Welcome to above the clouds
AWS – Introducing Amazon SageMaker Feature Store – a fully managed repository to store, discover, share and serve machine learning features
We’re excited to announce Amazon SageMaker Feature Store, a new capability of Amazon SageMaker to ingest, store, share, reuse, and serve features for real time and batch machine learning (ML) applications. Read More for the details.
AWS – Introducing Amazon SageMaker Pipelines, first purpose built CI/CD service for machine learning
We’re excited to announce Amazon SageMaker Pipelines, a new capability of Amazon SageMaker to build, manage, automate, and scale end to end machine learning workflows. SageMaker Pipelines brings automation and orchestration to ML workflows, enabling you to accelerate machine learning projects and scale up to thousands of models in production. Read More for the details.
AWS – AWS Security Hub integrates with AWS Audit Manager for simplified security posture management
AWS Security Hub is now integrated with AWS Audit Manager, which helps simplify how you assess risk and monitor your compliance with regulations and industry standards. AWS Audit Manager is a new service that helps you continuously audit your AWS usage and automates evidence collection to make it easier for you to assess whether your […]
AWS – Amazon AppFlow now provides Amazon Lookout for Metrics connectivity to several cloud applications
Read More for the details.
AWS – Amazon Kendra adds Google Drive connector
Amazon Kendra is a highly accurate and easy to use intelligent search service powered by machine learning. Starting today, AWS customers can automatically index and search content that is contained in Google Drive repositories using Amazon Kendra’s new built-in Google Drive connector. Read More for the details.
AWS – Amazon SageMaker Model Monitor now supports new capabilities to maintain model quality in production
Amazon SageMaker Model Monitor continuously monitors machine learning models for concept drift (i.e. changes in data distribution and characteristics over time) and alerts you if there are any deviations so you can take remedial action. Starting today, you can also use Amazon SageMaker Model Monitor to detect drift in model quality, bias, and feature importance. […]
AWS – Announcing Amazon Forecast Weather Index – automatically include local weather to increase your forecasting model accuracy
We’re excited to announce the Amazon Forecast Weather Index, which can increase your forecasting accuracy, by automatically including the latest local weather information to your demand forecasts with one click and at no extra cost. Weather conditions influence consumer demand patterns, product merchandizing decisions, staffing requirements and energy consumption needs; however, acquiring, cleaning, and effectively using […]
AWS – AWS announces AWS Audit Manager
AWS Audit Manager is a new service that helps you continuously audit your AWS usage to simplify how you assess risk and compliance with regulations and industry standards. Audit Manager automates evidence collection to make it easier to assess whether your policies, procedures, and activities, also known as controls, are operating effectively. When it is […]
AWS – Introducing Amazon SageMaker JumpStart – Easily and quickly bring machine learning applications to market
Amazon SageMaker JumpStart helps you easily and quickly bring machine learning (ML) applications to market using pre-built solutions for common use cases and open source models from popular model zoos. Read More for the details.
GCP – Admin Essentials: Ready, set, Chrome—Improvements and polices to make Chrome more performant
From its inception, Chrome’s core principles have been the four S’s: speed, security, stability, and simplicity. Those principles guide us in the way we build Chrome. The first S—speed—is what has driven us to make Chrome one of the most performant browsers out there, and we are constantly finding ways to improve. Enterprise environments often […]