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Deploy local files and directories to S3

Project description

AWS CDK Assets



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 This package is no longer being updated, and users should migrate to AWS CDK v2.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.

Assets are local files or directories which are needed by a CDK app. A common example is a directory which contains the handler code for a Lambda function, but assets can represent any artifact that is needed for the app's operation.

When deploying a CDK app that includes constructs with assets, the CDK toolkit will first upload all the assets to S3, and only then deploy the stacks. The S3 locations of the uploaded assets will be passed in as CloudFormation Parameters to the relevant stacks.

The following JavaScript example defines a directory asset which is archived as a .zip file and uploaded to S3 during deployment.

asset = assets.Asset(self, "SampleAsset",
    path=path.join(__dirname, "sample-asset-directory")

The following JavaScript example defines a file asset, which is uploaded as-is to an S3 bucket during deployment.

asset = assets.Asset(self, "SampleAsset",
    path=path.join(__dirname, "file-asset.txt")


Asset constructs expose the following deploy-time attributes:

  • s3BucketName - the name of the assets S3 bucket.
  • s3ObjectKey - the S3 object key of the asset file (whether it's a file or a zip archive)
  • s3ObjectUrl - the S3 object URL of the asset (i.e. s3://mybucket/
  • httpUrl - the S3 HTTP URL of the asset (i.e.

In the following example, the various asset attributes are exported as stack outputs:

asset = assets.Asset(self, "SampleAsset",
    path=path.join(__dirname, "sample-asset-directory")

cdk.CfnOutput(self, "S3BucketName", value=asset.s3_bucket_name)
cdk.CfnOutput(self, "S3ObjectKey", value=asset.s3_object_key)
cdk.CfnOutput(self, "S3HttpURL", value=asset.http_url)
cdk.CfnOutput(self, "S3ObjectURL", value=asset.s3_object_url)


IAM roles, users or groups which need to be able to read assets in runtime will should be granted IAM permissions. To do that use the asset.grantRead(principal) method:

The following example grants an IAM group read permissions on an asset:

group = iam.Group(self, "MyUserGroup")

How does it work

When an asset is defined in a construct, a construct metadata entry aws:cdk:asset is emitted with instructions on where to find the asset and what type of packaging to perform (zip or file). Furthermore, the synthesized CloudFormation template will also include two CloudFormation parameters: one for the asset's bucket and one for the asset S3 key. Those parameters are used to reference the deploy-time values of the asset (using { Ref: "Param" }).

Then, when the stack is deployed, the toolkit will package the asset (i.e. zip the directory), calculate an MD5 hash of the contents and will render an S3 key for this asset within the toolkit's asset store. If the file doesn't exist in the asset store, it is uploaded during deployment.

The toolkit's asset store is an S3 bucket created by the toolkit for each environment the toolkit operates in (environment = account + region).

Now, when the toolkit deploys the stack, it will set the relevant CloudFormation Parameters to point to the actual bucket and key for each asset.

Asset Bundling

When defining an asset, you can use the bundling option to specify a command to run inside a docker container. The command can read the contents of the asset source from /asset-input and is expected to write files under /asset-output (directories mapped inside the container). The files under /asset-output will be zipped and uploaded to S3 as the asset.

The following example uses custom asset bundling to convert a markdown file to html:

asset = assets.Asset(self, "BundledAsset",
    path=path.join(__dirname, "markdown-asset"),  # /asset-input and working directory in the container
        image=DockerImage.from_build(path.join(__dirname, "alpine-markdown")),  # Build an image
        command=["sh", "-c", """
                        markdown > /asset-output/index.html

The bundling docker image (image) can either come from a registry (DockerImage.fromRegistry) or it can be built from a Dockerfile located inside your project (DockerImage.fromBuild).

You can set the CDK_DOCKER environment variable in order to provide a custom docker program to execute. This may sometime be needed when building in environments where the standard docker cannot be executed (see for details).

Use local to specify a local bundling provider. The provider implements a method tryBundle() which should return true if local bundling was performed. If false is returned, docker bundling will be done:

class MyBundle:
    def try_bundle(self, output_dir, *, image, entrypoint=None, command=None, volumes=None, environment=None, workingDirectory=None, user=None, local=None, outputType=None, securityOpt=None):
        can_run_locally = True # replace with actual logic
        if can_run_locally:
            # perform local bundling here
            return True
        return False

assets.Asset(self, "BundledAsset",
        # Docker bundling fallback
        entrypoint=["/bin/sh", "-c"],

Although optional, it's recommended to provide a local bundling method which can greatly improve performance.

If the bundling output contains a single archive file (zip or jar) it will be uploaded to S3 as-is and will not be zipped. Otherwise the contents of the output directory will be zipped and the zip file will be uploaded to S3. This is the default behavior for bundling.outputType (BundlingOutput.AUTO_DISCOVER).

Use BundlingOutput.NOT_ARCHIVED if the bundling output must always be zipped:

asset = assets.Asset(self, "BundledAsset",

Use BundlingOutput.ARCHIVED if the bundling output contains a single archive file and you don't want it to be zipped.

CloudFormation Resource Metadata

NOTE: This section is relevant for authors of AWS Resource Constructs.

In certain situations, it is desirable for tools to be able to know that a certain CloudFormation resource is using a local asset. For example, SAM CLI can be used to invoke AWS Lambda functions locally for debugging purposes.

To enable such use cases, external tools will consult a set of metadata entries on AWS CloudFormation resources:

  • aws:asset:path points to the local path of the asset.
  • aws:asset:property is the name of the resource property where the asset is used

Using these two metadata entries, tools will be able to identify that assets are used by a certain resource, and enable advanced local experiences.

To add these metadata entries to a resource, use the asset.addResourceMetadata(resource, property) method.

See for more details

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