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AWS AppConfig announces feature flag targets, variants, and splits

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Today, AWS announces advanced targeting capabilities for AWS AppConfig feature flags. Customers can set up multiple values within flag data, and target those values to fine-grained and high-cardinality user segments. A common use-case for feature flag targets include allow lists, where a customer can specify user IDs or customer tiers, and only enable a new or premium feature for those segments. Another use-case is to split traffic to 15% of your user-base, and experiment with a user experience optimization for a limited cohort of users before rolling the feature out to all users.

Customers can start using this powerful feature by creating an AWS AppConfig feature flag , set its value, and then create one or more variants of that flag with different variations of data. Customers then create rules to determine which variant should be targeted to specific segments. Once the flag, variants, and rules are created, customers use the latest version of the AWS AppConfig Agent running in EC2, Lambda, ECS, EKS, or on-premises to retrieve the flag data. When requesting flag data, customers pass in context, like user IDs or other user metadata, which are evaluated client-side against the flag rules to return the appropriate and specific data.

AWS AppConfig’s feature flag targets, variants, and splits are available in all AWS Regions, including the AWS GovCloud (US) Regions. To get started, use the AWS AppConfig Getting Started Guide .

Amazon ECS now supports Amazon Linux 2023 and more for on-premises container workloads

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Amazon Elastic Container Service (Amazon ECS) now supports managing on-premises workloads running on Amazon Linux 2023, Fedora 40, Debian 11, Debian 12, Ubuntu 24, and CentOS Stream 9. Amazon ECS Anywhere is a feature of Amazon ECS that enables you to run and manage container-based applications on-premises, including on your own virtual machines (VMs) and bare metal servers.

Amazon ECS Anywhere is available in all AWS Regions globally . To learn more visit the ECS Anywhere user guide .
 

Meta Llama 3.1 generative AI models now available in Amazon Bedrock

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The most advanced Meta Llama models to date, Llama 3.1, are now available in Amazon Bedrock . Amazon Bedrock offers a turnkey way to build generative AI applications with Llama. Llama 3.1 models are a collection of 8B, 70B, and 405B parameter size models offering new capabilities for your generative AI applications.

All Llama 3.1 models demonstrate significant improvements over previous versions. The models support a 128K context length, have 16 times the capacity of Llama 3, and exhibit improved reasoning for multilingual dialogue use cases in eight languages. The models access more information from lengthy text to make more informed decisions and leverage richer contextual data to generate more subtle and refined responses. According to Meta, Llama 3.1 405B is one of the best and largest publicly available foundation models and is well suited for synthetic data generation and model distillation. Llama 3.1 models also provide state-of-the-art capabilities in general knowledge, math, tool use, and multilingual translation.

Meta’s Llama 3.1 models are available in Amazon Bedrock in the US West (Oregon) Region. To learn more, read the AWS News launch blog , Llama in Amazon Bedrock product page , and documentation . To get started with Llama 3.1 in Amazon Bedrock, visit the Amazon Bedrock console . To request to be considered for access to the preview of Llama 3.1 405B in Amazon Bedrock, contact your AWS account team or submit a support ticket via the AWS Management Console . When creating the support ticket, select Bedrock as the Service and Models as the Category.

AWS Mainframe Modernization Code Conversion with mLogica is now generally available

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We are excited to announce public availability of Mainframe Modernization Code Conversion with mLogica. This new capability enables automated conversion of legacy code written in Assembler language to COBOL. The majority of mainframe environments include Assembler code that is expensive to maintain. Modernization of the code unblocks modernization projects to enable refactor projects, replatform projects, on-mainframe modernization initiatives, within AWS Mainframe Modernization toolchains, or to use alongside third-party modernization toolchains.
AWS Mainframe Modernization service allows you to modernize and migrate on-premises mainframe applications to AWS. It offers automated refactor and replatform patterns, as well as augmentation patterns via data replication and file transfer.

AWS Mainframe Modernization Code Conversion is available through the AWS Mainframe Modernization service console. To learn more, visit AWS Mainframe Modernization service product and documentation pages.
 

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