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ECS Fargate Persistent Storage: EFS Access Points vs. Lambda Workarounds

Xebia

When running a Docker container on ECS Fargate, persistent storage is often a necessity. I initially attempted to solve this by manually creating the required directory on EFS using a Lambda-backed custom resource. A Lambda function could do this, so I started implementing a custom resource. How about a custom resource?

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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning - AI

Recognizing this need, we have developed a Chrome extension that harnesses the power of AWS AI and generative AI services, including Amazon Bedrock , an AWS managed service to build and scale generative AI applications with foundation models (FMs). The user signs in by entering a user name and a password.

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Automate Amazon Bedrock batch inference: Building a scalable and efficient pipeline

AWS Machine Learning - AI

Refer to Supported Regions and models for batch inference for current supporting AWS Regions and models. To address this consideration and enhance your use of batch inference, we’ve developed a scalable solution using AWS Lambda and Amazon DynamoDB. It stores information such as job ID, status, creation time, and other metadata.

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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. You can use AWS services such as Application Load Balancer to implement this approach. API Gateway also provides a WebSocket API. These components are illustrated in the following diagram.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. This allows teams to focus more on implementing improvements and optimizing AWS infrastructure. This systematic approach leads to more reliable and standardized evaluations.

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

AWS Machine Learning - AI

AWS offers powerful generative AI services , including Amazon Bedrock , which allows organizations to create tailored use cases such as AI chat-based assistants that give answers based on knowledge contained in the customers’ documents, and much more. The following figure illustrates the high-level design of the solution.

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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning - AI

The workflow includes the following steps: Documents (owner manuals) are uploaded to an Amazon Simple Storage Service (Amazon S3) bucket. The Lambda function runs the database query against the appropriate OpenSearch Service indexes, searching for exact matches or using fuzzy matching for partial information.

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