# CDK Construct library for higher-level ECS Constructs--- ![Stability: Experimental](https://img.shields.io/badge/stability-Experimental-important.svg?style=for-the-badge) > **This is a *developer preview* (public beta) module. Releases might lack important features and might have > future breaking changes.** > > This API is still under active development and subject to non-backward > compatible changes or removal in any future version. Use of the API is not recommended in production > environments. Experimental APIs are not subject to the Semantic Versioning model. --- 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) ## Application Load Balanced Services To define an Amazon ECS service that is behind an application load balancer, instantiate one of the following: * `ApplicationLoadBalancedEc2Service` ```python load_balanced_ecs_service = ecs_patterns.ApplicationLoadBalancedEc2Service(stack, "Service", cluster=cluster, memory_limit_mi_b=1024, image=ecs.ContainerImage.from_registry("test"), desired_count=2, environment={ "TEST_ENVIRONMENT_VARIABLE1": "test environment variable 1 value", "TEST_ENVIRONMENT_VARIABLE2": "test environment variable 2 value" } ) ``` * `ApplicationLoadBalancedFargateService` ```python load_balanced_fargate_service = ecs_patterns.ApplicationLoadBalancedFargateService(stack, "Service", cluster=cluster, memory_limit_mi_b=1024, cpu=512, 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 on 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` ```python load_balanced_ecs_service = ecs_patterns.NetworkLoadBalancedEc2Service(stack, "Service", cluster=cluster, memory_limit_mi_b=1024, image=ecs.ContainerImage.from_registry("test"), desired_count=2, environment={ "TEST_ENVIRONMENT_VARIABLE1": "test environment variable 1 value", "TEST_ENVIRONMENT_VARIABLE2": "test environment variable 2 value" } ) ``` * `NetworkLoadBalancedFargateService` ```python load_balanced_fargate_service = ecs_patterns.NetworkLoadBalancedFargateService(stack, "Service", cluster=cluster, memory_limit_mi_b=1024, cpu=512, 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` ```python 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` ```python 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`: ```python # Instantiate an Amazon EC2 Task to run at a scheduled interval ecs_scheduled_task = ScheduledEc2Task(self, "ScheduledTask", cluster=cluster, image=ecs.ContainerImage.from_registry("amazon/amazon-ecs-sample"), schedule_expression="rate(1 minute)", environment=[{"name": "TRIGGER", "value": "CloudWatch Events"}], memory_limit_mi_b=256 ) ```