Amazon SageMaker Studio provides a unified, web-based visual interface where you can perform all machine learning (ML) development steps, making data science teams up to 10 times more productive. Studio gives you complete access, control, and visibility into each step required to build, train, and deploy models. Studio notebooks are collaborative notebooks that you can launch quickly because you don’t need to set up compute instances and file storage beforehand. Amazon SageMaker is a fully managed service that offers capabilities that abstract the heavy lifting of infrastructure management and provides the agility and scalability you desire for large-scale ML activities with different features and a pay-as-you-use pricing model.
In this post, we demonstrate how to do the following:

Detect and stop idle resources that are incurring costs within Studio using an auto-shutdown Jupyter extension that can be both manually and automatically installed
Enable event notifications to track

Continue reading



At FusionWeb, we aim to look at the future through the lenses of imagination, creativity, expertise and simplicity in the most cost effective ways. All we want to make something that brings smile to our clients face. Let’s try us to believe us.