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Boost Your Productivity with awscurl: Simplifying IAM-Secured API Testing in AWS

Xebia

When you use AWS, you can interact with it through the console, sdk, or cli. But what if you want to test the API from your local machine or the cloud shell from the console? You can use it to perform any API call that supports sigv4, but for the majority of services, the AWS cli tool is the best tool for the job.

AWS 162
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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

AWS provides a powerful set of tools and services that simplify the process of building and deploying generative AI applications, even for those with limited experience in frontend and backend development. The AWS deployment architecture makes sure the Python application is hosted and accessible from the internet to authenticated users.

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What happens when you leak AWS credentials and how AWS minimizes the damage

Xebia

I heard multiple times that AWS scans public GitHub repositories for AWS credentials and informs its users of the leaked credentials. So I am curious to see this for myself, so I decided to intentionally leak AWS credentials to a Public GitHub repository. Below you will find detailed information about every event.

AWS 246
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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning - AI

Recognizing this need, we have developed a Chrome extension that harnesses the power of AWS AI and generative AI services, including Amazon Bedrock , an AWS managed service to build and scale generative AI applications with foundation models (FMs). The user signs in by entering a user name and a password.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Careful model selection, fine-tuning, configuration, and testing might be necessary to balance the impact of latency and cost with the desired classification accuracy. Before migrating any of the provided solutions to production, we recommend following the AWS Well-Architected Framework. seconds.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. This allows teams to focus more on implementing improvements and optimizing AWS infrastructure. This systematic approach leads to more reliable and standardized evaluations.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. The generative AI playground is a UI provided to tenants where they can run their one-time experiments, chat with several FMs, and manually test capabilities such as guardrails or model evaluation for exploration purposes.