Metadata-Version: 2.1
Name: aws-cdk.aws-ecs
Version: 1.57.0
Summary: The CDK Construct Library for AWS::ECS
Home-page: https://github.com/aws/aws-cdk
Author: Amazon Web Services
License: Apache-2.0
Project-URL: Source, https://github.com/aws/aws-cdk.git
Description: ## Amazon ECS Construct Library
        
        <!--BEGIN STABILITY BANNER-->---
        
        
        ![cfn-resources: Stable](https://img.shields.io/badge/cfn--resources-stable-success.svg?style=for-the-badge)
        
        ![cdk-constructs: Stable](https://img.shields.io/badge/cdk--constructs-stable-success.svg?style=for-the-badge)
        
        ---
        <!--END STABILITY BANNER-->
        
        This package contains constructs for working with **Amazon Elastic Container
        Service** (Amazon ECS).
        
        Amazon ECS is a highly scalable, fast, container management service
        that makes it easy to run, stop,
        and manage Docker containers on a cluster of Amazon EC2 instances.
        
        For further information on Amazon ECS,
        see the [Amazon ECS documentation](https://docs.aws.amazon.com/ecs)
        
        The following example creates an Amazon ECS cluster,
        adds capacity to it,
        and instantiates the Amazon ECS Service with an automatic load balancer.
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_ecs as ecs
        
        # Create an ECS cluster
        cluster = ecs.Cluster(self, "Cluster",
            vpc=vpc
        )
        
        # Add capacity to it
        cluster.add_capacity("DefaultAutoScalingGroupCapacity",
            instance_type=ec2.InstanceType("t2.xlarge"),
            desired_capacity=3
        )
        
        task_definition = ecs.Ec2TaskDefinition(self, "TaskDef")
        
        task_definition.add_container("DefaultContainer",
            image=ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample"),
            memory_limit_mi_b=512
        )
        
        # Instantiate an Amazon ECS Service
        ecs_service = ecs.Ec2Service(self, "Service",
            cluster=cluster,
            task_definition=task_definition
        )
        ```
        
        For a set of constructs defining common ECS architectural patterns, see the `@aws-cdk/aws-ecs-patterns` package.
        
        ## Launch Types: AWS Fargate vs Amazon EC2
        
        There are two sets of constructs in this library; one to run tasks on Amazon EC2 and
        one to run tasks on AWS Fargate.
        
        * Use the `Ec2TaskDefinition` and `Ec2Service` constructs to run tasks on Amazon EC2 instances running in your account.
        * Use the `FargateTaskDefinition` and `FargateService` constructs to run tasks on
          instances that are managed for you by AWS.
        
        Here are the main differences:
        
        * **Amazon EC2**: instances are under your control. Complete control of task to host
          allocation. Required to specify at least a memory reseration or limit for
          every container. Can use Host, Bridge and AwsVpc networking modes. Can attach
          Classic Load Balancer. Can share volumes between container and host.
        * **AWS Fargate**: tasks run on AWS-managed instances, AWS manages task to host
          allocation for you. Requires specification of memory and cpu sizes at the
          taskdefinition level. Only supports AwsVpc networking modes and
          Application/Network Load Balancers. Only the AWS log driver is supported.
          Many host features are not supported such as adding kernel capabilities
          and mounting host devices/volumes inside the container.
        
        For more information on Amazon EC2 vs AWS Fargate and networking see the AWS Documentation:
        [AWS Fargate](https://docs.aws.amazon.com/AmazonECS/latest/developerguide/AWS_Fargate.html) and
        [Task Networking](https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task-networking.html).
        
        ## Clusters
        
        A `Cluster` defines the infrastructure to run your
        tasks on. You can run many tasks on a single cluster.
        
        The following code creates a cluster that can run AWS Fargate tasks:
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        cluster = ecs.Cluster(self, "Cluster",
            vpc=vpc
        )
        ```
        
        To use tasks with Amazon EC2 launch-type, you have to add capacity to
        the cluster in order for tasks to be scheduled on your instances.  Typically,
        you add an AutoScalingGroup with instances running the latest
        Amazon ECS-optimized AMI to the cluster. There is a method to build and add such an
        AutoScalingGroup automatically, or you can supply a customized AutoScalingGroup
        that you construct yourself. It's possible to add multiple AutoScalingGroups
        with various instance types.
        
        The following example creates an Amazon ECS cluster and adds capacity to it:
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        cluster = ecs.Cluster(self, "Cluster",
            vpc=vpc
        )
        
        # Either add default capacity
        cluster.add_capacity("DefaultAutoScalingGroupCapacity",
            instance_type=ec2.InstanceType("t2.xlarge"),
            desired_capacity=3
        )
        
        # Or add customized capacity. Be sure to start the Amazon ECS-optimized AMI.
        auto_scaling_group = autoscaling.AutoScalingGroup(self, "ASG",
            vpc=vpc,
            instance_type=ec2.InstanceType("t2.xlarge"),
            machine_image=EcsOptimizedImage.amazon_linux(),
            # Or use Amazon ECS-Optimized Amazon Linux 2 AMI
            # machineImage: EcsOptimizedImage.amazonLinux2(),
            desired_capacity=3
        )
        
        cluster.add_auto_scaling_group(auto_scaling_group)
        ```
        
        If you omit the property `vpc`, the construct will create a new VPC with two AZs.
        
        ### Spot Instances
        
        To add spot instances into the cluster, you must specify the `spotPrice` in the `ecs.AddCapacityOptions` and optionally enable the `spotInstanceDraining` property.
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        # Add an AutoScalingGroup with spot instances to the existing cluster
        cluster.add_capacity("AsgSpot",
            max_capacity=2,
            min_capacity=2,
            desired_capacity=2,
            instance_type=ec2.InstanceType("c5.xlarge"),
            spot_price="0.0735",
            # Enable the Automated Spot Draining support for Amazon ECS
            spot_instance_draining=True
        )
        ```
        
        ## Task definitions
        
        A task Definition describes what a single copy of a **task** should look like.
        A task definition has one or more containers; typically, it has one
        main container (the *default container* is the first one that's added
        to the task definition, and it is marked *essential*) and optionally
        some supporting containers which are used to support the main container,
        doings things like upload logs or metrics to monitoring services.
        
        To run a task or service with Amazon EC2 launch type, use the `Ec2TaskDefinition`. For AWS Fargate tasks/services, use the
        `FargateTaskDefinition`. These classes provide a simplified API that only contain
        properties relevant for that specific launch type.
        
        For a `FargateTaskDefinition`, specify the task size (`memoryLimitMiB` and `cpu`):
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        fargate_task_definition = ecs.FargateTaskDefinition(self, "TaskDef",
            memory_limit_mi_b=512,
            cpu=256
        )
        ```
        
        To add containers to a task definition, call `addContainer()`:
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        container = fargate_task_definition.add_container("WebContainer",
            # Use an image from DockerHub
            image=ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample")
        )
        ```
        
        For a `Ec2TaskDefinition`:
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        ec2_task_definition = ecs.Ec2TaskDefinition(self, "TaskDef",
            network_mode=NetworkMode.BRIDGE
        )
        
        container = ec2_task_definition.add_container("WebContainer",
            # Use an image from DockerHub
            image=ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample"),
            memory_limit_mi_b=1024
        )
        ```
        
        You can specify container properties when you add them to the task definition, or with various methods, e.g.:
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        container.add_port_mappings(
            container_port=3000
        )
        ```
        
        To use a TaskDefinition that can be used with either Amazon EC2 or
        AWS Fargate launch types, use the `TaskDefinition` construct.
        
        When creating a task definition you have to specify what kind of
        tasks you intend to run: Amazon EC2, AWS Fargate, or both.
        The following example uses both:
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        task_definition = ecs.TaskDefinition(self, "TaskDef",
            memory_mi_b="512",
            cpu="256",
            network_mode=NetworkMode.AWS_VPC,
            compatibility=ecs.Compatibility.EC2_AND_FARGATE
        )
        ```
        
        ### Images
        
        Images supply the software that runs inside the container. Images can be
        obtained from either DockerHub or from ECR repositories, or built directly from a local Dockerfile.
        
        * `ecs.ContainerImage.fromRegistry(imageName)`: use a public image.
        * `ecs.ContainerImage.fromRegistry(imageName, { credentials: mySecret })`: use a private image that requires credentials.
        * `ecs.ContainerImage.fromEcrRepository(repo, tag)`: use the given ECR repository as the image
          to start. If no tag is provided, "latest" is assumed.
        * `ecs.ContainerImage.fromAsset('./image')`: build and upload an
          image directly from a `Dockerfile` in your source directory.
        * `ecs.ContainerImage.fromDockerImageAsset(asset)`: uses an existing
          `@aws-cdk/aws-ecr-assets.DockerImageAsset` as a container image.
        
        ### Environment variables
        
        To pass environment variables to the container, use the `environment` and `secrets` props.
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        task_definition.add_container("container",
            image=ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample"),
            memory_limit_mi_b=1024,
            environment={# clear text, not for sensitive data
                "STAGE": "prod"},
            secrets={# Retrieved from AWS Secrets Manager or AWS Systems Manager Parameter Store at container start-up.
                "SECRET": ecs.Secret.from_secrets_manager(secret),
                "DB_PASSWORD": ecs.Secret.from_secrets_manager(db_secret, "password"), # Reference a specific JSON field
                "PARAMETER": ecs.Secret.from_ssm_parameter(parameter)}
        )
        ```
        
        The task execution role is automatically granted read permissions on the secrets/parameters.
        
        ## Service
        
        A `Service` instantiates a `TaskDefinition` on a `Cluster` a given number of
        times, optionally associating them with a load balancer.
        If a task fails,
        Amazon ECS automatically restarts the task.
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        task_definition =
        
        service = ecs.FargateService(self, "Service",
            cluster=cluster,
            task_definition=task_definition,
            desired_count=5
        )
        ```
        
        `Services` by default will create a security group if not provided.
        If you'd like to specify which security groups to use you can override the `securityGroups` property.
        
        ### Include an application/network load balancer
        
        `Services` are load balancing targets and can be added to a target group, which will be attached to an application/network load balancers:
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_elasticloadbalancingv2 as elbv2
        
        service = ecs.FargateService(self, "Service")
        
        lb = elbv2.ApplicationLoadBalancer(self, "LB", vpc=vpc, internet_facing=True)
        listener = lb.add_listener("Listener", port=80)
        target_group1 = listener.add_targets("ECS1",
            port=80,
            targets=[service]
        )
        target_group2 = listener.add_targets("ECS2",
            port=80,
            targets=[service.load_balancer_target(
                container_name="MyContainer",
                container_port=8080
            )]
        )
        ```
        
        Note that in the example above, the default `service` only allows you to register the first essential container or the first mapped port on the container as a target and add it to a new target group. To have more control over which container and port to register as targets, you can use `service.loadBalancerTarget()` to return a load balancing target for a specific container and port.
        
        Alternatively, you can also create all load balancer targets to be registered in this service, add them to target groups, and attach target groups to listeners accordingly.
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_elasticloadbalancingv2 as elbv2
        
        service = ecs.FargateService(self, "Service")
        
        lb = elbv2.ApplicationLoadBalancer(self, "LB", vpc=vpc, internet_facing=True)
        listener = lb.add_listener("Listener", port=80)
        service.register_load_balancer_targets(
            container_name="web",
            container_port=80,
            new_target_group_id="ECS",
            listener=ecs.ListenerConfig.application_listener(listener,
                protocol=elbv2.ApplicationProtocol.HTTPS
            )
        )
        ```
        
        ### Using a Load Balancer from a different Stack
        
        If you want to put your Load Balancer and the Service it is load balancing to in
        different stacks, you may not be able to use the convenience methods
        `loadBalancer.addListener()` and `listener.addTargets()`.
        
        The reason is that these methods will create resources in the same Stack as the
        object they're called on, which may lead to cyclic references between stacks.
        Instead, you will have to create an `ApplicationListener` in the service stack,
        or an empty `TargetGroup` in the load balancer stack that you attach your
        service to.
        
        See the [ecs/cross-stack-load-balancer example](https://github.com/aws-samples/aws-cdk-examples/tree/master/typescript/ecs/cross-stack-load-balancer/)
        for the alternatives.
        
        ### Include a classic load balancer
        
        `Services` can also be directly attached to a classic load balancer as targets:
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_elasticloadbalancing as elb
        
        service = ecs.Ec2Service(self, "Service")
        
        lb = elb.LoadBalancer(stack, "LB", vpc=vpc)
        lb.add_listener(external_port=80)
        lb.add_target(service)
        ```
        
        Similarly, if you want to have more control over load balancer targeting:
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_elasticloadbalancing as elb
        
        service = ecs.Ec2Service(self, "Service")
        
        lb = elb.LoadBalancer(stack, "LB", vpc=vpc)
        lb.add_listener(external_port=80)
        lb.add_target(service.load_balancer_target,
            container_name="MyContainer",
            container_port=80
        )
        ```
        
        There are two higher-level constructs available which include a load balancer for you that can be found in the aws-ecs-patterns module:
        
        * `LoadBalancedFargateService`
        * `LoadBalancedEc2Service`
        
        ## Task Auto-Scaling
        
        You can configure the task count of a service to match demand. Task auto-scaling is
        configured by calling `autoScaleTaskCount()`:
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        scaling = service.auto_scale_task_count(max_capacity=10)
        scaling.scale_on_cpu_utilization("CpuScaling",
            target_utilization_percent=50
        )
        
        scaling.scale_on_request_count("RequestScaling",
            requests_per_target=10000,
            target_group=target
        )
        ```
        
        Task auto-scaling is powered by *Application Auto-Scaling*.
        See that section for details.
        
        ## Instance Auto-Scaling
        
        If you're running on AWS Fargate, AWS manages the physical machines that your
        containers are running on for you. If you're running an Amazon ECS cluster however,
        your Amazon EC2 instances might fill up as your number of Tasks goes up.
        
        To avoid placement errors, configure auto-scaling for your
        Amazon EC2 instance group so that your instance count scales with demand. To keep
        your Amazon EC2 instances halfway loaded, scaling up to a maximum of 30 instances
        if required:
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        auto_scaling_group = cluster.add_capacity("DefaultAutoScalingGroup",
            instance_type=ec2.InstanceType("t2.xlarge"),
            min_capacity=3,
            max_capacity=30,
            desired_capacity=3,
        
            # Give instances 5 minutes to drain running tasks when an instance is
            # terminated. This is the default, turn this off by specifying 0 or
            # change the timeout up to 900 seconds.
            task_drain_time=Duration.seconds(300)
        )
        
        auto_scaling_group.scale_on_cpu_utilization("KeepCpuHalfwayLoaded",
            target_utilization_percent=50
        )
        ```
        
        See the `@aws-cdk/aws-autoscaling` library for more autoscaling options
        you can configure on your instances.
        
        ## Integration with CloudWatch Events
        
        To start an Amazon ECS task on an Amazon EC2-backed Cluster, instantiate an
        `@aws-cdk/aws-events-targets.EcsTask` instead of an `Ec2Service`:
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_events_targets as targets
        
        # Create a Task Definition for the container to start
        task_definition = ecs.Ec2TaskDefinition(self, "TaskDef")
        task_definition.add_container("TheContainer",
            image=ecs.ContainerImage.from_asset(path.resolve(__dirname, "..", "eventhandler-image")),
            memory_limit_mi_b=256,
            logging=ecs.AwsLogDriver(stream_prefix="EventDemo")
        )
        
        # An Rule that describes the event trigger (in this case a scheduled run)
        rule = events.Rule(self, "Rule",
            schedule=events.Schedule.expression("rate(1 min)")
        )
        
        # Pass an environment variable to the container 'TheContainer' in the task
        rule.add_target(targets.EcsTask(
            cluster=cluster,
            task_definition=task_definition,
            task_count=1,
            container_overrides=[ContainerOverride(
                container_name="TheContainer",
                environment=[TaskEnvironmentVariable(
                    name="I_WAS_TRIGGERED",
                    value="From CloudWatch Events"
                )]
            )]
        ))
        ```
        
        ## Log Drivers
        
        Currently Supported Log Drivers:
        
        * awslogs
        * fluentd
        * gelf
        * journald
        * json-file
        * splunk
        * syslog
        * awsfirelens
        
        ### awslogs Log Driver
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        # Create a Task Definition for the container to start
        task_definition = ecs.Ec2TaskDefinition(self, "TaskDef")
        task_definition.add_container("TheContainer",
            image=ecs.ContainerImage.from_registry("example-image"),
            memory_limit_mi_b=256,
            logging=ecs.LogDrivers.aws_logs(stream_prefix="EventDemo")
        )
        ```
        
        ### fluentd Log Driver
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        # Create a Task Definition for the container to start
        task_definition = ecs.Ec2TaskDefinition(self, "TaskDef")
        task_definition.add_container("TheContainer",
            image=ecs.ContainerImage.from_registry("example-image"),
            memory_limit_mi_b=256,
            logging=ecs.LogDrivers.fluentd()
        )
        ```
        
        ### gelf Log Driver
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        # Create a Task Definition for the container to start
        task_definition = ecs.Ec2TaskDefinition(self, "TaskDef")
        task_definition.add_container("TheContainer",
            image=ecs.ContainerImage.from_registry("example-image"),
            memory_limit_mi_b=256,
            logging=ecs.LogDrivers.gelf(address="my-gelf-address")
        )
        ```
        
        ### journald Log Driver
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        # Create a Task Definition for the container to start
        task_definition = ecs.Ec2TaskDefinition(self, "TaskDef")
        task_definition.add_container("TheContainer",
            image=ecs.ContainerImage.from_registry("example-image"),
            memory_limit_mi_b=256,
            logging=ecs.LogDrivers.journald()
        )
        ```
        
        ### json-file Log Driver
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        # Create a Task Definition for the container to start
        task_definition = ecs.Ec2TaskDefinition(self, "TaskDef")
        task_definition.add_container("TheContainer",
            image=ecs.ContainerImage.from_registry("example-image"),
            memory_limit_mi_b=256,
            logging=ecs.LogDrivers.json_file()
        )
        ```
        
        ### splunk Log Driver
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        # Create a Task Definition for the container to start
        task_definition = ecs.Ec2TaskDefinition(self, "TaskDef")
        task_definition.add_container("TheContainer",
            image=ecs.ContainerImage.from_registry("example-image"),
            memory_limit_mi_b=256,
            logging=ecs.LogDrivers.splunk(
                token=cdk.SecretValue.secrets_manager("my-splunk-token"),
                url="my-splunk-url"
            )
        )
        ```
        
        ### syslog Log Driver
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        # Create a Task Definition for the container to start
        task_definition = ecs.Ec2TaskDefinition(self, "TaskDef")
        task_definition.add_container("TheContainer",
            image=ecs.ContainerImage.from_registry("example-image"),
            memory_limit_mi_b=256,
            logging=ecs.LogDrivers.syslog()
        )
        ```
        
        ### firelens Log Driver
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        # Create a Task Definition for the container to start
        task_definition = ecs.Ec2TaskDefinition(self, "TaskDef")
        task_definition.add_container("TheContainer",
            image=ecs.ContainerImage.from_registry("example-image"),
            memory_limit_mi_b=256,
            logging=ecs.LogDrivers.firelens(
                options={
                    "Name": "firehose",
                    "region": "us-west-2",
                    "delivery_stream": "my-stream"
                }
            )
        )
        ```
        
        ### Generic Log Driver
        
        A generic log driver object exists to provide a lower level abstraction of the log driver configuration.
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        # Create a Task Definition for the container to start
        task_definition = ecs.Ec2TaskDefinition(self, "TaskDef")
        task_definition.add_container("TheContainer",
            image=ecs.ContainerImage.from_registry("example-image"),
            memory_limit_mi_b=256,
            logging=ecs.GenericLogDriver(
                log_driver="fluentd",
                options={
                    "tag": "example-tag"
                }
            )
        )
        ```
        
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