The purpose of this code repository is to house the resources used in the workshop called "GenerativeAI-Powered anomaly detection: Spotting anomalies in real-time". The repository contains the following sections:
This is located on the root of the project (app.py) is the entrypoint, coupled with the requirements.txt for dependencies and cdk/ folder for the shared code resources and other complementary CDK files.
Type pip install -r requirements.txt to start working with the project, then cdk synth or cdk deploy to deploy the required resources to your own account using the CDK.
Located in flink-app/, can be executed by loading into an IDE and executing the program, or by running mvn compile to build an application jar.
The lambda code can be found under code/ tab under lambdas for any component of the workshop that leverages lambda functions.
The remaining components of the workshop can be found via the workshop itself found here.
In this sample notebook, you will train, build, and deploy a model using the IP Insights algorithm and Amazon VPC flowlog data. You will query an Athena table and create a dataset for model training. You will perform data transformation on the results from the VPC flowlog data. Train an IP Insights model with this data. Deploy your model to a SageMaker endpoint and ultimately test your model.