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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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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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Securing a Web Application with AWS Application Load Balancer

Stackery

AWS Lambdas don’t let you do that. If you’re still using an Elastic Compute Cloud (EC2) Virtual Machine, enjoy this very useful tutorial on load balancing. That’s what I’m using AWS Application Load Balancer (“ALB”) for, even though I have only a single instance at the moment so there’s no actual load balancing going on.

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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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Can VPC Lattice replace AWS Transit Gateway?

Xebia

This resembles a familiar concept from Elastic Load Balancing. A target group can refer to Instances, IP addresses, a Lambda function or an Application Load Balancer. If you’re coming from a setup using Application Load Balancers in front of EC2 instances, VPC Lattice pricing looks quite similar.

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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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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. Load balancer – Another option is to use a load balancer that exposes an HTTPS endpoint and routes the request to the orchestrator. API Gateway also provides a WebSocket API.