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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. 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. 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.

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. 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. 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.

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. 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. 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
)

Scheduled Tasks

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

# Example automatically generated. 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. 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. 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
)

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