Skip to main content

CDK Constructs for AWS ECS

Project description

CDK Construct library for higher-level ECS Constructs

---

Stability: Stable


This library provides higher-level Amazon ECS constructs which follow common architectural patterns. It contains:

  • Application Load Balanced Services
  • Network Load Balanced Services
  • Queue Processing Services
  • Scheduled Tasks (cron jobs)
  • Additional Examples

Application Load Balanced Services

To define an Amazon ECS service that is behind an application load balancer, instantiate one of the following:

  • ApplicationLoadBalancedEc2Service
# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
load_balanced_ecs_service = ecs_patterns.ApplicationLoadBalancedEc2Service(stack, "Service",
    cluster=cluster,
    memory_limit_mi_b=1024,
    task_image_options={
        "image": ecs.ContainerImage.from_registry("test"),
        "environment": {
            "TEST_ENVIRONMENT_VARIABLE1": "test environment variable 1 value",
            "TEST_ENVIRONMENT_VARIABLE2": "test environment variable 2 value"
        }
    },
    desired_count=2
)
  • ApplicationLoadBalancedFargateService
# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
load_balanced_fargate_service = ecs_patterns.ApplicationLoadBalancedFargateService(stack, "Service",
    cluster=cluster,
    memory_limit_mi_b=1024,
    cpu=512,
    task_image_options={
        "image": ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample")
    }
)

Instead of providing a cluster you can specify a VPC and CDK will create a new ECS cluster. If you deploy multiple services CDK will only create one cluster per VPC.

You can omit cluster and vpc to let CDK create a new VPC with two AZs and create a cluster inside this VPC.

Additionally, if more than one application target group are needed, instantiate one of the following:

  • ApplicationMultipleTargetGroupsEc2Service
# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
# One application load balancer with one listener and two target groups.
load_balanced_ec2_service = ApplicationMultipleTargetGroupsEc2Service(stack, "Service",
    cluster=cluster,
    memory_limit_mi_b=256,
    task_image_options={
        "image": ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample")
    },
    target_groups=[{
        "container_port": 80
    }, {
        "container_port": 90,
        "path_pattern": "a/b/c",
        "priority": 10
    }
    ]
)
  • ApplicationMultipleTargetGroupsFargateService
# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
# One application load balancer with one listener and two target groups.
load_balanced_fargate_service = ApplicationMultipleTargetGroupsFargateService(stack, "Service",
    cluster=cluster,
    memory_limit_mi_b=1024,
    cpu=512,
    task_image_options={
        "image": ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample")
    },
    target_groups=[{
        "container_port": 80
    }, {
        "container_port": 90,
        "path_pattern": "a/b/c",
        "priority": 10
    }
    ]
)

Network Load Balanced Services

To define an Amazon ECS service that is behind a network load balancer, instantiate one of the following:

  • NetworkLoadBalancedEc2Service
# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
load_balanced_ecs_service = ecs_patterns.NetworkLoadBalancedEc2Service(stack, "Service",
    cluster=cluster,
    memory_limit_mi_b=1024,
    task_image_options={
        "image": ecs.ContainerImage.from_registry("test"),
        "environment": {
            "TEST_ENVIRONMENT_VARIABLE1": "test environment variable 1 value",
            "TEST_ENVIRONMENT_VARIABLE2": "test environment variable 2 value"
        }
    },
    desired_count=2
)
  • NetworkLoadBalancedFargateService
# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
load_balanced_fargate_service = ecs_patterns.NetworkLoadBalancedFargateService(stack, "Service",
    cluster=cluster,
    memory_limit_mi_b=1024,
    cpu=512,
    task_image_options={
        "image": ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample")
    }
)

The CDK will create a new Amazon ECS cluster if you specify a VPC and omit cluster. If you deploy multiple services the CDK will only create one cluster per VPC.

If cluster and vpc are omitted, the CDK creates a new VPC with subnets in two Availability Zones and a cluster within this VPC.

Additionally, if more than one network target group is needed, instantiate one of the following:

  • NetworkMultipleTargetGroupsEc2Service
# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
# Two network load balancers, each with their own listener and target group.
load_balanced_ec2_service = NetworkMultipleTargetGroupsEc2Service(stack, "Service",
    cluster=cluster,
    memory_limit_mi_b=256,
    task_image_options={
        "image": ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample")
    },
    load_balancers=[{
        "name": "lb1",
        "listeners": [{
            "name": "listener1"
        }
        ]
    }, {
        "name": "lb2",
        "listeners": [{
            "name": "listener2"
        }
        ]
    }
    ],
    target_groups=[{
        "container_port": 80,
        "listener": "listener1"
    }, {
        "container_port": 90,
        "listener": "listener2"
    }
    ]
)
  • NetworkMultipleTargetGroupsFargateService
# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
# Two network load balancers, each with their own listener and target group.
load_balanced_fargate_service = NetworkMultipleTargetGroupsFargateService(stack, "Service",
    cluster=cluster,
    memory_limit_mi_b=512,
    task_image_options={
        "image": ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample")
    },
    load_balancers=[{
        "name": "lb1",
        "listeners": [{
            "name": "listener1"
        }
        ]
    }, {
        "name": "lb2",
        "listeners": [{
            "name": "listener2"
        }
        ]
    }
    ],
    target_groups=[{
        "container_port": 80,
        "listener": "listener1"
    }, {
        "container_port": 90,
        "listener": "listener2"
    }
    ]
)

Queue Processing Services

To define a service that creates a queue and reads from that queue, instantiate one of the following:

  • QueueProcessingEc2Service
# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
queue_processing_ec2_service = QueueProcessingEc2Service(stack, "Service",
    cluster=cluster,
    memory_limit_mi_b=1024,
    image=ecs.ContainerImage.from_registry("test"),
    command=["-c", "4", "amazon.com"],
    enable_logging=False,
    desired_task_count=2,
    environment={
        "TEST_ENVIRONMENT_VARIABLE1": "test environment variable 1 value",
        "TEST_ENVIRONMENT_VARIABLE2": "test environment variable 2 value"
    },
    queue=queue,
    max_scaling_capacity=5
)
  • QueueProcessingFargateService
# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
queue_processing_fargate_service = QueueProcessingFargateService(stack, "Service",
    cluster=cluster,
    memory_limit_mi_b=512,
    image=ecs.ContainerImage.from_registry("test"),
    command=["-c", "4", "amazon.com"],
    enable_logging=False,
    desired_task_count=2,
    environment={
        "TEST_ENVIRONMENT_VARIABLE1": "test environment variable 1 value",
        "TEST_ENVIRONMENT_VARIABLE2": "test environment variable 2 value"
    },
    queue=queue,
    max_scaling_capacity=5
)

when queue not provided by user, CDK will create a primary queue and a dead letter queue with default redrive policy and attach permission to the task to be able to access the primary queue.

Scheduled Tasks

To define a task that runs periodically, instantiate an ScheduledEc2Task:

# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
# Instantiate an Amazon EC2 Task to run at a scheduled interval
ecs_scheduled_task = ScheduledEc2Task(stack, "ScheduledTask",
    cluster=cluster,
    scheduled_ec2_task_image_options={
        "image": ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample"),
        "memory_limit_mi_b": 256,
        "environment": {"name": "TRIGGER", "value": "CloudWatch Events"}
    },
    schedule=events.Schedule.expression("rate(1 minute)")
)

Additional Examples

In addition to using the constructs, users can also add logic to customize these constructs:

Add Schedule-Based Auto-Scaling to an ApplicationLoadBalancedFargateService

# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
from aws_cdk.aws_applicationautoscaling import Schedule
from ..application_load_balanced_fargate_service import ApplicationLoadBalancedFargateService, ApplicationLoadBalancedFargateServiceProps

load_balanced_fargate_service = ApplicationLoadBalancedFargateService(stack, "Service",
    cluster=cluster,
    memory_limit_mi_b=1024,
    desired_count=1,
    cpu=512,
    task_image_options={
        "image": ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample")
    }
)

scalable_target = load_balanced_fargate_service.service.auto_scale_task_count(
    min_capacity=5,
    max_capacity=20
)

scalable_target.scale_on_schedule("DaytimeScaleDown",
    schedule=Schedule.cron(hour="8", minute="0"),
    min_capacity=1
)

scalable_target.scale_on_schedule("EveningRushScaleUp",
    schedule=Schedule.cron(hour="20", minute="0"),
    min_capacity=10
)

Add Metric-Based Auto-Scaling to an ApplicationLoadBalancedFargateService

# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
from ..application_load_balanced_fargate_service import ApplicationLoadBalancedFargateService

load_balanced_fargate_service = ApplicationLoadBalancedFargateService(stack, "Service",
    cluster=cluster,
    memory_limit_mi_b=1024,
    desired_count=1,
    cpu=512,
    task_image_options={
        "image": ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample")
    }
)

scalable_target = load_balanced_fargate_service.service.auto_scale_task_count(
    min_capacity=1,
    max_capacity=20
)

scalable_target.scale_on_cpu_utilization("CpuScaling",
    target_utilization_percent=50
)

scalable_target.scale_on_memory_utilization("MemoryScaling",
    target_utilization_percent=50
)

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aws-cdk.aws-ecs-patterns-1.32.2.tar.gz (266.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

aws_cdk.aws_ecs_patterns-1.32.2-py3-none-any.whl (264.4 kB view details)

Uploaded Python 3

File details

Details for the file aws-cdk.aws-ecs-patterns-1.32.2.tar.gz.

File metadata

  • Download URL: aws-cdk.aws-ecs-patterns-1.32.2.tar.gz
  • Upload date:
  • Size: 266.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/39.0.1 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.6.5

File hashes

Hashes for aws-cdk.aws-ecs-patterns-1.32.2.tar.gz
Algorithm Hash digest
SHA256 36b7cfa9bcb4c79a5dd33ef97e9870fda71bf532550a2fd2805c430b7265f377
MD5 0c2740a4f44d8102e0b1068063a11a53
BLAKE2b-256 097fd37264f9f905aa1f1d539cf5ad6abef74934b0bcb385b2db2e338209e8f2

See more details on using hashes here.

File details

Details for the file aws_cdk.aws_ecs_patterns-1.32.2-py3-none-any.whl.

File metadata

  • Download URL: aws_cdk.aws_ecs_patterns-1.32.2-py3-none-any.whl
  • Upload date:
  • Size: 264.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/39.0.1 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.6.5

File hashes

Hashes for aws_cdk.aws_ecs_patterns-1.32.2-py3-none-any.whl
Algorithm Hash digest
SHA256 912ca066adf6931fb5a41694fa1c0304340cb3ddc774f201e4ebcf49eb6c760d
MD5 e01c92870644d9aa1ffa41dd85de9c51
BLAKE2b-256 e9e82763da8131ed42cf9b93268a8a89139add6752c38906003e89d19c530944

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page