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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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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.

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AWS Lambda Versioning and Aliases

Linux Academy

The course has three new sections (and Lambda Versioning and Aliases plays an important part in the Lambda section): Deployment Pipelines. AWS Lambda, and. AWS Lambda and Serverless Concepts. Now to be clear, it is not Lambda’s sole purpose to work with CloudFormation, but it is certainly a common use case.

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Enhance conversational AI with advanced routing techniques with Amazon Bedrock

AWS Machine Learning - AI

This is done using ReAct prompting, which breaks down the task into a series of steps that are processed sequentially: For device metrics checks, we use the check-device-metrics action group, which involves an API call to Lambda functions that then query Amazon Athena for the requested data. It serves as the data source to the knowledge base.

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AWS vs. Azure vs. Google Cloud: Comparing Cloud Platforms

Kaseya

In addition, you can also take advantage of the reliability of multiple cloud data centers as well as responsive and customizable load balancing that evolves with your changing demands. Cloud adoption also provides businesses with flexibility and scalability by not restricting them to the physical limitations of on-premises servers.

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AWS Disaster Recovery Strategies – PoC with Terraform

Xebia

This post explores a proof-of-concept (PoC) written in Terraform , where one region is provisioned with a basic auto-scaled and load-balanced HTTP * basic service, and another recovery region is configured to serve as a plan B by using different strategies recommended by AWS. Pilot Light strategy diagram.

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Build RAG-based generative AI applications in AWS using Amazon FSx for NetApp ONTAP with Amazon Bedrock

AWS Machine Learning - AI

Event-driven compute with AWS Lambda is a good fit for compute-intensive, on-demand tasks such as document embedding and flexible large language model (LLM) orchestration, and Amazon API Gateway provides an API interface that allows for pluggable frontends and event-driven invocation of the LLMs.