Remove Applications Remove Lambda Remove Scalability
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Automate Amazon Bedrock batch inference: Building a scalable and efficient pipeline

AWS Machine Learning - AI

To address this consideration and enhance your use of batch inference, we’ve developed a scalable solution using AWS Lambda and Amazon DynamoDB. We walk you through our solution, detailing the core logic of the Lambda functions. Amazon S3 invokes the {stack_name}-create-batch-queue-{AWS-Region} Lambda function.

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

AWS Machine Learning - AI

The workflow includes the following steps: The process begins when a user sends a message through Google Chat, either in a direct message or in a chat space where the application is installed. Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message.

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A Beginner’s Guide To Building Microservices With AWS Lambda

Dzone - DevOps

When used to construct microservices, AWS Lambda provides a route to craft scalable and flexible cloud-based applications. AWS Lambda supports code execution without server provisioning or management, rendering it an appropriate choice for microservices architecture.

Lambda 97
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Service Oriented Architecture with AWS Lambda: A Step-by-Step Tutorial

Toptal

AWS Lambda offers a relatively thin service with a rich set of ancillary configuration options, making it possible to implement easily scalable and maintainable applications leveraging these services.

Lambda 91
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AWS Lambda Pricing: Low, But Unpredictable

ParkMyCloud

Today’s entry into our exploration of public cloud prices focuses on AWS Lambda pricing. In this article, we’ll take a look at the Lambda pricing model, and some things you need to keep in mind when estimating costs for serverless infrastructure. How AWS Lambda Pricing Works. AWS Lambda pricing is based on what you use.

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Build a contextual chatbot application using Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

Therefore, a managed solution that handles these undifferentiated tasks could streamline and accelerate the process of implementing and managing RAG applications. It also supports source attribution and short-term memory needed for RAG applications. A contextually relevant response is sent back to the chatbot application and user.

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Knowledge Bases for Amazon Bedrock now supports advanced parsing, chunking, and query reformulation giving greater control of accuracy in RAG based applications

AWS Machine Learning - AI

However, it’s important to note that in RAG-based applications, when dealing with large or complex input text documents, such as PDFs or.txt files, querying the indexes might yield subpar results. In the next section, we discuss custom processing using Lambda function provided by Knowledge bases for Amazon Bedrock.