags per resource
limit.
[required] The family and revision (family:revision) or full ARN of the task
definition to run. If a revision is not specified, the latest ACTIVE
revision is used.
svc$run_task(
capacityProviderStrategy = list(
list(
capacityProvider = "string",
weight = 123,
base = 123
)
),
cluster = "string",
count = 123,
enableECSManagedTags = TRUE|FALSE,
group = "string",
launchType = "EC2"|"FARGATE",
networkConfiguration = list(
awsvpcConfiguration = list(
subnets = list(
"string"
),
securityGroups = list(
"string"
),
assignPublicIp = "ENABLED"|"DISABLED"
)
),
overrides = list(
containerOverrides = list(
list(
name = "string",
command = list(
"string"
),
environment = list(
list(
name = "string",
value = "string"
)
),
environmentFiles = list(
list(
value = "string",
type = "s3"
)
),
cpu = 123,
memory = 123,
memoryReservation = 123,
resourceRequirements = list(
list(
value = "string",
type = "GPU"|"InferenceAccelerator"
)
)
)
),
cpu = "string",
inferenceAcceleratorOverrides = list(
list(
deviceName = "string",
deviceType = "string"
)
),
executionRoleArn = "string",
memory = "string",
taskRoleArn = "string"
),
placementConstraints = list(
list(
type = "distinctInstance"|"memberOf",
expression = "string"
)
),
placementStrategy = list(
list(
type = "random"|"spread"|"binpack",
field = "string"
)
),
platformVersion = "string",
propagateTags = "TASK_DEFINITION"|"SERVICE",
referenceId = "string",
startedBy = "string",
tags = list(
list(
key = "string",
value = "string"
)
),
taskDefinition = "string"
)
if (FALSE) {
# This example runs the specified task definition on your default cluster.
svc$run_task(
cluster = "default",
taskDefinition = "sleep360:1"
)
}
Run the code above in your browser using DataLab