Use AWS Fault Injection Service to demonstrate multi-region and multi-AZ application resilience

AWS Fault Injection Service (FIS) helps you to put chaos engineering into practice at scale. Today we are launching new scenarios that will let you demonstrate that your applications perform as intended if an AWS Availability Zone experiences a full power interruption or connectivity from one AWS region to another is lost. You can use Read more about Use AWS Fault Injection Service to demonstrate multi-region and multi-AZ application resilience[…]

Zonal autoshift – Automatically shift your traffic away from Availability Zones when we detect potential issues

Today we’re launching zonal autoshift, a new capability of Amazon Route 53 Application Recovery Controller that you can enable to automatically and safely shift your workload’s traffic away from an Availability Zone when AWS identifies a potential failure affecting that Availability Zone and shift it back once the failure is resolved. When deploying resilient applications, Read more about Zonal autoshift – Automatically shift your traffic away from Availability Zones when we detect potential issues[…]

IDE extension for AWS Application Composer enhances visual modern applications development with AI-generated IaC

Today, I’m happy to share the integrated development environment (IDE) extension for AWS Application Composer. Now you can use AWS Application Composer directly in your IDE to visually build modern applications and iteratively develop your infrastructure as code templates with Amazon CodeWhisperer. Announced as preview at AWS re:Invent 2022 and generally available in March 2023, Application Composer is Read more about IDE extension for AWS Application Composer enhances visual modern applications development with AI-generated IaC[…]

Amazon SageMaker Studio adds web-based interface, Code Editor, flexible workspaces, and streamlines user onboarding

Today, we are announcing an improved Amazon SageMaker Studio experience! The new SageMaker Studio web-based interface loads faster and provides consistent access to your preferred integrated development environment (IDE) and SageMaker resources and tooling, irrespective of your IDE choice. In addition to JupyterLab and RStudio, SageMaker Studio now includes a fully managed Code Editor based Read more about Amazon SageMaker Studio adds web-based interface, Code Editor, flexible workspaces, and streamlines user onboarding[…]

Three new capabilities for Amazon Inspector broaden the realm of vulnerability scanning for workloads

Today, Amazon Inspector adds three new capabilities to increase the realm of possibilities when scanning your workloads for software vulnerabilities: Amazon Inspector introduces a new set of open source plugins and an API allowing you to assess your container images for software vulnerabilities at build time directly from your continuous integration and continuous delivery (CI/CD) Read more about Three new capabilities for Amazon Inspector broaden the realm of vulnerability scanning for workloads[…]

Easily deploy SaaS products with new Quick Launch in AWS Marketplace

Today we are excited to announce the general availability of SaaS Quick Launch, a new feature in AWS Marketplace that makes it easy and secure to deploy SaaS products. Before SaaS Quick Launch, configuring and launching third-party SaaS products could be time-consuming and costly, especially in certain categories like security and monitoring. Some products require Read more about Easily deploy SaaS products with new Quick Launch in AWS Marketplace[…]

Package and deploy models faster with new tools and guided workflows in Amazon SageMaker

I’m happy to share that Amazon SageMaker now comes with an improved model deployment experience to help you deploy traditional machine learning (ML) models and foundation models (FMs) faster. As a data scientist or ML practitioner, you can now use the new ModelBuilder class in the SageMaker Python SDK to package models, perform local inference Read more about Package and deploy models faster with new tools and guided workflows in Amazon SageMaker[…]

Use natural language to explore and prepare data with a new capability of Amazon SageMaker Canvas

Today, I’m happy to introduce the ability to use natural language instructions in Amazon SageMaker Canvas to explore, visualize, and transform data for machine learning (ML). SageMaker Canvas now supports using foundation model-(FM) powered natural language instructions to complement its comprehensive data preparation capabilities for data exploration, analysis, visualization, and transformation. Using natural language instructions, Read more about Use natural language to explore and prepare data with a new capability of Amazon SageMaker Canvas[…]

Amazon SageMaker adds new inference capabilities to help reduce foundation model deployment costs and latency

Today, we are announcing new Amazon SageMaker inference capabilities that can help you optimize deployment costs and reduce latency. With the new inference capabilities, you can deploy one or more foundation models (FMs) on the same SageMaker endpoint and control how many accelerators and how much memory is reserved for each FM. This helps to Read more about Amazon SageMaker adds new inference capabilities to help reduce foundation model deployment costs and latency[…]

Leverage foundation models for business analysis at scale with Amazon SageMaker Canvas

Today, I’m excited to introduce a new capability in Amazon SageMaker Canvas to use foundation models (FMs) from Amazon Bedrock and Amazon SageMaker Jumpstart through a no-code experience. This new capability makes it easier for you to evaluate and generate responses from FMs for your specific use case with high accuracy. Every business has its Read more about Leverage foundation models for business analysis at scale with Amazon SageMaker Canvas[…]