Remove Events Remove Lambda Remove Scalability Remove Storage
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Build scalable Low-Code backends with Booster

The Agile Monkey

However, these tools may not be suitable for more complex data or situations requiring scalability and robust business logic. The app, called Live Questions, is a tool for live events, keynotes, and Q&A sessions that allows hosts to create a topic and gather questions from other users in real time. create a topic).

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Transform one-on-one customer interactions: Build speech-capable order processing agents with AWS and generative AI

AWS Machine Learning - AI

In this post, we show you how to build a speech-capable order processing agent using Amazon Lex, Amazon Bedrock, and AWS Lambda. A Lambda function pulls the appropriate prompt template from the Lambda layer and formats model prompts by adding the customer input in the associated prompt template. awscli>=1.29.57

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Dynamic Data Processing Using Serverless Java With Quarkus on AWS Lambda (Part 1)

Dzone - DevOps

This was not only about rewriting applications, but the backend data stores were also redesigned in terms of dynamic scalability , high performance, and flexibility for event-driven architecture.

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AWS Lambda: The Honcho of the Serverless World

RapidValue

One such service is their serverless computing service , AWS Lambda. For the uninitiated, Lambda is an event-driven serverless computing platform that lets you run code without managing or provisioning servers and involves zero administration. How does AWS Lambda Work. Why use AWS Lambda? Read on to know.

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Journey to Event Driven – Part 3: The Affinity Between Events, Streams and Serverless

Confluent

Given that it is at a relatively early stage, developers are still trying to grok the best approach for each cloud vendor and often face the following question: Should I go cloud native with AWS Lambda, GCP functions, etc., What is more, as the world adopts the event-driven streaming architecture, how does it fit with serverless?

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Techniques and approaches for monitoring large language models on AWS

AWS Machine Learning - AI

Our proposed architecture provides a scalable and customizable solution for online LLM monitoring, enabling teams to tailor your monitoring solution to your specific use cases and requirements. The file saved on Amazon S3 creates an event that triggers a Lambda function. The function invokes the modules.

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Build an internal SaaS service with cost and usage tracking for foundation models on Amazon Bedrock

AWS Machine Learning - AI

API Gateway routes the request to an AWS Lambda function ( bedrock_invoke_model ) that’s responsible for logging team usage information in Amazon CloudWatch and invoking the Amazon Bedrock model. After the Amazon Bedrock invocation, Amazon CloudTrail generates a CloudTrail event. requestId – The unique identifier of the request.

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