How Rocket Companies modernized their data science solution on AWS
In this post, we share how we modernized Rocket Companies’ data science solution on AWS to increase the speed to delivery from eight weeks to under one hour, improve operational…
Amazon SageMaker AI
Governing the ML lifecycle at scale, Part 4: Scaling MLOps with security and governance controls
This post provides detailed steps for setting up the key components of a multi-account ML platform. This includes configuring the ML Shared Services Account, which manages the central templates, model…
Streamline custom environment provisioning for Amazon SageMaker Studio: An automated CI/CD pipeline approach
In this post, we show how to create an automated continuous integration and delivery (CI/CD) pipeline solution to build, scan, and deploy custom Docker images to SageMaker Studio domains. You…