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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. Overview of solution The first thing to consider is that different metrics require different computation considerations.

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Sending OpenTelemetry Data From AWS Lambda to Honeycomb

Honeycomb

In this post, I describe how to send OpenTelemetry (OTel) data from an AWS Lambda instance to Honeycomb. I will be showing these steps using a Lambda written in Python and created and deployed using AWS Serverless Application Model (AWS SAM). Add your Honeycomb environment’s API key to AWS Secrets Manager.

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Optimizing Medication Management: How AWS ETL Transforms Healthcare Data for a Leading PBM

Perficient

How are AWS ETL Services Used to Overcome the Challenges AWS ETL services offer powerful solutions to tackle such challenges. Unified data cataloging For the disparate sources, AWS Glue Crawlers creates a searchable catalog of datasets, tables, and their associated schemas.

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Learning Lambda — Part 9

Mike Roberts

Scaling and State This is Part 9 of Learning Lambda, a tutorial series about engineering using AWS Lambda. So far in this series we’ve only been talking about processing a small number of events with Lambda, one after the other. Finally I mention Lambda’s limited, but not trivial, vertical scaling capability.

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Learning Lambda — Part 7

Mike Roberts

Error Handling This is Part 7 of Learning Lambda, a tutorial series about engineering using AWS Lambda. Welcome to Part 7 of Learning Lambda! Classes of error When using AWS Lambda there are several different classes of error that can occur.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning - AI

Understanding and addressing LLM vulnerabilities, threats, and risks during the design and architecture phases helps teams focus on maximizing the economic and productivity benefits generative AI can bring. What are some ways to implement security and privacy controls in the development lifecycle for generative AI LLM applications on AWS?

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Lowering TCO | Maximizing Business Value with AWS

Linux Academy

Moving to AWS abstracts away the majority of these costs, replacing them with services that can automate them while drastically reducing costs. Longer term, applications that can be run using microservices, such as Lambda, can reduce costs even further. Moving databases to a managed service such as AWS RDS. Improving elasticity.

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