Three key security themes from AWS re:Invent 2022
AWS re:Invent returned to Las Vegas, Nevada, November 28 to December 2, 2022. After a virtual event in 2020 and a hybrid 2021 edition, spirits were
AWS re:Invent returned to Las Vegas, Nevada, November 28 to December 2, 2022. After a virtual event in 2020 and a hybrid 2021 edition, spirits were
AWS re:Invent returned to Las Vegas, Nevada, November 28 to December 2, 2022. After a virtual event in 2020 and a hybrid 2021 edition, spirits were
AWS re:Invent returned to Las Vegas, NV, in November 2022. The conference featured over 2,200 sessions and hands-on labs and more than 51,000
The 11th annual Amazon Web Services re:Invent is now in the books. This was the first fully attended re:Invent since the pandemic — 2021 had a
Today we are announcing a new Amazon Comprehend feature for intelligent document processing (IDP). This feature allows you to classify and extract
Today we are announcing a new Amazon Comprehend feature for intelligent document processing (IDP). This feature allows you to classify and extract
In 2016, we launched Amazon GameLift, a dedicated hosting solution that securely deploys and automatically scales fleets of session-based multiplayer
Today, we announced the preview release of Amazon CodeCatalyst. A unified software development and delivery service, Amazon CodeCatalyst enables
It is increasingly common to use multiple cloud services as building blocks to assemble a modern event-driven application. Using purpose-built
I am excited to announce the availability of a distributed map for AWS Step Functions. This flow extends support for orchestrating large-scale
One of the major focus areas for Amazon Web Services Inc.‘s 11th annual re:Invent conference this week is machine learning and artificial
Update 8 February 2023: I edited this blog post to remove the “preview” messaging for AWS Artifact third-party reports. —- AWS Marketplace
AWS Marketplace Vendor Insights is a new capability of AWS Marketplace. It simplifies third-party software risk assessments when procuring solutions
As you move your machine learning (ML) workloads into production, you need to continuously monitor your deployed models and iterate when you observe
In 2019, we introduced Amazon SageMaker Studio, the first fully integrated development environment (IDE) for data science and machine learning (ML).