aws-cdk.integ-tests-alpha 2.141.0a0

CDK Integration Testing Constructs

integ-tests

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The APIs of higher level constructs in this module are experimental and under active development. They are subject to non-backward compatible changes or removal in any future version. These are not subject to the Semantic Versioning model and breaking changes will be announced in the release notes. This means that while you may use them, you may need to update your source code when upgrading to a newer version of this package.

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Overview

This library is meant to be used in combination with the integ-runner CLI to enable users to write and execute integration tests for AWS CDK Constructs.

An integration test should be defined as a CDK application, and there should be a 1:1 relationship between an integration test and a CDK application.

So for example, in order to create an integration test called my-function we would need to create a file to contain our integration test application.

test/integ.my-function.ts

app = App()
stack = Stack()
lambda_.Function(stack, "MyFunction",
    runtime=lambda_.Runtime.NODEJS_LATEST,
    handler="index.handler",
    code=lambda_.Code.from_asset(path.join(__dirname, "lambda-handler"))
)

This is a self contained CDK application which we could deploy by running

cdk deploy --app 'node test/integ.my-function.js'

In order to turn this into an integration test, all that is needed is to use the IntegTest construct.

# app: App
# stack: Stack

IntegTest(app, "Integ", test_cases=[stack])

You will notice that the stack is registered to the IntegTest as a test case. Each integration test can contain multiple test cases, which are just instances of a stack. See the Usage section for more details.

Usage

IntegTest

Suppose you have a simple stack, that only encapsulates a Lambda function with a certain handler:

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

        lambda_.Function(self, "Handler",
            runtime=lambda_.Runtime.NODEJS_LATEST,
            handler="index.handler",
            code=lambda_.Code.from_asset(path.join(__dirname, "lambda-handler")),
            architecture=architecture
        )

You may want to test this stack under different conditions. For example, we want this stack to be deployed correctly, regardless of the architecture we choose for the Lambda function. In particular, it should work for both ARM_64 and X86_64. So you can create an IntegTestCase that exercises both scenarios:

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

        lambda_.Function(self, "Handler",
            runtime=lambda_.Runtime.NODEJS_LATEST,
            handler="index.handler",
            code=lambda_.Code.from_asset(path.join(__dirname, "lambda-handler")),
            architecture=architecture
        )

# Beginning of the test suite
app = App()

IntegTest(app, "DifferentArchitectures",
    test_cases=[
        StackUnderTest(app, "Stack1",
            architecture=lambda_.Architecture.ARM_64
        ),
        StackUnderTest(app, "Stack2",
            architecture=lambda_.Architecture.X86_64
        )
    ]
)

This is all the instruction you need for the integration test runner to know which stacks to synthesize, deploy and destroy. But you may also need to customize the behavior of the runner by changing its parameters. For example:

app = App()

stack_under_test = Stack(app, "StackUnderTest")

stack = Stack(app, "stack")

test_case = IntegTest(app, "CustomizedDeploymentWorkflow",
    test_cases=[stack_under_test],
    diff_assets=True,
    stack_update_workflow=True,
    cdk_command_options=CdkCommands(
        deploy=DeployCommand(
            args=DeployOptions(
                require_approval=RequireApproval.NEVER,
                json=True
            )
        ),
        destroy=DestroyCommand(
            args=DestroyOptions(
                force=True
            )
        )
    )
)

IntegTestCaseStack

In the majority of cases an integration test will contain a single IntegTestCase. By default when you create an IntegTest an IntegTestCase is created for you and all of your test cases are registered to this IntegTestCase. The IntegTestCase and IntegTestCaseStack constructs are only needed when it is necessary to defined different options for individual test cases.

For example, you might want to have one test case where diffAssets is enabled.

# app: App
# stack_under_test: Stack

test_case_with_assets = IntegTestCaseStack(app, "TestCaseAssets",
    diff_assets=True
)

IntegTest(app, "Integ", test_cases=[stack_under_test, test_case_with_assets])

Assertions

This library also provides a utility to make assertions against the infrastructure that the integration test deploys.

There are two main scenarios in which assertions are created.

• Part of an integration test using integ-runner

In this case you would create an integration test using the IntegTest construct and then make assertions using the assert property. You should not utilize the assertion constructs directly, but should instead use the methods on IntegTest.assertions.

# app: App
# stack: Stack


integ = IntegTest(app, "Integ", test_cases=[stack])
integ.assertions.aws_api_call("S3", "getObject")

By default an assertions stack is automatically generated for you. You may however provide your own stack to use.

# app: App
# stack: Stack
# assertion_stack: Stack


integ = IntegTest(app, "Integ", test_cases=[stack], assertion_stack=assertion_stack)
integ.assertions.aws_api_call("S3", "getObject")

• Part of a normal CDK deployment

In this case you may be using assertions as part of a normal CDK deployment in order to make an assertion on the infrastructure before the deployment is considered successful. In this case you can utilize the assertions constructs directly.

# my_app_stack: Stack


AwsApiCall(my_app_stack, "GetObject",
    service="S3",
    api="getObject"
)

DeployAssert

Assertions are created by using the DeployAssert construct. This construct creates it's own Stack separate from any stacks that you create as part of your integration tests. This Stack is treated differently from other stacks by the integ-runner tool. For example, this stack will not be diffed by the integ-runner.

DeployAssert also provides utilities to register your own assertions.

# my_custom_resource: CustomResource
# stack: Stack
# app: App


integ = IntegTest(app, "Integ", test_cases=[stack])
integ.assertions.expect("CustomAssertion",
    ExpectedResult.object_like({"foo": "bar"}),
    ActualResult.from_custom_resource(my_custom_resource, "data"))

In the above example an assertion is created that will trigger a user defined CustomResource and assert that the data attribute is equal to { foo: 'bar' }.

API Calls

A common method to retrieve the "actual" results to compare with what is expected is to make an API call to receive some data. This library does this by utilizing CloudFormation custom resources which means that CloudFormation will call out to a Lambda Function which will make the API call.

HttpApiCall

Using the HttpApiCall will use the node-fetch JavaScript library to make the HTTP call.

This can be done by using the class directory (in the case of a normal deployment):

# stack: Stack


HttpApiCall(stack, "MyAsssertion",
    url="https://example-api.com/abc"
)

Or by using the httpApiCall method on DeployAssert (when writing integration tests):

# app: App
# stack: Stack

integ = IntegTest(app, "Integ",
    test_cases=[stack]
)
integ.assertions.http_api_call("https://example-api.com/abc")

AwsApiCall

Using the AwsApiCall construct will use the AWS JavaScript SDK to make the API call.

This can be done by using the class directory (in the case of a normal deployment):

# stack: Stack


AwsApiCall(stack, "MyAssertion",
    service="SQS",
    api="receiveMessage",
    parameters={
        "QueueUrl": "url"
    }
)

Or by using the awsApiCall method on DeployAssert (when writing integration tests):

# app: App
# stack: Stack

integ = IntegTest(app, "Integ",
    test_cases=[stack]
)
integ.assertions.aws_api_call("SQS", "receiveMessage", {
    "QueueUrl": "url"
})

You must specify the service and the api when using The AwsApiCall construct. The service is the name of an AWS service, in one of the following forms:

• An AWS SDK for JavaScript v3 package name (@aws-sdk/client-api-gateway)
• An AWS SDK for JavaScript v3 client name (api-gateway)
• An AWS SDK for JavaScript v2 constructor name (APIGateway)
• A lowercase AWS SDK for JavaScript v2 constructor name (apigateway)

The api is the name of an AWS API call, in one of the following forms:

• An API call name as found in the API Reference documentation (GetObject)
• The API call name starting with a lowercase letter (getObject)
• The AWS SDK for JavaScript v3 command class name (GetObjectCommand)

By default, the AwsApiCall construct will automatically add the correct IAM policies to allow the Lambda function to make the API call. It does this based on the service and api that is provided. In the above example the service is SQS and the api is receiveMessage so it will create a policy with Action: 'sqs:ReceiveMessage.

There are some cases where the permissions do not exactly match the service/api call, for example the S3 listObjectsV2 api. In these cases it is possible to add the correct policy by accessing the provider object.

# app: App
# stack: Stack
# integ: IntegTest


api_call = integ.assertions.aws_api_call("S3", "listObjectsV2", {
    "Bucket": "mybucket"
})

api_call.provider.add_to_role_policy({
    "Effect": "Allow",
    "Action": ["s3:GetObject", "s3:ListBucket"],
    "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.

EqualsAssertion

This library currently provides the ability to assert that two values are equal to one another by utilizing the EqualsAssertion class. This utilizes a Lambda backed CustomResource which in tern uses the Match utility from the @aws-cdk/assertions library.

# app: App
# stack: Stack
# queue: sqs.Queue
# fn: lambda.IFunction


integ = IntegTest(app, "Integ",
    test_cases=[stack]
)

integ.assertions.invoke_function(
    function_name=fn.function_name,
    invocation_type=InvocationType.EVENT,
    payload=JSON.stringify({"status": "OK"})
)

message = integ.assertions.aws_api_call("SQS", "receiveMessage", {
    "QueueUrl": queue.queue_url,
    "WaitTimeSeconds": 20
})

message.assert_at_path("Messages.0.Body", ExpectedResult.object_like({
    "request_context": {
        "condition": "Success"
    },
    "request_payload": {
        "status": "OK"
    },
    "response_context": {
        "status_code": 200
    },
    "response_payload": "success"
}))

Match

integ-tests also provides a Match utility similar to the @aws-cdk/assertions module. Match can be used to construct the ExpectedResult. While the utility is similar, only a subset of methods are currently available on the Match utility of this module: arrayWith, objectLike, stringLikeRegexp and serializedJson.

# message: AwsApiCall


message.expect(ExpectedResult.object_like({
    "Messages": Match.array_with([{
        "Payload": Match.serialized_json({"key": "value"})
    }, {
        "Body": {
            "Values": Match.array_with([{"Asdf": 3}]),
            "Message": Match.string_like_regexp("message")
        }
    }
    ])
}))

Examples

Invoke a Lambda Function

In this example there is a Lambda Function that is invoked and we assert that the payload that is returned is equal to '200'.

# lambda_function: lambda.IFunction
# app: App


stack = Stack(app, "cdk-integ-lambda-bundling")

integ = IntegTest(app, "IntegTest",
    test_cases=[stack]
)

invoke = integ.assertions.invoke_function(
    function_name=lambda_function.function_name
)
invoke.expect(ExpectedResult.object_like({
    "Payload": "200"
}))

The above example will by default create a CloudWatch log group that's never expired. If you want to configure it with custom log retention days, you need to specify the logRetention property.

import aws_cdk.aws_logs as logs

# lambda_function: lambda.IFunction
# app: App


stack = Stack(app, "cdk-integ-lambda-bundling")

integ = IntegTest(app, "IntegTest",
    test_cases=[stack]
)

invoke = integ.assertions.invoke_function(
    function_name=lambda_function.function_name,
    log_retention=logs.RetentionDays.ONE_WEEK
)

Make an AWS API Call

In this example there is a StepFunctions state machine that is executed and then we assert that the result of the execution is successful.

# app: App
# stack: Stack
# sm: IStateMachine


test_case = IntegTest(app, "IntegTest",
    test_cases=[stack]
)

# Start an execution
start = test_case.assertions.aws_api_call("StepFunctions", "startExecution", {
    "state_machine_arn": sm.state_machine_arn
})

# describe the results of the execution
describe = test_case.assertions.aws_api_call("StepFunctions", "describeExecution", {
    "execution_arn": start.get_att_string("executionArn")
})

# assert the results
describe.expect(ExpectedResult.object_like({
    "status": "SUCCEEDED"
}))

Chain ApiCalls

Sometimes it may be necessary to chain API Calls. Since each API call is its own resource, all you need to do is add a dependency between the calls. There is an helper method next that can be used.

# integ: IntegTest


integ.assertions.aws_api_call("S3", "putObject", {
    "Bucket": "my-bucket",
    "Key": "my-key",
    "Body": "helloWorld"
}).next(integ.assertions.aws_api_call("S3", "getObject", {
    "Bucket": "my-bucket",
    "Key": "my-key"
}))

Wait for results

A common use case when performing assertions is to wait for a condition to pass. Sometimes the thing that you are asserting against is not done provisioning by the time the assertion runs. In these cases it is possible to run the assertion asynchronously by calling the waitForAssertions() method.

Taking the example above of executing a StepFunctions state machine, depending on the complexity of the state machine, it might take a while for it to complete.

# app: App
# stack: Stack
# sm: IStateMachine


test_case = IntegTest(app, "IntegTest",
    test_cases=[stack]
)

# Start an execution
start = test_case.assertions.aws_api_call("StepFunctions", "startExecution", {
    "state_machine_arn": sm.state_machine_arn
})

# describe the results of the execution
describe = test_case.assertions.aws_api_call("StepFunctions", "describeExecution", {
    "execution_arn": start.get_att_string("executionArn")
}).expect(ExpectedResult.object_like({
    "status": "SUCCEEDED"
})).wait_for_assertions()

When you call waitForAssertions() the assertion provider will continuously make the awsApiCall until the ExpectedResult is met. You can also control the parameters for waiting, for example:

# test_case: IntegTest
# start: IApiCall


describe = test_case.assertions.aws_api_call("StepFunctions", "describeExecution", {
    "execution_arn": start.get_att_string("executionArn")
}).expect(ExpectedResult.object_like({
    "status": "SUCCEEDED"
})).wait_for_assertions(
    total_timeout=Duration.minutes(5),
    interval=Duration.seconds(15),
    backoff_rate=3
)