Learn how to schedule automatic execution of AWS SageMaker notebooks using CloudWatch, Lambda and Lifecycle configurations
SageMaker provides multiple tools and functionalities to label, build, train and deploy machine learning models at a scale. One of the most popular ones is Notebooks Instances which are used to prepare and process data, write code to train models, deploy models to Amazon SageMaker hosting, and test or validate the models. I was recently working on a project which involved automating a SageMaker notebook.
There are multiple ways to deploy models in Sagemaker using Amazon Glue as described here and here. You can also deploy models using End Point API. What if you are not deploying the models, rather executing the script again and again? SageMaker does not have a direct way to automate this right now. Also, what if you want to shut down the notebook instance as soon as you are done executing the script? This will surely save you money given AWS charges on an-hourly basis for Notebook Instances.