AWS Lambda Construct Library
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This construct library allows you to define AWS Lambda Functions.
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
});
Handler Code
The lambda.Code
class includes static convenience methods for various types of
runtime code.
lambda.Code.fromBucket(bucket, key[, objectVersion])
- specify an S3 object
that contains the archive of your runtime code.lambda.Code.fromInline(code)
- inline the handle code as a string. This is
limited to supported runtimes and the code cannot exceed 4KiB.lambda.Code.fromAsset(path)
- specify a directory or a .zip file in the local
filesystem which will be zipped and uploaded to S3 before deployment. See also
bundling asset code.lambda.Code.fromDockerBuild(path, options)
- use the result of a Docker
build as code. The runtime code is expected to be located at /asset
in the
image and will be zipped and uploaded to S3 as an asset.
The following example shows how to define a Python function and deploy the code
from the local directory my-lambda-handler
to it:
Example of Lambda Code from Local Assets
When deploying a stack that contains this code, the directory will be zip
archived and then uploaded to an S3 bucket, then the exact location of the S3
objects will be passed when the stack is deployed.
During synthesis, the CDK expects to find a directory on disk at the asset
directory specified. Note that we are referencing the asset directory relatively
to our CDK project directory. This is especially important when we want to share
this construct through a library. Different programming languages will have
different techniques for bundling resources into libraries.
Docker Images
Lambda functions allow specifying their handlers within docker images. The docker
image can be an image from ECR or a local asset that the CDK will package and load
into ECR.
The following DockerImageFunction
construct uses a local folder with a
Dockerfile as the asset that will be used as the function handler.
new lambda.DockerImageFunction(this, 'AssetFunction', {
code: lambda.DockerImageCode.fromImageAsset(path.join(__dirname, 'docker-handler')),
});
You can also specify an image that already exists in ECR as the function handler.
import * as ecr from '@aws-cdk/aws-ecr';
const repo = new ecr.Repository(this, 'Repository');
new lambda.DockerImageFunction(this, 'ECRFunction', {
code: lambda.DockerImageCode.fromEcr(repo),
});
The props for these docker image resources allow overriding the image's CMD
, ENTRYPOINT
, and WORKDIR
configurations as well as choosing a specific tag or digest. See their docs for more information.
Execution Role
Lambda functions assume an IAM role during execution. In CDK by default, Lambda
functions will use an autogenerated Role if one is not provided.
The autogenerated Role is automatically given permissions to execute the Lambda
function. To reference the autogenerated Role:
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
});
const role = fn.role;
You can also provide your own IAM role. Provided IAM roles will not automatically
be given permissions to execute the Lambda function. To provide a role and grant
it appropriate permissions:
const myRole = new iam.Role(this, 'My Role', {
assumedBy: new iam.ServicePrincipal('sns.amazonaws.com'),
});
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
role: myRole,
});
myRole.addManagedPolicy(iam.ManagedPolicy.fromAwsManagedPolicyName("service-role/AWSLambdaBasicExecutionRole"));
myRole.addManagedPolicy(iam.ManagedPolicy.fromAwsManagedPolicyName("service-role/AWSLambdaVPCAccessExecutionRole"));
Function Timeout
AWS Lambda functions have a default timeout of 3 seconds, but this can be increased
up to 15 minutes. The timeout is available as a property of Function
so that
you can reference it elsewhere in your stack. For instance, you could use it to create
a CloudWatch alarm to report when your function timed out:
import * as cdk from '@aws-cdk/core';
import * as cloudwatch from '@aws-cdk/aws-cloudwatch';
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
timeout: cdk.Duration.minutes(5),
});
if (fn.timeout) {
new cloudwatch.Alarm(this, `MyAlarm`, {
metric: fn.metricDuration().with({
statistic: 'Maximum',
}),
evaluationPeriods: 1,
datapointsToAlarm: 1,
threshold: fn.timeout.toMilliseconds(),
treatMissingData: cloudwatch.TreatMissingData.IGNORE,
alarmName: 'My Lambda Timeout',
});
}
Resource-based Policies
AWS Lambda supports resource-based policies for controlling access to Lambda
functions and layers on a per-resource basis. In particular, this allows you to
give permission to AWS services and other AWS accounts to modify and invoke your
functions. You can also restrict permissions given to AWS services by providing
a source account or ARN (representing the account and identifier of the resource
that accesses the function or layer).
declare const fn: lambda.Function;
const principal = new iam.ServicePrincipal('my-service');
fn.grantInvoke(principal);
fn.addPermission('my-service Invocation', {
principal: principal,
});
For more information, see Resource-based
policies
in the AWS Lambda Developer Guide.
Providing an unowned principal (such as account principals, generic ARN
principals, service principals, and principals in other accounts) to a call to
fn.grantInvoke
will result in a resource-based policy being created. If the
principal in question has conditions limiting the source account or ARN of the
operation (see above), these conditions will be automatically added to the
resource policy.
declare const fn: lambda.Function;
const servicePrincipal = new iam.ServicePrincipal('my-service');
const sourceArn = 'arn:aws:s3:::my-bucket';
const sourceAccount = '111122223333';
const servicePrincipalWithConditions = servicePrincipal.withConditions({
ArnLike: {
'aws:SourceArn': sourceArn,
},
StringEquals: {
'aws:SourceAccount': sourceAccount,
},
});
fn.grantInvoke(servicePrincipalWithConditions);
fn.addPermission('my-service Invocation', {
principal: servicePrincipal,
sourceArn: sourceArn,
sourceAccount: sourceAccount,
});
Versions
You can use
versions
to manage the deployment of your AWS Lambda functions. For example, you can
publish a new version of a function for beta testing without affecting users of
the stable production version.
The function version includes the following information:
- The function code and all associated dependencies.
- The Lambda runtime that executes the function.
- All of the function settings, including the environment variables.
- A unique Amazon Resource Name (ARN) to identify this version of the function.
You could create a version to your lambda function using the Version
construct.
declare const fn: lambda.Function;
const version = new lambda.Version(this, 'MyVersion', {
lambda: fn,
});
The major caveat to know here is that a function version must always point to a
specific 'version' of the function. When the function is modified, the version
will continue to point to the 'then version' of the function.
One way to ensure that the lambda.Version
always points to the latest version
of your lambda.Function
is to set an environment variable which changes at
least as often as your code does. This makes sure the function always has the
latest code. For instance -
const codeVersion = "stringOrMethodToGetCodeVersion";
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
environment: {
'CodeVersionString': codeVersion,
},
});
The fn.latestVersion
property returns a lambda.IVersion
which represents
the $LATEST
pseudo-version.
However, most AWS services require a specific AWS Lambda version,
and won't allow you to use $LATEST
. Therefore, you would normally want
to use lambda.currentVersion
.
The fn.currentVersion
property can be used to obtain a lambda.Version
resource that represents the AWS Lambda function defined in your application.
Any change to your function's code or configuration will result in the creation
of a new version resource. You can specify options for this version through the
currentVersionOptions
property.
NOTE: The currentVersion
property is only supported when your AWS Lambda function
uses either lambda.Code.fromAsset
or lambda.Code.fromInline
. Other types
of code providers (such as lambda.Code.fromBucket
) require that you define a
lambda.Version
resource directly since the CDK is unable to determine if
their contents had changed.
currentVersion
: Updated hashing logic
To produce a new lambda version each time the lambda function is modified, the
currentVersion
property under the hood, computes a new logical id based on the
properties of the function. This informs CloudFormation that a new
AWS::Lambda::Version
resource should be created pointing to the updated Lambda
function.
However, a bug was introduced in this calculation that caused the logical id to
change when it was not required (ex: when the Function's Tags
property, or
when the DependsOn
clause was modified). This caused the deployment to fail
since the Lambda service does not allow creating duplicate versions.
This has been fixed in the AWS CDK but existing users need to opt-in via a
feature flag. Users who have run cdk init
since this fix will be opted in,
by default.
Otherwise, you will need to enable the feature flag
@aws-cdk/aws-lambda:recognizeVersionProps
. Since CloudFormation does not
allow duplicate versions, you will also need to make some modification to
your function so that a new version can be created. To efficiently and trivially
modify all your lambda functions at once, you can attach the
FunctionVersionUpgrade
aspect to the stack, which slightly alters the
function description. This aspect is intended for one-time use to upgrade the
version of all your functions at the same time, and can safely be removed after
deploying once.
const stack = new Stack();
Aspects.of(stack).add(new lambda.FunctionVersionUpgrade(LAMBDA_RECOGNIZE_VERSION_PROPS));
When the new logic is in effect, you may rarely come across the following error:
The following properties are not recognized as version properties
. This will
occur, typically when property overrides are used, when a new property
introduced in AWS::Lambda::Function
is used that CDK is still unaware of.
To overcome this error, use the API Function.classifyVersionProperty()
to
record whether a new version should be generated when this property is changed.
This can be typically determined by checking whether the property can be
modified using the UpdateFunctionConfiguration API or not.
currentVersion
: Updated hashing logic for layer versions
An additional update to the hashing logic fixes two issues surrounding layers.
Prior to this change, updating the lambda layer version would have no effect on
the function version. Also, the order of lambda layers provided to the function
was unnecessarily baked into the hash.
This has been fixed in the AWS CDK starting with version 2.27. If you ran
cdk init
with an earlier version, you will need to opt-in via a feature flag.
If you run cdk init
with v2.27 or later, this fix will be opted in, by default.
Existing users will need to enable the feature flag
@aws-cdk/aws-lambda:recognizeLayerVersion
. Since CloudFormation does not
allow duplicate versions, they will also need to make some modification to
their function so that a new version can be created. To efficiently and trivially
modify all your lambda functions at once, users can attach the
FunctionVersionUpgrade
aspect to the stack, which slightly alters the
function description. This aspect is intended for one-time use to upgrade the
version of all your functions at the same time, and can safely be removed after
deploying once.
const stack = new Stack();
Aspects.of(stack).add(new lambda.FunctionVersionUpgrade(LAMBDA_RECOGNIZE_LAYER_VERSION));
Aliases
You can define one or more
aliases
for your AWS Lambda function. A Lambda alias is like a pointer to a specific
Lambda function version. Users can access the function version using the alias
ARN.
The version.addAlias()
method can be used to define an AWS Lambda alias that
points to a specific version.
The following example defines an alias named live
which will always point to a
version that represents the function as defined in your CDK app. When you change
your lambda code or configuration, a new resource will be created. You can
specify options for the current version through the currentVersionOptions
property.
const fn = new lambda.Function(this, 'MyFunction', {
currentVersionOptions: {
removalPolicy: RemovalPolicy.RETAIN,
retryAttempts: 1,
},
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
});
fn.addAlias('live');
Function URL
A function URL is a dedicated HTTP(S) endpoint for your Lambda function. When you create a function URL, Lambda automatically generates a unique URL endpoint for you. Function URLs can be created for the latest version Lambda Functions, or Function Aliases (but not for Versions).
Function URLs are dual stack-enabled, supporting IPv4 and IPv6, and cross-origin resource sharing (CORS) configuration. After you configure a function URL for your function, you can invoke your function through its HTTP(S) endpoint via a web browser, curl, Postman, or any HTTP client. To invoke a function using IAM authentication your HTTP client must support SigV4 signing.
See the Invoking Function URLs section of the AWS Lambda Developer Guide
for more information on the input and output payloads of Functions invoked in this way.
IAM-authenticated Function URLs
To create a Function URL which can be called by an IAM identity, call addFunctionUrl()
, followed by grantInvokeFunctionUrl()
:
declare const fn: lambda.Function;
declare const myRole: iam.Role;
const fnUrl = fn.addFunctionUrl();
fnUrl.grantInvokeUrl(myRole);
new CfnOutput(this, 'TheUrl', {
value: fnUrl.url,
});
Calls to this URL need to be signed with SigV4.
Anonymous Function URLs
To create a Function URL which can be called anonymously, pass authType: FunctionUrlAuthType.NONE
to addFunctionUrl()
:
declare const fn: lambda.Function;
const fnUrl = fn.addFunctionUrl({
authType: lambda.FunctionUrlAuthType.NONE,
});
new CfnOutput(this, 'TheUrl', {
value: fnUrl.url,
});
CORS configuration for Function URLs
If you want your Function URLs to be invokable from a web page in browser, you
will need to configure cross-origin resource sharing to allow the call (if you do
not do this, your browser will refuse to make the call):
declare const fn: lambda.Function;
fn.addFunctionUrl({
authType: lambda.FunctionUrlAuthType.NONE,
cors: {
allowedOrigins: ['https://example.com'],
},
});
Layers
The lambda.LayerVersion
class can be used to define Lambda layers and manage
granting permissions to other AWS accounts or organizations.
Example of Lambda Layer usage
By default, updating a layer creates a new layer version, and CloudFormation will delete the old version as part of the stack update.
Alternatively, a removal policy can be used to retain the old version:
new lambda.LayerVersion(this, 'MyLayer', {
removalPolicy: RemovalPolicy.RETAIN,
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
});
Architecture
Lambda functions, by default, run on compute systems that have the 64 bit x86 architecture.
The AWS Lambda service also runs compute on the ARM architecture, which can reduce cost
for some workloads.
A lambda function can be configured to be run on one of these platforms:
new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
architecture: lambda.Architecture.ARM_64,
});
Similarly, lambda layer versions can also be tagged with architectures it is compatible with.
new lambda.LayerVersion(this, 'MyLayer', {
removalPolicy: RemovalPolicy.RETAIN,
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
compatibleArchitectures: [lambda.Architecture.X86_64, lambda.Architecture.ARM_64],
});
Lambda Insights
Lambda functions can be configured to use CloudWatch Lambda Insights
which provides low-level runtime metrics for a Lambda functions.
new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
insightsVersion: lambda.LambdaInsightsVersion.VERSION_1_0_98_0,
});
If the version of insights is not yet available in the CDK, you can also provide the ARN directly as so -
const layerArn = 'arn:aws:lambda:us-east-1:580247275435:layer:LambdaInsightsExtension:14';
new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
insightsVersion: lambda.LambdaInsightsVersion.fromInsightVersionArn(layerArn),
});
If you are deploying an ARM_64 Lambda Function, you must specify a
Lambda Insights Version >= 1_0_119_0
.
new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
architecture: lambda.Architecture.ARM_64,
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
insightsVersion: lambda.LambdaInsightsVersion.VERSION_1_0_119_0,
});
Event Rule Target
You can use an AWS Lambda function as a target for an Amazon CloudWatch event
rule:
import * as events from '@aws-cdk/aws-events';
import * as targets from '@aws-cdk/aws-events-targets';
declare const fn: lambda.Function;
const rule = new events.Rule(this, 'Schedule Rule', {
schedule: events.Schedule.cron({ minute: '0', hour: '4' }),
});
rule.addTarget(new targets.LambdaFunction(fn));
Event Sources
AWS Lambda supports a variety of event sources.
In most cases, it is possible to trigger a function as a result of an event by
using one of the add<Event>Notification
methods on the source construct. For
example, the s3.Bucket
construct has an onEvent
method which can be used to
trigger a Lambda when an event, such as PutObject occurs on an S3 bucket.
An alternative way to add event sources to a function is to use function.addEventSource(source)
.
This method accepts an IEventSource
object. The module @aws-cdk/aws-lambda-event-sources
includes classes for the various event sources supported by AWS Lambda.
For example, the following code adds an SQS queue as an event source for a function:
import * as eventsources from '@aws-cdk/aws-lambda-event-sources';
import * as sqs from '@aws-cdk/aws-sqs';
declare const fn: lambda.Function;
const queue = new sqs.Queue(this, 'Queue');
fn.addEventSource(new eventsources.SqsEventSource(queue));
The following code adds an S3 bucket notification as an event source:
import * as eventsources from '@aws-cdk/aws-lambda-event-sources';
import * as s3 from '@aws-cdk/aws-s3';
declare const fn: lambda.Function;
const bucket = new s3.Bucket(this, 'Bucket');
fn.addEventSource(new eventsources.S3EventSource(bucket, {
events: [ s3.EventType.OBJECT_CREATED, s3.EventType.OBJECT_REMOVED ],
filters: [ { prefix: 'subdir/' } ]
}));
See the documentation for the @aws-cdk/aws-lambda-event-sources module for more details.
Imported Lambdas
When referencing an imported lambda in the CDK, use fromFunctionArn()
for most use cases:
const fn = lambda.Function.fromFunctionArn(
this,
'Function',
'arn:aws:lambda:us-east-1:123456789012:function:MyFn',
);
The fromFunctionAttributes()
API is available for more specific use cases:
const fn = lambda.Function.fromFunctionAttributes(this, 'Function', {
functionArn: 'arn:aws:lambda:us-east-1:123456789012:function:MyFn',
sameEnvironment: true,
skipPermissions: true,
});
If fromFunctionArn()
causes an error related to having to provide an account and/or region in a different construct,
and the lambda is in the same account and region as the stack you're importing it into,
you can use Function.fromFunctionName()
instead:
const fn = lambda.Function.fromFunctionName(this, 'Function', 'MyFn');
Lambda with DLQ
A dead-letter queue can be automatically created for a Lambda function by
setting the deadLetterQueueEnabled: true
configuration. In such case CDK creates
a sqs.Queue
as deadLetterQueue
.
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromInline('exports.handler = function(event, ctx, cb) { return cb(null, "hi"); }'),
deadLetterQueueEnabled: true,
});
It is also possible to provide a dead-letter queue instead of getting a new queue created:
import * as sqs from '@aws-cdk/aws-sqs';
const dlq = new sqs.Queue(this, 'DLQ');
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromInline('exports.handler = function(event, ctx, cb) { return cb(null, "hi"); }'),
deadLetterQueue: dlq,
});
You can also use a sns.Topic
instead of an sqs.Queue
as dead-letter queue:
import * as sns from '@aws-cdk/aws-sns';
const dlt = new sns.Topic(this, 'DLQ');
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromInline('// your code here'),
deadLetterTopic: dlt,
});
See the AWS documentation
to learn more about AWS Lambdas and DLQs.
Lambda with X-Ray Tracing
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromInline('exports.handler = function(event, ctx, cb) { return cb(null, "hi"); }'),
tracing: lambda.Tracing.ACTIVE,
});
See the AWS documentation
to learn more about AWS Lambda's X-Ray support.
Lambda with Profiling
The following code configures the lambda function with CodeGuru profiling. By default, this creates a new CodeGuru
profiling group -
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.PYTHON_3_9,
handler: 'index.handler',
code: lambda.Code.fromAsset('lambda-handler'),
profiling: true,
});
The profilingGroup
property can be used to configure an existing CodeGuru profiler group.
CodeGuru profiling is supported for all Java runtimes and Python3.6+ runtimes.
See the AWS documentation
to learn more about AWS Lambda's Profiling support.
Lambda with Reserved Concurrent Executions
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromInline('exports.handler = function(event, ctx, cb) { return cb(null, "hi"); }'),
reservedConcurrentExecutions: 100,
});
See the AWS documentation
managing concurrency.
AutoScaling
You can use Application AutoScaling to automatically configure the provisioned concurrency for your functions. AutoScaling can be set to track utilization or be based on a schedule. To configure AutoScaling on a function alias:
import * as autoscaling from '@aws-cdk/aws-autoscaling';
declare const fn: lambda.Function;
const alias = fn.addAlias('prod');
const as = alias.addAutoScaling({ maxCapacity: 50 });
as.scaleOnUtilization({
utilizationTarget: 0.5,
});
as.scaleOnSchedule('ScaleUpInTheMorning', {
schedule: autoscaling.Schedule.cron({ hour: '8', minute: '0'}),
minCapacity: 20,
});
Example of Lambda AutoScaling usage
See the AWS documentation on autoscaling lambda functions.
Log Group
Lambda functions automatically create a log group with the name /aws/lambda/<function-name>
upon first execution with
log data set to never expire.
The logRetention
property can be used to set a different expiration period.
It is possible to obtain the function's log group as a logs.ILogGroup
by calling the logGroup
property of the
Function
construct.
By default, CDK uses the AWS SDK retry options when creating a log group. The logRetentionRetryOptions
property
allows you to customize the maximum number of retries and base backoff duration.
Note that, if either logRetention
is set or logGroup
property is called, a CloudFormation custom
resource is added
to the stack that pre-creates the log group as part of the stack deployment, if it already doesn't exist, and sets the
correct log retention period (never expire, by default).
Further note that, if the log group already exists and the logRetention
is not set, the custom resource will reset
the log retention to never expire even if it was configured with a different value.
FileSystem Access
You can configure a function to mount an Amazon Elastic File System (Amazon EFS) to a
directory in your runtime environment with the filesystem
property. To access Amazon EFS
from lambda function, the Amazon EFS access point will be required.
The following sample allows the lambda function to mount the Amazon EFS access point to /mnt/msg
in the runtime environment and access the filesystem with the POSIX identity defined in posixUser
.
import * as ec2 from '@aws-cdk/aws-ec2';
import * as efs from '@aws-cdk/aws-efs';
const vpc = new ec2.Vpc(this, 'VPC');
const fileSystem = new efs.FileSystem(this, 'Efs', { vpc });
const accessPoint = fileSystem.addAccessPoint('AccessPoint', {
path: '/export/lambda',
createAcl: {
ownerUid: '1001',
ownerGid: '1001',
permissions: '750',
},
posixUser: {
uid: '1001',
gid: '1001',
},
});
const fn = new lambda.Function(this, 'MyLambda', {
filesystem: lambda.FileSystem.fromEfsAccessPoint(accessPoint, '/mnt/msg'),
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
vpc,
});
Ephemeral Storage
You can configure ephemeral storage on a function to control the amount of storage it gets for reading
or writing data, allowing you to use AWS Lambda for ETL jobs, ML inference, or other data-intensive workloads.
The ephemeral storage will be accessible in the functions' /tmp
directory.
import { Size } from '@aws-cdk/core';
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
ephemeralStorageSize: Size.mebibytes(1024),
});
Read more about using this feature in this AWS blog post.
Singleton Function
The SingletonFunction
construct is a way to guarantee that a lambda function will be guaranteed to be part of the stack,
once and only once, irrespective of how many times the construct is declared to be part of the stack. This is guaranteed
as long as the uuid
property and the optional lambdaPurpose
property stay the same whenever they're declared into the
stack.
A typical use case of this function is when a higher level construct needs to declare a Lambda function as part of it but
needs to guarantee that the function is declared once. However, a user of this higher level construct can declare it any
number of times and with different properties. Using SingletonFunction
here with a fixed uuid
will guarantee this.
For example, the LogRetention
construct requires only one single lambda function for all different log groups whose
retention it seeks to manage.
Bundling Asset Code
When using lambda.Code.fromAsset(path)
it is possible to bundle the code by running a
command in a Docker container. The asset path will be mounted at /asset-input
. The
Docker container is responsible for putting content at /asset-output
. The content at
/asset-output
will be zipped and used as Lambda code.
Example with Python:
new lambda.Function(this, 'Function', {
code: lambda.Code.fromAsset(path.join(__dirname, 'my-python-handler'), {
bundling: {
image: lambda.Runtime.PYTHON_3_9.bundlingImage,
command: [
'bash', '-c',
'pip install -r requirements.txt -t /asset-output && cp -au . /asset-output'
],
},
}),
runtime: lambda.Runtime.PYTHON_3_9,
handler: 'index.handler',
});
Runtimes expose a bundlingImage
property that points to the AWS SAM build image.
Use cdk.DockerImage.fromRegistry(image)
to use an existing image or
cdk.DockerImage.fromBuild(path)
to build a specific image:
new lambda.Function(this, 'Function', {
code: lambda.Code.fromAsset('/path/to/handler', {
bundling: {
image: DockerImage.fromBuild('/path/to/dir/with/DockerFile', {
buildArgs: {
ARG1: 'value1',
},
}),
command: ['my', 'cool', 'command'],
},
}),
runtime: lambda.Runtime.PYTHON_3_9,
handler: 'index.handler',
});
Language-specific APIs
Language-specific higher level constructs are provided in separate modules:
Code Signing
Code signing for AWS Lambda helps to ensure that only trusted code runs in your Lambda functions.
When enabled, AWS Lambda checks every code deployment and verifies that the code package is signed by a trusted source.
For more information, see Configuring code signing for AWS Lambda.
The following code configures a function with code signing.
import * as signer from '@aws-cdk/aws-signer';
const signingProfile = new signer.SigningProfile(this, 'SigningProfile', {
platform: signer.Platform.AWS_LAMBDA_SHA384_ECDSA,
});
const codeSigningConfig = new lambda.CodeSigningConfig(this, 'CodeSigningConfig', {
signingProfiles: [signingProfile],
});
new lambda.Function(this, 'Function', {
codeSigningConfig,
runtime: lambda.Runtime.NODEJS_16_X,
handler: 'index.handler',
code: lambda.Code.fromAsset(path.join(__dirname, 'lambda-handler')),
});