AWS Machine Learning Blog
Category: Amazon CloudWatch
Detect and protect sensitive data with Amazon Lex and Amazon CloudWatch Logs
In today’s digital landscape, the protection of personally identifiable information (PII) is not just a regulatory requirement, but a cornerstone of consumer trust and business integrity. Organizations use advanced natural language detection services like Amazon Lex for building conversational interfaces and Amazon CloudWatch for monitoring and analyzing operational data. One risk many organizations face is […]
The Weather Company enhances MLOps with Amazon SageMaker, AWS CloudFormation, and Amazon CloudWatch
In this post, we share the story of how The Weather Company (TWCo) enhanced its MLOps platform using services such as Amazon SageMaker, AWS CloudFormation, and Amazon CloudWatch. TWCo data scientists and ML engineers took advantage of automation, detailed experiment tracking, integrated training, and deployment pipelines to help scale MLOps effectively. TWCo reduced infrastructure management time by 90% while also reducing model deployment time by 20%.
Identify idle endpoints in Amazon SageMaker
Amazon SageMaker is a machine learning (ML) platform designed to simplify the process of building, training, deploying, and managing ML models at scale. With a comprehensive suite of tools and services, SageMaker offers developers and data scientists the resources they need to accelerate the development and deployment of ML solutions. In today’s fast-paced technological landscape, […]
Improve visibility into Amazon Bedrock usage and performance with Amazon CloudWatch
In this blog post, we will share some of capabilities to help you get quick and easy visibility into Amazon Bedrock workloads in context of your broader application. We will use the contextual conversational assistant example in the Amazon Bedrock GitHub repository to provide examples of how you can customize these views to further enhance visibility, tailored to your use case. Specifically, we will describe how you can use the new automatic dashboard in Amazon CloudWatch to get a single pane of glass visibility into the usage and performance of Amazon Bedrock models and gain end-to-end visibility by customizing dashboards with widgets that provide visibility and insights into components and operations such as Retrieval Augmented Generation in your application.
How LotteON built dynamic A/B testing for their personalized recommendation system
This post is co-written with HyeKyung Yang, Jieun Lim, and SeungBum Shim from LotteON. LotteON is transforming itself into an online shopping platform that provides customers with an unprecedented shopping experience based on its in-store and online shopping expertise. Rather than simply selling the product, they create and let customers experience the product through their […]
Open source observability for AWS Inferentia nodes within Amazon EKS clusters
This post walks you through the Open Source Observability pattern for AWS Inferentia, which shows you how to monitor the performance of ML chips, used in an Amazon Elastic Kubernetes Service (Amazon EKS) cluster, with data plane nodes based on Amazon Elastic Compute Cloud (Amazon EC2) instances of type Inf1 and Inf2.
Techniques and approaches for monitoring large language models on AWS
Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP), improving tasks such as language translation, text summarization, and sentiment analysis. However, as these models continue to grow in size and complexity, monitoring their performance and behavior has become increasingly challenging. Monitoring the performance and behavior of LLMs is a critical task […]
Build an internal SaaS service with cost and usage tracking for foundation models on Amazon Bedrock
In this post, we show you how to build an internal SaaS layer to access foundation models with Amazon Bedrock in a multi-tenant (team) architecture. We specifically focus on usage and cost tracking per tenant and also controls such as usage throttling per tenant. We describe how the solution and Amazon Bedrock consumption plans map to the general SaaS journey framework. The code for the solution and an AWS Cloud Development Kit (AWS CDK) template is available in the GitHub repository.
Unlocking language barriers: Translate application logs with Amazon Translate for seamless support
This post addresses the challenge faced by developers and support teams when application logs are presented in languages other than English, making it difficult for them to debug and provide support. The proposed solution uses Amazon Translate to automatically translate non-English logs in CloudWatch, and provides step-by-step guidance on deploying the solution in your environment.
Enable pod-based GPU metrics in Amazon CloudWatch
This post details how to set up container-based GPU metrics and provides an example of collecting these metrics from EKS pods.