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Edge Delta rakes in $63M for its distributed approach to data observability

TechCrunch

Databases are growing at an exponential rate these days, and so when it comes to real-time data observability, organizations are often fighting a losing battle if they try to run analytics or any observability process in a centralized way. ” he exclaimed.). “It makes us much more unique.”

Data 192
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Serverless is more than AWS Lambda

Stackery

Too often serverless is equated with just AWS Lambda. Yes, it’s true: Amazon Web Services (AWS) helped to pioneer what is commonly referred to as serverless today with AWS Lambda, which was first announced back in 2015. Lambda is just one component of a modern serverless stack.

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Innovative data integration in 2024: Pioneering the future of data integration

CIO

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

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CBRE and AWS perform natural language queries of structured data using Amazon Bedrock

AWS Machine Learning - AI

The opportunities to unlock value using AI in the commercial real estate lifecycle starts with data at scale. Although CBRE provides customers their curated best-in-class dashboards, CBRE wanted to provide a solution for their customers to quickly make custom queries of their data using only natural language prompts.

AWS 127
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Fundamentals of Data Engineering

Xebia

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

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Using Agents for Amazon Bedrock to interactively generate infrastructure as code

AWS Machine Learning - AI

This solution shows how Amazon Bedrock agents can be configured to accept cloud architecture diagrams, automatically analyze them, and generate Terraform or AWS CloudFormation templates. Solution overview Before we explore the deployment process, let’s walk through the key steps of the architecture as illustrated in Figure 1.

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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. A modular architecture, where each module can intake model inference data and produce its own metrics, is necessary.