aws-cdk

问题 I am using the new higher level GraphqlAPI class instead of the lower level constructs to create my Appsync api and connect it to a table. this.api = new GraphqlApi(...); The new GraphqlApi instance allows you to simply add datasources: this.api.addDynamoDbDataSource('name', tableRef); If you look at the example code at https://docs.aws.amazon.com/cdk/api/latest/docs/aws-appsync-readme.html, I notice that they do not create a role to grant permission for Appsync to access the table: const

问题 I am using the new higher level GraphqlAPI class instead of the lower level constructs to create my Appsync api and connect it to a table. this.api = new GraphqlApi(...); The new GraphqlApi instance allows you to simply add datasources: this.api.addDynamoDbDataSource('name', tableRef); If you look at the example code at https://docs.aws.amazon.com/cdk/api/latest/docs/aws-appsync-readme.html, I notice that they do not create a role to grant permission for Appsync to access the table: const

问题 I am using the new higher level GraphqlAPI class instead of the lower level constructs to create my Appsync api and connect it to a table. this.api = new GraphqlApi(...); The new GraphqlApi instance allows you to simply add datasources: this.api.addDynamoDbDataSource('name', tableRef); If you look at the example code at https://docs.aws.amazon.com/cdk/api/latest/docs/aws-appsync-readme.html, I notice that they do not create a role to grant permission for Appsync to access the table: const

问题 Recently I have been using aws-cdk to create EC2, VPC and S3 services. But if I want to create my custom EC2 Library in python(not using JSII) than will be using aws_cdk's aws_ec2 library to actually create the EC2 Instance and a VPC. The custom library will accept arguments like Instance Name(String) , InstanceType(String) , MachineImage(String) , Subnet Type (String) Than this arguments will be refer like below: Disclaimer: Code below Might not be correct dummy_ec2 = ec2.Instance(self,

问题 I'm running an Aurora PostgreSQL (Serverless) cluster. After I deploy the infrastructure for the first time, and every time I re-deploy, I want to run database schema migrations (add tables, add columns). How can I accomplish this? Lambda is out of the question, as migrations may run for a long time. Edit : clarified about schema migration Thanks! 回答1: The correct way to migrate it would be through using the AWS Database Migration Service. You could create the resources in the CDK for this,

问题 I'm running an Aurora PostgreSQL (Serverless) cluster. After I deploy the infrastructure for the first time, and every time I re-deploy, I want to run database schema migrations (add tables, add columns). How can I accomplish this? Lambda is out of the question, as migrations may run for a long time. Edit : clarified about schema migration Thanks! 回答1: The correct way to migrate it would be through using the AWS Database Migration Service. You could create the resources in the CDK for this,

问题 I'm migrating my cloud solution to cdk. I can see how to add a stream to a new DynamoDB in the constructor through the TableProps: const newTable = new dynamodb.Table(this, 'new Table', { tableName: 'streaming', partitionKey: { name : 'id', type: dynamodb.AttributeType.NUMBER }, stream: StreamViewType.NEW_AND_OLD_IMAGES, }) but there is no apparent way to enable a stream on an existing DynamoDB. I can't seem to access the TableProps on an existing item. const sandpitTable = dynamodb.Table

问题 CDK Pipelines is great, specially for cross-account deployments. It enables the developers to define and customize the CI/CD pipeline for their app to their heart's content. But to remain SoC compliant, we need to make sure that necessary controls like below are validated/enforced A manual approval stage should be present before the stage that does the cross-account deployment to production Direct deployment to production bypassing dev/staging environment is not allowed Test cases (Unit tests

问题 I have an AWS CDK script that I'm now unable to deploy. I could deploy it before adding a bucket policy. After adding a bucket policy, it fails to deploy. Here's the Python code: bucket = aws_s3.Bucket( self, "myBucket", bucket_name="mybucket", access_control=aws_s3.BucketAccessControl.PRIVATE, versioned=True, encryption=aws_s3.BucketEncryption.S3_MANAGED, block_public_access=aws_s3.BlockPublicAccess.BLOCK_ALL ) policy_statement = aws_iam.PolicyStatement( effect=aws_iam.Effect.DENY, actions=[

问题 AWS Step Functions may be run in a local Docker environment using Step Functions Local Docker. However, the step functions need to be defined using the JSON-based Amazon States Language. This is not at all convenient if your AWS infrastructure (Step Functions plus lambdas) is defined using AWS CDK/CloudFormation. Is there a way to create the Amazon States Language definition of a state machine from the CDK or CloudFormation output, such that it’s possible to run the step functions locally? My