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Author: Amazon Web Services

Requires Python: ~=3.7

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Intended Audience

Developers

Operating System

OS Independent

Programming Language

JavaScript
Python :: 3 :: Only
Python :: 3.7
Python :: 3.8
Python :: 3.9
Python :: 3.10
Python :: 3.11

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Typed

Development Status

7 - Inactive

License

OSI Approved

Framework

AWS CDK
AWS CDK :: 1

AWS CodeDeploy Construct Library

---

AWS CDK v1 has reached End-of-Support on 2023-06-01. This package is no longer being updated, and users should migrate to AWS CDK v2.

For more information on how to migrate, see the Migrating to AWS CDK v2 guide.

AWS CodeDeploy is a deployment service that automates application deployments to Amazon EC2 instances, on-premises instances, serverless Lambda functions, or Amazon ECS services.

The CDK currently supports Amazon EC2, on-premise and AWS Lambda applications.

EC2/on-premise Applications

To create a new CodeDeploy Application that deploys to EC2/on-premise instances:

application = codedeploy.ServerApplication(self, "CodeDeployApplication",
    application_name="MyApplication"
)

To import an already existing Application:

application = codedeploy.ServerApplication.from_server_application_name(self, "ExistingCodeDeployApplication", "MyExistingApplication")

EC2/on-premise Deployment Groups

To create a new CodeDeploy Deployment Group that deploys to EC2/on-premise instances:

import aws_cdk.aws_autoscaling as autoscaling
import aws_cdk.aws_cloudwatch as cloudwatch

# application: codedeploy.ServerApplication
# asg: autoscaling.AutoScalingGroup
# alarm: cloudwatch.Alarm

deployment_group = codedeploy.ServerDeploymentGroup(self, "CodeDeployDeploymentGroup",
    application=application,
    deployment_group_name="MyDeploymentGroup",
    auto_scaling_groups=[asg],
    # adds User Data that installs the CodeDeploy agent on your auto-scaling groups hosts
    # default: true
    install_agent=True,
    # adds EC2 instances matching tags
    ec2_instance_tags=codedeploy.InstanceTagSet({
        # any instance with tags satisfying
        # key1=v1 or key1=v2 or key2 (any value) or value v3 (any key)
        # will match this group
        "key1": ["v1", "v2"],
        "key2": [],
        "": ["v3"]
    }),
    # adds on-premise instances matching tags
    on_premise_instance_tags=codedeploy.InstanceTagSet({
        "key1": ["v1", "v2"]
    }, {
        "key2": ["v3"]
    }),
    # CloudWatch alarms
    alarms=[alarm],
    # whether to ignore failure to fetch the status of alarms from CloudWatch
    # default: false
    ignore_poll_alarms_failure=False,
    # auto-rollback configuration
    auto_rollback=codedeploy.AutoRollbackConfig(
        failed_deployment=True,  # default: true
        stopped_deployment=True,  # default: false
        deployment_in_alarm=True
    )
)

All properties are optional - if you don't provide an Application, one will be automatically created.

To import an already existing Deployment Group:

# application: codedeploy.ServerApplication

deployment_group = codedeploy.ServerDeploymentGroup.from_server_deployment_group_attributes(self, "ExistingCodeDeployDeploymentGroup",
    application=application,
    deployment_group_name="MyExistingDeploymentGroup"
)

Load balancers

You can specify a load balancer with the loadBalancer property when creating a Deployment Group.

LoadBalancer is an abstract class with static factory methods that allow you to create instances of it from various sources.

With Classic Elastic Load Balancer, you provide it directly:

import aws_cdk.aws_elasticloadbalancing as elb

# lb: elb.LoadBalancer

lb.add_listener(
    external_port=80
)

deployment_group = codedeploy.ServerDeploymentGroup(self, "DeploymentGroup",
    load_balancer=codedeploy.LoadBalancer.classic(lb)
)

With Application Load Balancer or Network Load Balancer, you provide a Target Group as the load balancer:

import aws_cdk.aws_elasticloadbalancingv2 as elbv2

# alb: elbv2.ApplicationLoadBalancer

listener = alb.add_listener("Listener", port=80)
target_group = listener.add_targets("Fleet", port=80)

deployment_group = codedeploy.ServerDeploymentGroup(self, "DeploymentGroup",
    load_balancer=codedeploy.LoadBalancer.application(target_group)
)

Deployment Configurations

You can also pass a Deployment Configuration when creating the Deployment Group:

deployment_group = codedeploy.ServerDeploymentGroup(self, "CodeDeployDeploymentGroup",
    deployment_config=codedeploy.ServerDeploymentConfig.ALL_AT_ONCE
)

The default Deployment Configuration is ServerDeploymentConfig.ONE_AT_A_TIME.

You can also create a custom Deployment Configuration:

deployment_config = codedeploy.ServerDeploymentConfig(self, "DeploymentConfiguration",
    deployment_config_name="MyDeploymentConfiguration",  # optional property
    # one of these is required, but both cannot be specified at the same time
    minimum_healthy_hosts=codedeploy.MinimumHealthyHosts.count(2)
)

Or import an existing one:

deployment_config = codedeploy.ServerDeploymentConfig.from_server_deployment_config_name(self, "ExistingDeploymentConfiguration", "MyExistingDeploymentConfiguration")

Lambda Applications

To create a new CodeDeploy Application that deploys to a Lambda function:

application = codedeploy.LambdaApplication(self, "CodeDeployApplication",
    application_name="MyApplication"
)

To import an already existing Application:

application = codedeploy.LambdaApplication.from_lambda_application_name(self, "ExistingCodeDeployApplication", "MyExistingApplication")

Lambda Deployment Groups

To enable traffic shifting deployments for Lambda functions, CodeDeploy uses Lambda Aliases, which can balance incoming traffic between two different versions of your function. Before deployment, the alias sends 100% of invokes to the version used in production. When you publish a new version of the function to your stack, CodeDeploy will send a small percentage of traffic to the new version, monitor, and validate before shifting 100% of traffic to the new version.

To create a new CodeDeploy Deployment Group that deploys to a Lambda function:

# my_application: codedeploy.LambdaApplication
# func: lambda.Function

version = func.current_version
version1_alias = lambda_.Alias(self, "alias",
    alias_name="prod",
    version=version
)

deployment_group = codedeploy.LambdaDeploymentGroup(self, "BlueGreenDeployment",
    application=my_application,  # optional property: one will be created for you if not provided
    alias=version1_alias,
    deployment_config=codedeploy.LambdaDeploymentConfig.LINEAR_10PERCENT_EVERY_1MINUTE
)

In order to deploy a new version of this function:

Reference the version with the latest changes const version = func.currentVersion.
Re-deploy the stack (this will trigger a deployment).
Monitor the CodeDeploy deployment as traffic shifts between the versions.

Create a custom Deployment Config

CodeDeploy for Lambda comes with built-in configurations for traffic shifting. If you want to specify your own strategy, you can do so with the CustomLambdaDeploymentConfig construct, letting you specify precisely how fast a new function version is deployed.

# application: codedeploy.LambdaApplication
# alias: lambda.Alias
config = codedeploy.CustomLambdaDeploymentConfig(self, "CustomConfig",
    type=codedeploy.CustomLambdaDeploymentConfigType.CANARY,
    interval=Duration.minutes(1),
    percentage=5
)
deployment_group = codedeploy.LambdaDeploymentGroup(self, "BlueGreenDeployment",
    application=application,
    alias=alias,
    deployment_config=config
)

You can specify a custom name for your deployment config, but if you do you will not be able to update the interval/percentage through CDK.

config = codedeploy.CustomLambdaDeploymentConfig(self, "CustomConfig",
    type=codedeploy.CustomLambdaDeploymentConfigType.CANARY,
    interval=Duration.minutes(1),
    percentage=5,
    deployment_config_name="MyDeploymentConfig"
)

Rollbacks and Alarms

CodeDeploy will roll back if the deployment fails. You can optionally trigger a rollback when one or more alarms are in a failed state:

import aws_cdk.aws_cloudwatch as cloudwatch

# alias: lambda.Alias

# or add alarms to an existing group
# blue_green_alias: lambda.Alias

alarm = cloudwatch.Alarm(self, "Errors",
    comparison_operator=cloudwatch.ComparisonOperator.GREATER_THAN_THRESHOLD,
    threshold=1,
    evaluation_periods=1,
    metric=alias.metric_errors()
)
deployment_group = codedeploy.LambdaDeploymentGroup(self, "BlueGreenDeployment",
    alias=alias,
    deployment_config=codedeploy.LambdaDeploymentConfig.LINEAR_10PERCENT_EVERY_1MINUTE,
    alarms=[alarm
    ]
)
deployment_group.add_alarm(cloudwatch.Alarm(self, "BlueGreenErrors",
    comparison_operator=cloudwatch.ComparisonOperator.GREATER_THAN_THRESHOLD,
    threshold=1,
    evaluation_periods=1,
    metric=blue_green_alias.metric_errors()
))

Pre and Post Hooks

CodeDeploy allows you to run an arbitrary Lambda function before traffic shifting actually starts (PreTraffic Hook) and after it completes (PostTraffic Hook). With either hook, you have the opportunity to run logic that determines whether the deployment must succeed or fail. For example, with PreTraffic hook you could run integration tests against the newly created Lambda version (but not serving traffic). With PostTraffic hook, you could run end-to-end validation checks.

# warm_up_user_cache: lambda.Function
# end_to_end_validation: lambda.Function
# alias: lambda.Alias


# pass a hook whe creating the deployment group
deployment_group = codedeploy.LambdaDeploymentGroup(self, "BlueGreenDeployment",
    alias=alias,
    deployment_config=codedeploy.LambdaDeploymentConfig.LINEAR_10PERCENT_EVERY_1MINUTE,
    pre_hook=warm_up_user_cache
)

# or configure one on an existing deployment group
deployment_group.add_post_hook(end_to_end_validation)

Import an existing Deployment Group

To import an already existing Deployment Group:

# application: codedeploy.LambdaApplication

deployment_group = codedeploy.LambdaDeploymentGroup.from_lambda_deployment_group_attributes(self, "ExistingCodeDeployDeploymentGroup",
    application=application,
    deployment_group_name="MyExistingDeploymentGroup"
)