AWS Cloud Development Kit Library

The AWS CDK construct library provides APIs to define your CDK application and add CDK constructs to the application.

Usage

Upgrade from CDK 1.x

When upgrading from CDK 1.x, remove all dependencies to individual CDK packages from your dependencies file and follow the rest of the sections.

Installation

To use this package, you need to declare this package and the constructs package as dependencies.

According to the kind of project you are developing:

For projects that are CDK libraries in NPM, declare them both under the devDependencies and peerDependencies sections. To make sure your library is compatible with the widest range of CDK versions: pick the minimum aws-cdk-lib version that your library requires; declare a range dependency with a caret on that version in peerDependencies, and declare a point version dependency on that version in devDependencies.

For example, let's say the minimum version your library needs is 2.38.0. Your package.json should look like this:

{
  "peerDependencies": {
    "aws-cdk-lib": "^2.38.0",
    "constructs": "^10.0.0"
  },
  "devDependencies": {
    /* Install the oldest version for testing so we don't accidentally use features from a newer version than we declare */
    "aws-cdk-lib": "2.38.0"
  }
}

For CDK apps, declare them under the dependencies section. Use a caret so you always get the latest version:

{
  "dependencies": {
    "aws-cdk-lib": "^2.38.0",
    "constructs": "^10.0.0"
  }
}

Use in your code

Classic import

You can use a classic import to get access to each service namespaces:

from aws_cdk import Stack, App, aws_s3 as s3

app = App()
stack = Stack(app, "TestStack")

s3.Bucket(stack, "TestBucket")

Barrel import

Alternatively, you can use "barrel" imports:

from aws_cdk import App, Stack
from aws_cdk.aws_s3 import Bucket

app = App()
stack = Stack(app, "TestStack")

Bucket(stack, "TestBucket")

Stacks and Stages

A Stack is the smallest physical unit of deployment, and maps directly onto a CloudFormation Stack. You define a Stack by defining a subclass of Stack -- let's call it MyStack -- and instantiating the constructs that make up your application in MyStack's constructor. You then instantiate this stack one or more times to define different instances of your application. For example, you can instantiate it once using few and cheap EC2 instances for testing, and once again using more and bigger EC2 instances for production.

When your application grows, you may decide that it makes more sense to split it out across multiple Stack classes. This can happen for a number of reasons:

• You could be starting to reach the maximum number of resources allowed in a single stack (this is currently 500).
• You could decide you want to separate out stateful resources and stateless resources into separate stacks, so that it becomes easy to tear down and recreate the stacks that don't have stateful resources.
• There could be a single stack with resources (like a VPC) that are shared between multiple instances of other stacks containing your applications.

As soon as your conceptual application starts to encompass multiple stacks, it is convenient to wrap them in another construct that represents your logical application. You can then treat that new unit the same way you used to be able to treat a single stack: by instantiating it multiple times for different instances of your application.

You can define a custom subclass of Stage, holding one or more Stacks, to represent a single logical instance of your application.

As a final note: Stacks are not a unit of reuse. They describe physical deployment layouts, and as such are best left to application builders to organize their deployments with. If you want to vend a reusable construct, define it as a subclasses of Construct: the consumers of your construct will decide where to place it in their own stacks.

Stack Synthesizers

Each Stack has a synthesizer, an object that determines how and where the Stack should be synthesized and deployed. The synthesizer controls aspects like:

• How does the stack reference assets? (Either through CloudFormation parameters the CLI supplies, or because the Stack knows a predefined location where assets will be uploaded).
• What roles are used to deploy the stack? These can be bootstrapped roles, roles created in some other way, or just the CLI's current credentials.

The following synthesizers are available:

• DefaultStackSynthesizer: recommended. Uses predefined asset locations and roles created by the modern bootstrap template. Access control is done by controlling who can assume the deploy role. This is the default stack synthesizer in CDKv2.
• LegacyStackSynthesizer: Uses CloudFormation parameters to communicate asset locations, and the CLI's current permissions to deploy stacks. This is the default stack synthesizer in CDKv1.
• CliCredentialsStackSynthesizer: Uses predefined asset locations, and the CLI's current permissions.

Each of these synthesizers takes configuration arguments. To configure a stack with a synthesizer, pass it as one of its properties:

MyStack(app, "MyStack",
    synthesizer=DefaultStackSynthesizer(
        file_assets_bucket_name="amzn-s3-demo-bucket"
    )
)

For more information on bootstrapping accounts and customizing synthesis, see Bootstrapping in the CDK Developer Guide.

Nested Stacks

Nested stacks are stacks created as part of other stacks. You create a nested stack within another stack by using the NestedStack construct.

As your infrastructure grows, common patterns can emerge in which you declare the same components in multiple templates. You can separate out these common components and create dedicated templates for them. Then use the resource in your template to reference other templates, creating nested stacks.

For example, assume that you have a load balancer configuration that you use for most of your stacks. Instead of copying and pasting the same configurations into your templates, you can create a dedicated template for the load balancer. Then, you just use the resource to reference that template from within other templates.

The following example will define a single top-level stack that contains two nested stacks: each one with a single Amazon S3 bucket:

class MyNestedStack(cfn.NestedStack):
    def __init__(self, scope, id, *, parameters=None, timeout=None, notifications=None):
        super().__init__(scope, id, parameters=parameters, timeout=timeout, notifications=notifications)

        s3.Bucket(self, "NestedBucket")

class MyParentStack(Stack):
    def __init__(self, scope, id, *, description=None, env=None, stackName=None, tags=None, notificationArns=None, synthesizer=None, terminationProtection=None, analyticsReporting=None, crossRegionReferences=None, permissionsBoundary=None, suppressTemplateIndentation=None):
        super().__init__(scope, id, description=description, env=env, stackName=stackName, tags=tags, notificationArns=notificationArns, synthesizer=synthesizer, terminationProtection=terminationProtection, analyticsReporting=analyticsReporting, crossRegionReferences=crossRegionReferences, permissionsBoundary=permissionsBoundary, suppressTemplateIndentation=suppressTemplateIndentation)

        MyNestedStack(self, "Nested1")
        MyNestedStack(self, "Nested2")

Resources references across nested/parent boundaries (even with multiple levels of nesting) will be wired by the AWS CDK through CloudFormation parameters and outputs. When a resource from a parent stack is referenced by a nested stack, a CloudFormation parameter will automatically be added to the nested stack and assigned from the parent; when a resource from a nested stack is referenced by a parent stack, a CloudFormation output will be automatically be added to the nested stack and referenced using Fn::GetAtt "Outputs.Xxx" from the parent.

Nested stacks also support the use of Docker image and file assets.

Accessing resources in a different stack

You can access resources in a different stack, as long as they are in the same account and AWS Region (see next section for an exception). The following example defines the stack stack1, which defines an Amazon S3 bucket. Then it defines a second stack, stack2, which takes the bucket from stack1 as a constructor property.

prod = {"account": "123456789012", "region": "us-east-1"}

stack1 = StackThatProvidesABucket(app, "Stack1", env=prod)

# stack2 will take a property { bucket: IBucket }
stack2 = StackThatExpectsABucket(app, "Stack2",
    bucket=stack1.bucket,
    env=prod
)

If the AWS CDK determines that the resource is in the same account and Region, but in a different stack, it automatically synthesizes AWS CloudFormation Exports in the producing stack and an Fn::ImportValue in the consuming stack to transfer that information from one stack to the other.

Accessing resources in a different stack and region

> This feature is currently experimental

You can enable the Stack property crossRegionReferences in order to access resources in a different stack and region. With this feature flag enabled it is possible to do something like creating a CloudFront distribution in us-east-2 and an ACM certificate in us-east-1.

stack1 = Stack(app, "Stack1",
    env=Environment(
        region="us-east-1"
    ),
    cross_region_references=True
)
cert = acm.Certificate(stack1, "Cert",
    domain_name="*.example.com",
    validation=acm.CertificateValidation.from_dns(route53.PublicHostedZone.from_hosted_zone_id(stack1, "Zone", "Z0329774B51CGXTDQV3X"))
)

stack2 = Stack(app, "Stack2",
    env=Environment(
        region="us-east-2"
    ),
    cross_region_references=True
)
cloudfront.Distribution(stack2, "Distribution",
    default_behavior=cloudfront.BehaviorOptions(
        origin=origins.HttpOrigin("example.com")
    ),
    domain_names=["dev.example.com"],
    certificate=cert
)

When the AWS CDK determines that the resource is in a different stack and is in a different region, it will "export" the value by creating a custom resource in the producing stack which creates SSM Parameters in the consuming region for each exported value. The parameters will be created with the name '/cdk/exports/${consumingStackName}/${export-name}'. In order to "import" the exports into the consuming stack a SSM Dynamic reference is used to reference the SSM parameter which was created.

In order to mimic strong references, a Custom Resource is also created in the consuming stack which marks the SSM parameters as being "imported". When a parameter has been successfully imported, the producing stack cannot update the value.

> [!NOTE] > As a consequence of this feature being built on a Custom Resource, we are restricted to a > CloudFormation response body size limitation of 4096 bytes. > To prevent deployment errors related to the Custom Resource Provider response body being too > large, we recommend limiting the use of nested stacks and minimizing the length of stack names. > Doing this will prevent SSM parameter names from becoming too long which will reduce the size of the > response body.

See the adr for more details on this feature.

Removing automatic cross-stack references

The automatic references created by CDK when you use resources across stacks are convenient, but may block your deployments if you want to remove the resources that are referenced in this way. You will see an error like:

Export Stack1:ExportsOutputFnGetAtt-****** cannot be deleted as it is in use by Stack1

Let's say there is a Bucket in the stack1, and the stack2 references its bucket.bucketName. You now want to remove the bucket and run into the error above.

It's not safe to remove stack1.bucket while stack2 is still using it, so unblocking yourself from this is a two-step process. This is how it works:

DEPLOYMENT 1: break the relationship

• Make sure stack2 no longer references bucket.bucketName (maybe the consumer stack now uses its own bucket, or it writes to an AWS DynamoDB table, or maybe you just remove the Lambda Function altogether).
• In the stack1 class, call this.exportValue(this.bucket.bucketName). This will make sure the CloudFormation Export continues to exist while the relationship between the two stacks is being broken.
• Deploy (this will effectively only change the stack2, but it's safe to deploy both).

DEPLOYMENT 2: remove the resource

• You are now free to remove the bucket resource from stack1.
• Don't forget to remove the exportValue() call as well.
• Deploy again (this time only the stack1 will be changed -- the bucket will be deleted).

Durations

To make specifications of time intervals unambiguous, a single class called Duration is used throughout the AWS Construct Library by all constructs that that take a time interval as a parameter (be it for a timeout, a rate, or something else).

An instance of Duration is constructed by using one of the static factory methods on it:

Duration.seconds(300) # 5 minutes
Duration.minutes(5) # 5 minutes
Duration.hours(1) # 1 hour
Duration.days(7) # 7 days
Duration.parse("PT5M")

Durations can be added or subtracted together:

Duration.minutes(1).plus(Duration.seconds(60)) # 2 minutes
Duration.minutes(5).minus(Duration.seconds(10))

Size (Digital Information Quantity)

To make specification of digital storage quantities unambiguous, a class called Size is available.

An instance of Size is initialized through one of its static factory methods:

Size.kibibytes(200) # 200 KiB
Size.mebibytes(5) # 5 MiB
Size.gibibytes(40) # 40 GiB
Size.tebibytes(200) # 200 TiB
Size.pebibytes(3)

Instances of Size created with one of the units can be converted into others. By default, conversion to a higher unit will fail if the conversion does not produce a whole number. This can be overridden by unsetting integral property.

Size.mebibytes(2).to_kibibytes() # yields 2048
Size.kibibytes(2050).to_mebibytes(rounding=SizeRoundingBehavior.FLOOR)

Secrets

To help avoid accidental storage of secrets as plain text, we use the SecretValue type to represent secrets. Any construct that takes a value that should be a secret (such as a password or an access key) will take a parameter of type SecretValue.

The best practice is to store secrets in AWS Secrets Manager and reference them using SecretValue.secretsManager:

secret = SecretValue.secrets_manager("secretId",
    json_field="password",  # optional: key of a JSON field to retrieve (defaults to all content),
    version_id="id",  # optional: id of the version (default AWSCURRENT)
    version_stage="stage"
)

Using AWS Secrets Manager is the recommended way to reference secrets in a CDK app. SecretValue also supports the following secret sources:

• SecretValue.unsafePlainText(secret): stores the secret as plain text in your app and the resulting template (not recommended).
• SecretValue.secretsManager(secret): refers to a secret stored in Secrets Manager
• SecretValue.ssmSecure(param, version): refers to a secret stored as a SecureString in the SSM Parameter Store. If you don't specify the exact version, AWS CloudFormation uses the latest version of the parameter.
• SecretValue.cfnParameter(param): refers to a secret passed through a CloudFormation parameter (must have NoEcho: true).
• SecretValue.cfnDynamicReference(dynref): refers to a secret described by a CloudFormation dynamic reference (used by ssmSecure and secretsManager).
• SecretValue.resourceAttribute(attr): refers to a secret returned from a CloudFormation resource creation.

SecretValues should only be passed to constructs that accept properties of type SecretValue. These constructs are written to ensure your secrets will not be exposed where they shouldn't be. If you try to use a SecretValue in a different location, an error about unsafe secret usage will be thrown at synthesis time.

If you rotate the secret's value in Secrets Manager, you must also change at least one property on the resource where you are using the secret, to force CloudFormation to re-read the secret.

SecretValue.ssmSecure() is only supported for a limited set of resources. Click here for a list of supported resources and properties.

ARN manipulation

Sometimes you will need to put together or pick apart Amazon Resource Names (ARNs). The functions stack.formatArn() and stack.splitArn() exist for this purpose.

formatArn() can be used to build an ARN from components. It will automatically use the region and account of the stack you're calling it on:

# stack: Stack


# Builds "arn::lambda:::function:MyFunction"
stack.format_arn(
    service="lambda",
    resource="function",
    arn_format=ArnFormat.COLON_RESOURCE_NAME,
    resource_name="MyFunction"
)

splitArn() can be used to get a single component from an ARN. splitArn() will correctly deal with both literal ARNs and deploy-time values (tokens), but in case of a deploy-time value be aware that the result will be another deploy-time value which cannot be inspected in the CDK application.

# stack: Stack


# Extracts the function name out of an AWS Lambda Function ARN
arn_components = stack.split_arn(arn, ArnFormat.COLON_RESOURCE_NAME)
function_name = arn_components.resource_name

Note that the format of the resource separator depends on the service and may be any of the values supported by ArnFormat. When dealing with these functions, it is important to know the format of the ARN you are dealing with.

For an exhaustive list of ARN formats used in AWS, see AWS ARNs and Namespaces in the AWS General Reference.

Dependencies

Construct Dependencies

Sometimes AWS resources depend on other resources, and the creation of one resource must be completed before the next one can be started.

In general, CloudFormation will correctly infer the dependency relationship between resources based on the property values that are used. In the cases where it doesn't, the AWS Construct Library will add the dependency relationship for you.

If you need to add an ordering dependency that is not automatically inferred, you do so by adding a dependency relationship using constructA.node.addDependency(constructB). This will add a dependency relationship between all resources in the scope of constructA and all resources in the scope of constructB.

If you want a single object to represent a set of constructs that are not necessarily in the same scope, you can use a DependencyGroup. The following creates a single object that represents a dependency on two constructs, constructB and constructC:

# Declare the dependable object
b_and_c = DependencyGroup()
b_and_c.add(construct_b)
b_and_c.add(construct_c)

# Take the dependency
construct_a.node.add_dependency(b_and_c)

Stack Dependencies

Two different stack instances can have a dependency on one another. This happens when an resource from one stack is referenced in another stack. In that case, CDK records the cross-stack referencing of resources, automatically produces the right CloudFormation primitives, and adds a dependency between the two stacks. You can also manually add a dependency between two stacks by using the stackA.addDependency(stackB) method.

A stack dependency has the following implications:

• Cyclic dependencies are not allowed, so if stackA is using resources from stackB, the reverse is not possible anymore.

• Stacks with dependencies between them are treated specially by the CDK toolkit:

  • If stackA depends on stackB, running cdk deploy stackA will also automatically deploy stackB.
  • stackB's deployment will be performed before stackA's deployment.

CfnResource Dependencies

To make declaring dependencies between CfnResource objects easier, you can declare dependencies from one CfnResource object on another by using the cfnResource1.addDependency(cfnResource2) method. This method will work for resources both within the same stack and across stacks as it detects the relative location of the two resources and adds the dependency either to the resource or between the relevant stacks, as appropriate. If more complex logic is in needed, you can similarly remove, replace, or view dependencies between CfnResource objects with the CfnResource removeDependency, replaceDependency, and obtainDependencies methods, respectively.

Custom Resources

Custom Resources are CloudFormation resources that are implemented by arbitrary user code. They can do arbitrary lookups or modifications during a CloudFormation deployment.

Custom resources are backed by custom resource providers. Commonly, these are Lambda Functions that are deployed in the same deployment as the one that defines the custom resource itself, but they can also be backed by Lambda Functions deployed previously, or code responding to SNS Topic events running on EC2 instances in a completely different account. For more information on custom resource providers, see the next section.

Once you have a provider, each definition of a CustomResource construct represents one invocation. A single provider can be used for the implementation of arbitrarily many custom resource definitions. A single definition looks like this:

CustomResource(self, "MyMagicalResource",
    resource_type="Custom::MyCustomResource",  # must start with 'Custom::'

    # the resource properties
    properties={
        "Property1": "foo",
        "Property2": "bar"
    },

    # the ARN of the provider (SNS/Lambda) which handles
    # CREATE, UPDATE or DELETE events for this resource type
    # see next section for details
    service_token="ARN"
)

Custom Resource Providers

Custom resources are backed by a custom resource provider which can be implemented in one of the following ways. The following table compares the various provider types (ordered from low-level to high-level):

Provider	Compute Type	Error Handling	Submit to CloudFormation	Max Timeout	Language	Footprint
sns.Topic	Self-managed	Manual	Manual	Unlimited	Any	Depends
lambda.Function	AWS Lambda	Manual	Manual	15min	Any	Small
core.CustomResourceProvider	AWS Lambda	Auto	Auto	15min	Node.js	Small
custom-resources.Provider	AWS Lambda	Auto	Auto	Unlimited Async	Any	Large

Legend:

• Compute type: which type of compute can be used to execute the handler.
• Error Handling: whether errors thrown by handler code are automatically trapped and a FAILED response is submitted to CloudFormation. If this is "Manual", developers must take care of trapping errors. Otherwise, events could cause stacks to hang.
• Submit to CloudFormation: whether the framework takes care of submitting SUCCESS/FAILED responses to CloudFormation through the event's response URL.
• Max Timeout: maximum allows/possible timeout.
• Language: which programming languages can be used to implement handlers.
• Footprint: how many resources are used by the provider framework itself.

A NOTE ABOUT SINGLETONS

When defining resources for a custom resource provider, you will likely want to define them as a stack singleton so that only a single instance of the provider is created in your stack and which is used by all custom resources of that type.

Here is a basic pattern for defining stack singletons in the CDK. The following examples ensures that only a single SNS topic is defined:

def get_or_create(self, scope):
    stack = Stack.of(scope)
    uniqueid = "GloballyUniqueIdForSingleton" # For example, a UUID from `uuidgen`
    existing = stack.node.try_find_child(uniqueid)
    if existing:
        return existing
    return sns.Topic(stack, uniqueid)

Amazon SNS Topic

Every time a resource event occurs (CREATE/UPDATE/DELETE), an SNS notification is sent to the SNS topic. Users must process these notifications (e.g. through a fleet of worker hosts) and submit success/failure responses to the CloudFormation service.

> You only need to use this type of provider if your custom resource cannot run on AWS Lambda, for reasons other than the 15 > minute timeout. If you are considering using this type of provider because you want to write a custom resource provider that may need > to wait for more than 15 minutes for the API calls to stabilize, have a look at the custom-resources module first. > > Refer to the CloudFormation Custom Resource documentation for information on the contract your custom resource needs to adhere to.

Set serviceToken to topic.topicArn in order to use this provider:

topic = sns.Topic(self, "MyProvider")

CustomResource(self, "MyResource",
    service_token=topic.topic_arn
)

AWS Lambda Function

An AWS lambda function is called directly by CloudFormation for all resource events. The handler must take care of explicitly submitting a success/failure response to the CloudFormation service and handle various error cases.

> We do not recommend you use this provider type. The CDK has wrappers around Lambda Functions that make them easier to work with. > > If you do want to use this provider, refer to the CloudFormation Custom Resource documentation for information on the contract your custom resource needs to adhere to.

Set serviceToken to lambda.functionArn to use this provider:

fn = lambda_.SingletonFunction(self, "MyProvider", function_props)

CustomResource(self, "MyResource",
    service_token=fn.function_arn
)

The core.CustomResourceProvider class

The class @aws-cdk/core.CustomResourceProvider offers a basic low-level framework designed to implement simple and slim custom resource providers. It currently only supports Node.js-based user handlers, represents permissions as raw JSON blobs instead of iam.PolicyStatement objects, and it does not have support for asynchronous waiting (handler cannot exceed the 15min lambda timeout). The CustomResourceProviderRuntime supports runtime nodejs12.x, nodejs14.x, nodejs16.x, nodejs18.x.

> As an application builder, we do not recommend you use this provider type. This provider exists purely for custom resources that are part of the AWS Construct Library. > > The custom-resources provider is more convenient to work with and more fully-featured.

The provider has a built-in singleton method which uses the resource type as a stack-unique identifier and returns the service token:

service_token = CustomResourceProvider.get_or_create(self, "Custom::MyCustomResourceType",
    code_directory=f"{__dirname}/my-handler",
    runtime=CustomResourceProviderRuntime.NODEJS_18_X,
    description="Lambda function created by the custom resource provider"
)

CustomResource(self, "MyResource",
    resource_type="Custom::MyCustomResourceType",
    service_token=service_token
)

The directory (my-handler in the above example) must include an index.js file. It cannot import external dependencies or files outside this directory. It must export an async function named handler. This function accepts the CloudFormation resource event object and returns an object with the following structure:

exports.handler = async function(event) {
  const id = event.PhysicalResourceId; // only for "Update" and "Delete"
  const props = event.ResourceProperties;
  const oldProps = event.OldResourceProperties; // only for "Update"s

  switch (event.RequestType) {
    case "Create":
      // ...

    case "Update":
      // ...

      // if an error is thrown, a FAILED response will be submitted to CFN
      throw new Error('Failed!');

    case "Delete":
      // ...
  }

  return {
    // (optional) the value resolved from `resource.ref`
    // defaults to "event.PhysicalResourceId" or "event.RequestId"
    PhysicalResourceId: "REF",

    // (optional) calling `resource.getAtt("Att1")` on the custom resource in the CDK app
    // will return the value "BAR".
    Data: {
      Att1: "BAR",
      Att2: "BAZ"
    },

    // (optional) user-visible message
    Reason: "User-visible message",

    // (optional) hides values from the console
    NoEcho: true
  };
}

Here is an complete example of a custom resource that summarizes two numbers:

sum-handler/index.js:

exports.handler = async (e) => {
  return {
    Data: {
      Result: e.ResourceProperties.lhs + e.ResourceProperties.rhs,
    },
  };
};

sum.ts:

from constructs import Construct
from aws_cdk import CustomResource, CustomResourceProvider, CustomResourceProviderRuntime, Token

class Sum(Construct):

    def __init__(self, scope, id, *, lhs, rhs):
        super().__init__(scope, id)

        resource_type = "Custom::Sum"
        service_token = CustomResourceProvider.get_or_create(self, resource_type,
            code_directory=f"{__dirname}/sum-handler",
            runtime=CustomResourceProviderRuntime.NODEJS_18_X
        )

        resource = CustomResource(self, "Resource",
            resource_type=resource_type,
            service_token=service_token,
            properties={
                "lhs": lhs,
                "rhs": rhs
            }
        )

        self.result = Token.as_number(resource.get_att("Result"))

Usage will look like this:

sum = Sum(self, "MySum", lhs=40, rhs=2)
CfnOutput(self, "Result", value=Token.as_string(sum.result))

To access the ARN of the provider's AWS Lambda function role, use the getOrCreateProvider() built-in singleton method:

provider = CustomResourceProvider.get_or_create_provider(self, "Custom::MyCustomResourceType",
    code_directory=f"{__dirname}/my-handler",
    runtime=CustomResourceProviderRuntime.NODEJS_18_X
)

role_arn = provider.role_arn

This role ARN can then be used in resource-based IAM policies.

To add IAM policy statements to this role, use addToRolePolicy():

provider = CustomResourceProvider.get_or_create_provider(self, "Custom::MyCustomResourceType",
    code_directory=f"{__dirname}/my-handler",
    runtime=CustomResourceProviderRuntime.NODEJS_18_X
)
provider.add_to_role_policy({
    "Effect": "Allow",
    "Action": "s3:GetObject",
    "Resource": "*"
})

Note that addToRolePolicy() uses direct IAM JSON policy blobs, not a iam.PolicyStatement object like you will see in the rest of the CDK.

The Custom Resource Provider Framework

The @aws-cdk/custom-resources module includes an advanced framework for implementing custom resource providers.

Handlers are implemented as AWS Lambda functions, which means that they can be implemented in any Lambda-supported runtime. Furthermore, this provider has an asynchronous mode, which means that users can provide an isComplete lambda function which is called periodically until the operation is complete. This allows implementing providers that can take up to two hours to stabilize.

Set serviceToken to provider.serviceToken to use this type of provider:

provider = customresources.Provider(self, "MyProvider",
    on_event_handler=on_event_handler,
    is_complete_handler=is_complete_handler
)

CustomResource(self, "MyResource",
    service_token=provider.service_token
)

See the documentation for more details.

AWS CloudFormation features

A CDK stack synthesizes to an AWS CloudFormation Template. This section explains how this module allows users to access low-level CloudFormation features when needed.

Stack Outputs

CloudFormation stack outputs and exports are created using the CfnOutput class:

CfnOutput(self, "OutputName",
    value=my_bucket.bucket_name,
    description="The name of an S3 bucket",  # Optional
    export_name="TheAwesomeBucket"
)

Parameters

CloudFormation templates support the use of Parameters to customize a template. They enable CloudFormation users to input custom values to a template each time a stack is created or updated. While the CDK design philosophy favors using build-time parameterization, users may need to use CloudFormation in a number of cases (for example, when migrating an existing stack to the AWS CDK).

Template parameters can be added to a stack by using the CfnParameter class:

CfnParameter(self, "MyParameter",
    type="Number",
    default=1337
)

The value of parameters can then be obtained using one of the value methods. As parameters are only resolved at deployment time, the values obtained are placeholder tokens for the real value (Token.isUnresolved() would return true for those):

param = CfnParameter(self, "ParameterName")

# If the parameter is a String
param.value_as_string

# If the parameter is a Number
param.value_as_number

# If the parameter is a List
param.value_as_list

Pseudo Parameters

CloudFormation supports a number of pseudo parameters, which resolve to useful values at deployment time. CloudFormation pseudo parameters can be obtained from static members of the Aws class.

It is generally recommended to access pseudo parameters from the scope's stack instead, which guarantees the values produced are qualifying the designated stack, which is essential in cases where resources are shared cross-stack:

# "this" is the current construct
stack = Stack.of(self)

stack.account # Returns the AWS::AccountId for this stack (or the literal value if known)
stack.region # Returns the AWS::Region for this stack (or the literal value if known)
stack.partition

Resource Options

CloudFormation resources can also specify resource attributes. The CfnResource class allows accessing those through the cfnOptions property:

raw_bucket = s3.CfnBucket(self, "Bucket")
# -or-
raw_bucket_alt = my_bucket.node.default_child

# then
raw_bucket.cfn_options.condition = CfnCondition(self, "EnableBucket")
raw_bucket.cfn_options.metadata = {
    "metadata_key": "MetadataValue"
}

Resource dependencies (the DependsOn attribute) is modified using the cfnResource.addDependency method:

resource_a = CfnResource(self, "ResourceA", resource_props)
resource_b = CfnResource(self, "ResourceB", resource_props)

resource_b.add_dependency(resource_a)

CreationPolicy

Some resources support a CreationPolicy to be specified as a CfnOption.

The creation policy is invoked only when AWS CloudFormation creates the associated resource. Currently, the only AWS CloudFormation resources that support creation policies are CfnAutoScalingGroup, CfnInstance, CfnWaitCondition and CfnFleet.

The CfnFleet resource from the aws-appstream module supports specifying startFleet as a property of the creationPolicy on the resource options. Setting it to true will make AWS CloudFormation wait until the fleet is started before continuing with the creation of resources that depend on the fleet resource.

fleet = appstream.CfnFleet(self, "Fleet",
    instance_type="stream.standard.small",
    name="Fleet",
    compute_capacity=appstream.CfnFleet.ComputeCapacityProperty(
        desired_instances=1
    ),
    image_name="AppStream-AmazonLinux2-09-21-2022"
)
fleet.cfn_options.creation_policy = CfnCreationPolicy(
    start_fleet=True
)

The properties passed to the level 2 constructs AutoScalingGroup and Instance from the aws-ec2 module abstract what is passed into the CfnOption properties resourceSignal and autoScalingCreationPolicy, but when using level 1 constructs you can specify these yourself.

The CfnWaitCondition resource from the aws-cloudformation module suppports the resourceSignal. The format of the timeout is PT#H#M#S. In the example below AWS Cloudformation will wait for 3 success signals to occur within 15 minutes before the status of the resource will be set to CREATE_COMPLETE.

# resource: CfnResource


resource.cfn_options.creation_policy = CfnCreationPolicy(
    resource_signal=CfnResourceSignal(
        count=3,
        timeout="PR15M"
    )
)

Intrinsic Functions and Condition Expressions

CloudFormation supports intrinsic functions. These functions can be accessed from the Fn class, which provides type-safe methods for each intrinsic function as well as condition expressions:

# my_object_or_array: Any
# my_array: Any


# To use Fn::Base64
Fn.base64("SGVsbG8gQ0RLIQo=")

# To compose condition expressions:
environment_parameter = CfnParameter(self, "Environment")
Fn.condition_and(
    # The "Environment" CloudFormation template parameter evaluates to "Production"
    Fn.condition_equals("Production", environment_parameter),
    # The AWS::Region pseudo-parameter value is NOT equal to "us-east-1"
    Fn.condition_not(Fn.condition_equals("us-east-1", Aws.REGION)))

# To use Fn::ToJsonString
Fn.to_json_string(my_object_or_array)

# To use Fn::Length
Fn.len(Fn.split(",", my_array))

When working with deploy-time values (those for which Token.isUnresolved returns true), idiomatic conditionals from the programming language cannot be used (the value will not be known until deployment time). When conditional logic needs to be expressed with un-resolved values, it is necessary to use CloudFormation conditions by means of the CfnCondition class:

environment_parameter = CfnParameter(self, "Environment")
is_prod = CfnCondition(self, "IsProduction",
    expression=Fn.condition_equals("Production", environment_parameter)
)

# Configuration value that is a different string based on IsProduction
stage = Fn.condition_if(is_prod.logical_id, "Beta", "Prod").to_string()

# Make Bucket creation condition to IsProduction by accessing
# and overriding the CloudFormation resource
bucket = s3.Bucket(self, "Bucket")
cfn_bucket = my_bucket.node.default_child
cfn_bucket.cfn_options.condition = is_prod

Mappings

CloudFormation mappings are created and queried using the CfnMappings class:

region_table = CfnMapping(self, "RegionTable",
    mapping={
        "us-east-1": {
            "region_name": "US East (N. Virginia)"
        },
        "us-east-2": {
            "region_name": "US East (Ohio)"
        }
    }
)

region_table.find_in_map(Aws.REGION, "regionName")

This will yield the following template:

Mappings:
  RegionTable:
    us-east-1:
      regionName: US East (N. Virginia)
    us-east-2:
      regionName: US East (Ohio)

Mappings can also be synthesized "lazily"; lazy mappings will only render a "Mappings" section in the synthesized CloudFormation template if some findInMap call is unable to immediately return a concrete value due to one or both of the keys being unresolved tokens (some value only available at deploy-time).

For example, the following code will not produce anything in the "Mappings" section. The call to findInMap will be able to resolve the value during synthesis and simply return 'US East (Ohio)'.

region_table = CfnMapping(self, "RegionTable",
    mapping={
        "us-east-1": {
            "region_name": "US East (N. Virginia)"
        },
        "us-east-2": {
            "region_name": "US East (Ohio)"
        }
    },
    lazy=True
)

region_table.find_in_map("us-east-2", "regionName")

On the other hand, the following code will produce the "Mappings" section shown above, since the top-level key is an unresolved token. The call to findInMap will return a token that resolves to { "Fn::FindInMap": [ "RegionTable", { "Ref": "AWS::Region" }, "regionName" ] }.

# region_table: CfnMapping


region_table.find_in_map(Aws.REGION, "regionName")

An optional default value can also be passed to findInMap. If either key is not found in the map and the mapping is lazy, findInMap will return the default value and not render the mapping. If the mapping is not lazy or either key is an unresolved token, the call to findInMap will return a token that resolves to { "Fn::FindInMap": [ "MapName", "TopLevelKey", "SecondLevelKey", { "DefaultValue": "DefaultValue" } ] }, and the mapping will be rendered. Note that the AWS::LanguageExtentions transform is added to enable the default value functionality.

For example, the following code will again not produce anything in the "Mappings" section. The call to findInMap will be able to resolve the value during synthesis and simply return 'Region not found'.

region_table = CfnMapping(self, "RegionTable",
    mapping={
        "us-east-1": {
            "region_name": "US East (N. Virginia)"
        },
        "us-east-2": {
            "region_name": "US East (Ohio)"
        }
    },
    lazy=True
)

region_table.find_in_map("us-west-1", "regionName", "Region not found")

Dynamic References

CloudFormation supports dynamically resolving values for SSM parameters (including secure strings) and Secrets Manager. Encoding such references is done using the CfnDynamicReference class:

CfnDynamicReference(CfnDynamicReferenceService.SECRETS_MANAGER, "secret-id:secret-string:json-key:version-stage:version-id")

Template Options & Transform

CloudFormation templates support a number of options, including which Macros or Transforms to use when deploying the stack. Those can be configured using the stack.templateOptions property:

stack = Stack(app, "StackName")

stack.template_options.description = "This will appear in the AWS console"
stack.template_options.transforms = ["AWS::Serverless-2016-10-31"]
stack.template_options.metadata = {
    "metadata_key": "MetadataValue"
}

Emitting Raw Resources

The CfnResource class allows emitting arbitrary entries in the Resources section of the CloudFormation template.

CfnResource(self, "ResourceId",
    type="AWS::S3::Bucket",
    properties={
        "BucketName": "amzn-s3-demo-bucket"
    }
)

As for any other resource, the logical ID in the CloudFormation template will be generated by the AWS CDK, but the type and properties will be copied verbatim in the synthesized template.

Including raw CloudFormation template fragments

When migrating a CloudFormation stack to the AWS CDK, it can be useful to include fragments of an existing template verbatim in the synthesized template. This can be achieved using the CfnInclude class.

CfnInclude(self, "ID",
    template={
        "Resources": {
            "Bucket": {
                "Type": "AWS::S3::Bucket",
                "Properties": {
                    "BucketName": "amzn-s3-demo-bucket"
                }
            }
        }
    }
)

Termination Protection

You can prevent a stack from being accidentally deleted by enabling termination protection on the stack. If a user attempts to delete a stack with termination protection enabled, the deletion fails and the stack--including its status--remains unchanged. Enabling or disabling termination protection on a stack sets it for any nested stacks belonging to that stack as well. You can enable termination protection on a stack by setting the terminationProtection prop to true.

stack = Stack(app, "StackName",
    termination_protection=True
)

You can also set termination protection with the setter after you've instantiated the stack.

stack = Stack(app, "StackName")
stack.termination_protection = True

By default, termination protection is disabled.

Description

You can add a description of the stack in the same way as StackProps.

stack = Stack(app, "StackName",
    description="This is a description."
)

CfnJson

CfnJson allows you to postpone the resolution of a JSON blob from deployment-time. This is useful in cases where the CloudFormation JSON template cannot express a certain value.

A common example is to use CfnJson in order to render a JSON map which needs to use intrinsic functions in keys. Since JSON map keys must be strings, it is impossible to use intrinsics in keys and CfnJson can help.

The following example defines an IAM role which can only be assumed by principals that are tagged with a specific tag.

tag_param = CfnParameter(self, "TagName")

string_equals = CfnJson(self, "ConditionJson",
    value={
        "f"aws:PrincipalTag/{tagParam.valueAsString}"": True
    }
)

principal = iam.AccountRootPrincipal().with_conditions({
    "StringEquals": string_equals
})

iam.Role(self, "MyRole", assumed_by=principal)

Explanation: since in this example we pass the tag name through a parameter, it can only be resolved during deployment. The resolved value can be represented in the template through a { "Ref": "TagName" }. However, since we want to use this value inside a aws:PrincipalTag/TAG-NAME IAM operator, we need it in the key of a StringEquals condition. JSON keys must be strings, so to circumvent this limitation, we use CfnJson to "delay" the rendition of this template section to deploy-time. This means that the value of StringEquals in the template will be { "Fn::GetAtt": [ "ConditionJson", "Value" ] }, and will only "expand" to the operator we synthesized during deployment.

Stack Resource Limit

When deploying to AWS CloudFormation, it needs to keep in check the amount of resources being added inside a Stack. Currently it's possible to check the limits in the AWS CloudFormation quotas page.

It's possible to synthesize the project with more Resources than the allowed (or even reduce the number of Resources).

Set the context key @aws-cdk/core:stackResourceLimit with the proper value, being 0 for disable the limit of resources.

Template Indentation

The AWS CloudFormation templates generated by CDK include indentation by default. Indentation makes the templates more readable, but also increases their size, and CloudFormation templates cannot exceed 1MB.

It's possible to reduce the size of your templates by suppressing indentation.

To do this for all templates, set the context key @aws-cdk/core:suppressTemplateIndentation to true.

To do this for a specific stack, add a suppressTemplateIndentation: true property to the stack's StackProps parameter. You can also set this property to false to override the context key setting.

App Context

Context values are key-value pairs that can be associated with an app, stack, or construct. One common use case for context is to use it for enabling/disabling feature flags. There are several places where context can be specified. They are listed below in the order they are evaluated (items at the top take precedence over those below).

• The node.setContext() method
• The postCliContext prop when you create an App
• The CLI via the --context CLI argument
• The cdk.json file via the context key:
• The cdk.context.json file:
• The ~/.cdk.json file via the context key:
• The context prop when you create an App

Examples of setting context

App(
    context={
        "@aws-cdk/core:newStyleStackSynthesis": True
    }
)

app = App()
app.node.set_context("@aws-cdk/core:newStyleStackSynthesis", True)

App(
    post_cli_context={
        "@aws-cdk/core:newStyleStackSynthesis": True
    }
)

cdk synth --context @aws-cdk/core:newStyleStackSynthesis=true

cdk.json

{
  "context": {
    "@aws-cdk/core:newStyleStackSynthesis": true
  }
}

cdk.context.json

{
  "@aws-cdk/core:newStyleStackSynthesis": true
}

~/.cdk.json

{
  "context": {
    "@aws-cdk/core:newStyleStackSynthesis": true
  }
}

IAM Permissions Boundary

It is possible to apply an IAM permissions boundary to all roles within a specific construct scope. The most common use case would be to apply a permissions boundary at the Stage level.

prod_stage = Stage(app, "ProdStage",
    permissions_boundary=PermissionsBoundary.from_name("cdk-${Qualifier}-PermissionsBoundary")
)

Any IAM Roles or Users created within this Stage will have the default permissions boundary attached.

For more details see the Permissions Boundary section in the IAM guide.

Policy Validation

If you or your organization use (or would like to use) any policy validation tool, such as CloudFormation Guard or OPA, to define constraints on your CloudFormation template, you can incorporate them into the CDK application. By using the appropriate plugin, you can make the CDK application check the generated CloudFormation templates against your policies immediately after synthesis. If there are any violations, the synthesis will fail and a report will be printed to the console or to a file (see below).

> Note > This feature is considered experimental, and both the plugin API and the > format of the validation report are subject to change in the future.

For application developers

To use one or more validation plugins in your application, use the policyValidationBeta1 property of Stage:

# globally for the entire app (an app is a stage)
app = App(
    policy_validation_beta1=[
        # These hypothetical classes implement IPolicyValidationPluginBeta1:
        ThirdPartyPluginX(),
        ThirdPartyPluginY()
    ]
)

# only apply to a particular stage
prod_stage = Stage(app, "ProdStage",
    policy_validation_beta1=[
        ThirdPartyPluginX()
    ]
)

Immediately after synthesis, all plugins registered this way will be invoked to validate all the templates generated in the scope you defined. In particular, if you register the templates in the App object, all templates will be subject to validation.

> Warning > Other than modifying the cloud assembly, plugins can do anything that your CDK > application can. They can read data from the filesystem, access the network > etc. It's your responsibility as the consumer of a plugin to verify that it is > secure to use.

By default, the report will be printed in a human readable format. If you want a report in JSON format, enable it using the @aws-cdk/core:validationReportJson context passing it directly to the application:

app = App(
    context={"@aws-cdk/core:validationReportJson": True}
)

Alternatively, you can set this context key-value pair using the cdk.json or cdk.context.json files in your project directory (see Runtime context).

If you choose the JSON format, the CDK will print the policy validation report to a file called policy-validation-report.json in the cloud assembly directory. For the default, human-readable format, the report will be printed to the standard output.

For plugin authors

The communication protocol between the CDK core module and your policy tool is defined by the IPolicyValidationPluginBeta1 interface. To create a new plugin you must write a class that implements this interface. There are two things you need to implement: the plugin name (by overriding the name property), and the validate() method.

The framework will call validate(), passing an IPolicyValidationContextBeta1 object. The location of the templates to be validated is given by templatePaths. The plugin should return an instance of PolicyValidationPluginReportBeta1. This object represents the report that the user wil receive at the end of the synthesis.

@jsii.implements(IPolicyValidationPluginBeta1)
class MyPlugin:

    def validate(self, context):
        # First read the templates using context.templatePaths...

        # ...then perform the validation, and then compose and return the report.
        # Using hard-coded values here for better clarity:
        return PolicyValidationPluginReportBeta1(
            success=False,
            violations=[PolicyViolationBeta1(
                rule_name="CKV_AWS_117",
                description="Ensure that AWS Lambda function is configured inside a VPC",
                fix="https://docs.bridgecrew.io/docs/ensure-that-aws-lambda-function-is-configured-inside-a-vpc-1",
                violating_resources=[PolicyViolatingResourceBeta1(
                    resource_logical_id="MyFunction3BAA72D1",
                    template_path="/home/johndoe/myapp/cdk.out/MyService.template.json",
                    locations=["Properties/VpcConfig"]
                )]
            )]
        )

In addition to the name, plugins may optionally report their version (version property ) and a list of IDs of the rules they are going to evaluate (ruleIds property).

Note that plugins are not allowed to modify anything in the cloud assembly. Any attempt to do so will result in synthesis failure.

If your plugin depends on an external tool, keep in mind that some developers may not have that tool installed in their workstations yet. To minimize friction, we highly recommend that you provide some installation script along with your plugin package, to automate the whole process. Better yet, run that script as part of the installation of your package. With npm, for example, you can run add it to the postinstall script in the package.json file.

Annotations

Construct authors can add annotations to constructs to report at three different levels: ERROR, WARN, INFO.

Typically warnings are added for things that are important for the user to be aware of, but will not cause deployment errors in all cases. Some common scenarios are (non-exhaustive list):

• Warn when the user needs to take a manual action, e.g. IAM policy should be added to an referenced resource.
• Warn if the user configuration might not follow best practices (but is still valid)
• Warn if the user is using a deprecated API

Acknowledging Warnings

If you would like to run with --strict mode enabled (warnings will throw errors) it is possible to acknowledge warnings to make the warning go away.

For example, if > 10 IAM managed policies are added to an IAM Group, a warning will be created:

IAM:Group:MaxPoliciesExceeded: You added 11 to IAM Group my-group. The maximum number of managed policies attached to an IAM group is 10.

If you have requested a quota increase you may have the ability to add > 10 managed policies which means that this warning does not apply to you. You can acknowledge this by acknowledging the warning by the id.

Annotations.of(self).acknowledge_warning("IAM:Group:MaxPoliciesExceeded", "Account has quota increased to 20")