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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message. After it’s authenticated, the request is forwarded to another Lambda function that contains our core application logic. The code runs in a Lambda function. Implement your business logic in this file.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

When API Gateway receives the request, it triggers an AWS Lambda The Lambda function sends the question to the classifier LLM to determine whether it is a history or math question. These embeddings are then saved as a reference index inside an in-memory FAISS vector store, which is deployed as a Lambda layer.

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Building Resilient Public Networking on AWS: Part 4

Xebia

One of the key differences between the approach in this post and the previous one is that here, the Application Load Balancers (ALBs) are private, so the only element exposed directly to the Internet is the Global Accelerator and its Edge locations. Fewer hops on the Internet result in better and more consistent response times.

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Using design patterns in AWS Lambda

Xebia

But when the world first shifted to the internet the general feeling was that these design patterns would not work for the web. Or use a compiled language like golang for your Lambda functions. Conclusion You can use design patterns in your Lambda functions. For very simple Lambda functions it might not be worth it.

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5 Simple Ways to Improve Security with Lambda at Edge

Modus Create

Lambda@Edge is Amazon Web Services’s (AWS’s) Lambda service run on the Amazon CloudFront Global Edge Network. There are numerous measures you can take to improve security with Lambda@Edge. Lambda@Edge provides you with the ability to customize headers after responses have left the origin. X-XSS-Protection.

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Dynamic Routing with AWS Lambda@Edge

LaunchDarkly

TrueCar had been hosting its internet presence in one or more colocation facilities with traditional business, design, development, and operational staff working to produce a world-class website experience for consumers. Early in 2016, TrueCar decided to move internet operations off premises from its data centers to the AWS cloud.

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Revolutionize trip planning with Amazon Bedrock and Amazon Location Service

AWS Machine Learning - AI

If an image is uploaded, it is stored in Amazon Simple Storage Service (Amazon S3) , and a custom AWS Lambda function will use a machine learning model deployed on Amazon SageMaker to analyze the image to extract a list of place names and the similarity score of each place name. The following figure shows the start of a trip-planning chat.