aws-cdk.aws-appsync-alpha 2.59.0a0

The CDK Construct Library for AWS::AppSync

AWS AppSync Construct Library

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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 This means that while you may use them, you may need to update your source code when upgrading to a newer version of this package.

---

The @aws-cdk/aws-appsync package contains constructs for building flexible APIs that use GraphQL.

import aws_cdk.aws_appsync_alpha as appsync

Example

DynamoDB

Example of a GraphQL API with AWS_IAM authorization resolving into a DynamoDb backend data source.

GraphQL schema file schema.graphql:

type demo {
  id: String!
  version: String!
}
type Query {
  getDemos: [ demo! ]
}
input DemoInput {
  version: String!
}
type Mutation {
  addDemo(input: DemoInput!): demo
}

CDK stack file app-stack.ts:

api = appsync.GraphqlApi(self, "Api",
    name="demo",
    schema=appsync.SchemaFile.from_asset(path.join(__dirname, "schema.graphql")),
    authorization_config=appsync.AuthorizationConfig(
        default_authorization=appsync.AuthorizationMode(
            authorization_type=appsync.AuthorizationType.IAM
        )
    ),
    xray_enabled=True
)

demo_table = dynamodb.Table(self, "DemoTable",
    partition_key=dynamodb.Attribute(
        name="id",
        type=dynamodb.AttributeType.STRING
    )
)

demo_dS = api.add_dynamo_db_data_source("demoDataSource", demo_table)

# Resolver for the Query "getDemos" that scans the DynamoDb table and returns the entire list.
# Resolver Mapping Template Reference:
# https://docs.aws.amazon.com/appsync/latest/devguide/resolver-mapping-template-reference-dynamodb.html
demo_dS.create_resolver("QueryGetDemosResolver",
    type_name="Query",
    field_name="getDemos",
    request_mapping_template=appsync.MappingTemplate.dynamo_db_scan_table(),
    response_mapping_template=appsync.MappingTemplate.dynamo_db_result_list()
)

# Resolver for the Mutation "addDemo" that puts the item into the DynamoDb table.
demo_dS.create_resolver("MutationAddDemoResolver",
    type_name="Mutation",
    field_name="addDemo",
    request_mapping_template=appsync.MappingTemplate.dynamo_db_put_item(
        appsync.PrimaryKey.partition("id").auto(),
        appsync.Values.projecting("input")),
    response_mapping_template=appsync.MappingTemplate.dynamo_db_result_item()
)

# To enable DynamoDB read consistency with the `MappingTemplate`:
demo_dS.create_resolver("QueryGetDemosConsistentResolver",
    type_name="Query",
    field_name="getDemosConsistent",
    request_mapping_template=appsync.MappingTemplate.dynamo_db_scan_table(True),
    response_mapping_template=appsync.MappingTemplate.dynamo_db_result_list()
)

Aurora Serverless

AppSync provides a data source for executing SQL commands against Amazon Aurora Serverless clusters. You can use AppSync resolvers to execute SQL statements against the Data API with GraphQL queries, mutations, and subscriptions.

# Build a data source for AppSync to access the database.
# api: appsync.GraphqlApi
# Create username and password secret for DB Cluster
secret = rds.DatabaseSecret(self, "AuroraSecret",
    username="clusteradmin"
)

# The VPC to place the cluster in
vpc = ec2.Vpc(self, "AuroraVpc")

# Create the serverless cluster, provide all values needed to customise the database.
cluster = rds.ServerlessCluster(self, "AuroraCluster",
    engine=rds.DatabaseClusterEngine.AURORA_MYSQL,
    vpc=vpc,
    credentials={"username": "clusteradmin"},
    cluster_identifier="db-endpoint-test",
    default_database_name="demos"
)
rds_dS = api.add_rds_data_source("rds", cluster, secret, "demos")

# Set up a resolver for an RDS query.
rds_dS.create_resolver("QueryGetDemosRdsResolver",
    type_name="Query",
    field_name="getDemosRds",
    request_mapping_template=appsync.MappingTemplate.from_string("""
          {
            "version": "2018-05-29",
            "statements": [
              "SELECT * FROM demos"
            ]
          }
          """),
    response_mapping_template=appsync.MappingTemplate.from_string("""
            $utils.toJson($utils.rds.toJsonObject($ctx.result)[0])
          """)
)

# Set up a resolver for an RDS mutation.
rds_dS.create_resolver("MutationAddDemoRdsResolver",
    type_name="Mutation",
    field_name="addDemoRds",
    request_mapping_template=appsync.MappingTemplate.from_string("""
          {
            "version": "2018-05-29",
            "statements": [
              "INSERT INTO demos VALUES (:id, :version)",
              "SELECT * WHERE id = :id"
            ],
            "variableMap": {
              ":id": $util.toJson($util.autoId()),
              ":version": $util.toJson($ctx.args.version)
            }
          }
          """),
    response_mapping_template=appsync.MappingTemplate.from_string("""
            $utils.toJson($utils.rds.toJsonObject($ctx.result)[1][0])
          """)
)

HTTP Endpoints

GraphQL schema file schema.graphql:

type job {
  id: String!
  version: String!
}

input DemoInput {
  version: String!
}

type Mutation {
  callStepFunction(input: DemoInput!): job
}

GraphQL request mapping template request.vtl:

{
  "version": "2018-05-29",
  "method": "POST",
  "resourcePath": "/",
  "params": {
    "headers": {
      "content-type": "application/x-amz-json-1.0",
      "x-amz-target":"AWSStepFunctions.StartExecution"
    },
    "body": {
      "stateMachineArn": "<your step functions arn>",
      "input": "{ \"id\": \"$context.arguments.id\" }"
    }
  }
}

GraphQL response mapping template response.vtl:

{
  "id": "${context.result.id}"
}

CDK stack file app-stack.ts:

api = appsync.GraphqlApi(self, "api",
    name="api",
    schema=appsync.SchemaFile.from_asset(path.join(__dirname, "schema.graphql"))
)

http_ds = api.add_http_data_source("ds", "https://states.amazonaws.com",
    name="httpDsWithStepF",
    description="from appsync to StepFunctions Workflow",
    authorization_config=appsync.AwsIamConfig(
        signing_region="us-east-1",
        signing_service_name="states"
    )
)

http_ds.create_resolver("MutationCallStepFunctionResolver",
    type_name="Mutation",
    field_name="callStepFunction",
    request_mapping_template=appsync.MappingTemplate.from_file("request.vtl"),
    response_mapping_template=appsync.MappingTemplate.from_file("response.vtl")
)

Amazon OpenSearch Service

AppSync has builtin support for Amazon OpenSearch Service (successor to Amazon Elasticsearch Service) from domains that are provisioned through your AWS account. You can use AppSync resolvers to perform GraphQL operations such as queries, mutations, and subscriptions.

import aws_cdk.aws_opensearchservice as opensearch

# api: appsync.GraphqlApi


user = iam.User(self, "User")
domain = opensearch.Domain(self, "Domain",
    version=opensearch.EngineVersion.OPENSEARCH_1_3,
    removal_policy=RemovalPolicy.DESTROY,
    fine_grained_access_control=opensearch.AdvancedSecurityOptions(master_user_arn=user.user_arn),
    encryption_at_rest=opensearch.EncryptionAtRestOptions(enabled=True),
    node_to_node_encryption=True,
    enforce_https=True
)
ds = api.add_open_search_data_source("ds", domain)

ds.create_resolver("QueryGetTestsResolver",
    type_name="Query",
    field_name="getTests",
    request_mapping_template=appsync.MappingTemplate.from_string(JSON.stringify({
        "version": "2017-02-28",
        "operation": "GET",
        "path": "/id/post/_search",
        "params": {
            "headers": {},
            "query_string": {},
            "body": {"from": 0, "size": 50}
        }
    })),
    response_mapping_template=appsync.MappingTemplate.from_string("""[
            #foreach($entry in $context.result.hits.hits)
            #if( $velocityCount > 1 ) , #end
            $utils.toJson($entry.get("_source"))
            #end
          ]""")
)

Custom Domain Names

For many use cases you may want to associate a custom domain name with your GraphQL API. This can be done during the API creation.

import aws_cdk.aws_certificatemanager as acm
import aws_cdk.aws_route53 as route53

# hosted zone and route53 features
# hosted_zone_id: str
zone_name = "example.com"


my_domain_name = "api.example.com"
certificate = acm.Certificate(self, "cert", domain_name=my_domain_name)
schema = appsync.SchemaFile(file_path="mySchemaFile")
api = appsync.GraphqlApi(self, "api",
    name="myApi",
    schema=schema,
    domain_name=appsync.DomainOptions(
        certificate=certificate,
        domain_name=my_domain_name
    )
)

# hosted zone for adding appsync domain
zone = route53.HostedZone.from_hosted_zone_attributes(self, "HostedZone",
    hosted_zone_id=hosted_zone_id,
    zone_name=zone_name
)

# create a cname to the appsync domain. will map to something like xxxx.cloudfront.net
route53.CnameRecord(self, "CnameApiRecord",
    record_name="api",
    zone=zone,
    domain_name=api.app_sync_domain_name
)

Log Group

AppSync automatically create a log group with the name /aws/appsync/apis/<graphql_api_id> upon deployment with log data set to never expire. If you want to set a different expiration period, use the logConfig.retention property.

To obtain the GraphQL API's log group as a logs.ILogGroup use the logGroup property of the GraphqlApi construct.

import aws_cdk.aws_logs as logs


log_config = appsync.LogConfig(
    retention=logs.RetentionDays.ONE_WEEK
)

appsync.GraphqlApi(self, "api",
    authorization_config=appsync.AuthorizationConfig(),
    name="myApi",
    schema=appsync.SchemaFile.from_asset(path.join(__dirname, "myApi.graphql")),
    log_config=log_config
)

Schema

You can define a schema using from a local file using SchemaFile.fromAsset

api = appsync.GraphqlApi(self, "api",
    name="myApi",
    schema=appsync.SchemaFile.from_asset(path.join(__dirname, "schema.graphl"))
)

ISchema

Alternative schema sources can be defined by implementing the ISchema interface. An example of this is the CodeFirstSchema class provided in awscdk-appsync-utils

Imports

Any GraphQL Api that has been created outside the stack can be imported from another stack into your CDK app. Utilizing the fromXxx function, you have the ability to add data sources and resolvers through a IGraphqlApi interface.

# api: appsync.GraphqlApi
# table: dynamodb.Table

imported_api = appsync.GraphqlApi.from_graphql_api_attributes(self, "IApi",
    graphql_api_id=api.api_id,
    graphql_api_arn=api.arn
)
imported_api.add_dynamo_db_data_source("TableDataSource", table)

If you don't specify graphqlArn in fromXxxAttributes, CDK will autogenerate the expected arn for the imported api, given the apiId. For creating data sources and resolvers, an apiId is sufficient.

Authorization

There are multiple authorization types available for GraphQL API to cater to different access use cases. They are:

• API Keys (AuthorizationType.API_KEY)
• Amazon Cognito User Pools (AuthorizationType.USER_POOL)
• OpenID Connect (AuthorizationType.OPENID_CONNECT)
• AWS Identity and Access Management (AuthorizationType.AWS_IAM)
• AWS Lambda (AuthorizationType.AWS_LAMBDA)

These types can be used simultaneously in a single API, allowing different types of clients to access data. When you specify an authorization type, you can also specify the corresponding authorization mode to finish defining your authorization. For example, this is a GraphQL API with AWS Lambda Authorization.

import aws_cdk.aws_lambda as lambda_
# auth_function: lambda.Function


appsync.GraphqlApi(self, "api",
    name="api",
    schema=appsync.SchemaFile.from_asset(path.join(__dirname, "appsync.test.graphql")),
    authorization_config=appsync.AuthorizationConfig(
        default_authorization=appsync.AuthorizationMode(
            authorization_type=appsync.AuthorizationType.LAMBDA,
            lambda_authorizer_config=appsync.LambdaAuthorizerConfig(
                handler=auth_function
            )
        )
    )
)

Permissions

When using AWS_IAM as the authorization type for GraphQL API, an IAM Role with correct permissions must be used for access to API.

When configuring permissions, you can specify specific resources to only be accessible by IAM authorization. For example, if you want to only allow mutability for IAM authorized access you would configure the following.

In schema.graphql:

type Mutation {
  updateExample(...): ...
    @aws_iam
}

In IAM:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "appsync:GraphQL"
      ],
      "Resource": [
        "arn:aws:appsync:REGION:ACCOUNT_ID:apis/GRAPHQL_ID/types/Mutation/fields/updateExample"
      ]
    }
  ]
}

See documentation for more details.

To make this easier, CDK provides grant API.

Use the grant function for more granular authorization.

# api: appsync.GraphqlApi
role = iam.Role(self, "Role",
    assumed_by=iam.ServicePrincipal("lambda.amazonaws.com")
)

api.grant(role, appsync.IamResource.custom("types/Mutation/fields/updateExample"), "appsync:GraphQL")

IamResource

In order to use the grant functions, you need to use the class IamResource.

• IamResource.custom(...arns) permits custom ARNs and requires an argument.
• IamResouce.ofType(type, ...fields) permits ARNs for types and their fields.
• IamResource.all() permits ALL resources.

Generic Permissions

Alternatively, you can use more generic grant functions to accomplish the same usage.

These include:

• grantMutation (use to grant access to Mutation fields)
• grantQuery (use to grant access to Query fields)
• grantSubscription (use to grant access to Subscription fields)

# api: appsync.GraphqlApi
# role: iam.Role


# For generic types
api.grant_mutation(role, "updateExample")

# For custom types and granular design
api.grant(role, appsync.IamResource.of_type("Mutation", "updateExample"), "appsync:GraphQL")

Pipeline Resolvers and AppSync Functions

AppSync Functions are local functions that perform certain operations onto a backend data source. Developers can compose operations (Functions) and execute them in sequence with Pipeline Resolvers.

# api: appsync.GraphqlApi


appsync_function = appsync.AppsyncFunction(self, "function",
    name="appsync_function",
    api=api,
    data_source=api.add_none_data_source("none"),
    request_mapping_template=appsync.MappingTemplate.from_file("request.vtl"),
    response_mapping_template=appsync.MappingTemplate.from_file("response.vtl")
)

AppSync Functions are used in tandem with pipeline resolvers to compose multiple operations.

# api: appsync.GraphqlApi
# appsync_function: appsync.AppsyncFunction


pipeline_resolver = appsync.Resolver(self, "pipeline",
    api=api,
    data_source=api.add_none_data_source("none"),
    type_name="typeName",
    field_name="fieldName",
    request_mapping_template=appsync.MappingTemplate.from_file("beforeRequest.vtl"),
    pipeline_config=[appsync_function],
    response_mapping_template=appsync.MappingTemplate.from_file("afterResponse.vtl")
)

Learn more about Pipeline Resolvers and AppSync Functions here.