Amazon EventBridge schema registry stores event structure - or schema - in a shared central location and maps those schemas to code for Java, Python, and Typescript so it’s easy to use events as objects in your code. https://aws.amazon.com/about-aws/whats-new/2019/12/introducing-amazon-eventbridge-schema-registry-now-in-preview/?trk=ls_card
AWS launches new program to drive migrations for end of support Windows Server applications https://aws.amazon.com/about-aws/whats-new/2019/12/aws-launches-program-drive-migration-windows-server/?trk=ls_card
Amazon Managed Apache Cassandra Service - Eat Databricks lunch https://aws.amazon.com/blogs/aws/new-amazon-managed-apache-cassandra-service-mcs/
ML works across Tensorflow, PyTorch and mxnet - Sagemaker Studio single pane of glass IDE for machine learning, Sagemaker Notebooks - pairs notebooks with compute, Sagemaker Experiments - Tune, compare, visualize, collect & share models and experiments automatically Sagemaker Debugger - Improve accuracy of models, feature prioritization, metrics for model training, SageMaker Model Monitor - detect concept drift SageMaker AutoML with no loss of visibility or control- CSV(data) -> trains 50 different machine learning models - with a model leaderboard - notebook with all the models & recipes
Amazon CodeGuru : Auto code reviews + performance profiling - driven by machine learning - input handling, aws best practices, latency & cpu utilization, visualize performance - will find the MOST EXPENSIVE line of code in terms of performance. Installed as an agent on the container . :plus: web hook for pull requests
AWS launches new program to drive migrations for end of support Windows Server applications https://aws.amazon.com/about-aws/whats-new/2019/12/aws-launches-program-drive-migration-windows-server/?trk=ls_card
Amazon Managed Apache Cassandra Service - Eat Databricks lunch https://aws.amazon.com/blogs/aws/new-amazon-managed-apache-cassandra-service-mcs/
ML works across Tensorflow, PyTorch and mxnet - Sagemaker Studio single pane of glass IDE for machine learning, Sagemaker Notebooks - pairs notebooks with compute, Sagemaker Experiments - Tune, compare, visualize, collect & share models and experiments automatically Sagemaker Debugger - Improve accuracy of models, feature prioritization, metrics for model training, SageMaker Model Monitor - detect concept drift SageMaker AutoML with no loss of visibility or control- CSV(data) -> trains 50 different machine learning models - with a model leaderboard - notebook with all the models & recipes
Amazon CodeGuru : Auto code reviews + performance profiling - driven by machine learning - input handling, aws best practices, latency & cpu utilization, visualize performance - will find the MOST EXPENSIVE line of code in terms of performance. Installed as an agent on the container . :plus: web hook for pull requests
