课程: Advanced AI Analytics on AWS: Amazon Bedrock, Q, SageMaker Data Wrangler, and QuickSight

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Visualizing Rust and Bedrock analytics integration

Visualizing Rust and Bedrock analytics integration

课程: Advanced AI Analytics on AWS: Amazon Bedrock, Q, SageMaker Data Wrangler, and QuickSight

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Visualizing Rust and Bedrock analytics integration

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- [Instructor] Today we're going to explore a Rust implementation for Amazon Bedrock with Claude. And we could take a look at a visualization that is showing this data flow and processing pipeline. A few things we're going to talk about include a modern cloud native architecture, also realtime data processing, and then this continuous feedback loop. So if we look at the upper section here, this data processing pipeline here we have the CSV file. And this is going to be the beginning where we ingest this raw sales data and we're able to use the Rust type system as well to have safe parsing, which is really critical with large scale data processing pipelines. We also have the AWS Bedrock client in the center, and this is where we do the configuration management with environmental variables. And we also have the robust client initialization with proper air handling. For example, you know, we don't have the credentials or some other bug. And we also have an E-sync await pattern as well…

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