How does LakeChain relates to Generative AI CDK Constructs?

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I would like to get some ideas what is the relation between AWS Generative AI CDK Constructs https://awslabs.github.io/generative-ai-cdk-constructs/ and Project Lakechain https://awslabs.github.io/project-lakechain/ ? Concurrency, complementers, different use cases or other?

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Amazon CDK abstracts writing AWS CloudFormation and turns it into a codified effort. By using code to define products it becomes more efficient, less time consuming, and allows you to build even higher order constructs. In CDK you'll see three tiers of constructs. T1 refers to the native CloudFormation implementation of a resource deployment (e.g. writing the full YAML/JSON CloudFormation for an EC2). T2 refers to resources that have been abstracted and can be called through the cdk language (e.g. cdk-lib/ec2). T3 refers to linked resources to accomplish a common pattern (e.g. S3 to Lambda to RDS) which connects multiple T2 constructs together.

In the case of the GenAI Amazon CDK, it would allow you to instantiate infrastructure necessary to call models and other activities as defined by your use case. This allows you to define your infrastructure and deploy it via code.

Project Lakechain has built their solution to leverage cdk in order to deploy the underlying infrastructure necessary for users to perform the actions within the solution. You can view the code (https://github.com/awslabs/project-lakechain) and see where and how they're using the different CDK constructs including any GenAI implementations.

AWS
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