Category: Learning Levels

SageMaker AI endpoints now support enhanced metrics with configurable publishing frequency. This launch provides the granular visibility needed to monitor, troubleshoot, and improve your production endpoints.

In this post, we will show you how to enforce data residency when deploying Amazon Quick Microsoft Teams extensions across multiple AWS Regions. You will learn how to configure multi-Region Amazon Quick extensions that automatically route users to AWS Region-appropriate resources, helping keep compliance with GDPR and other data sovereignty requirements.

In this post, we walk you through the process of using the Nova Forge SDK to train an Amazon Nova model using Amazon SageMaker AI Training Jobs.

This post shows you how to build an AI-powered A/B testing engine using Amazon Bedrock, Amazon Elastic Container Service, Amazon DynamoDB, and the Model Context Protocol (MCP). The system improves traditional A/B testing by analyzing user context  to make smarter variant assignment decisions during the experiment.

In this post, you will learn how to migrate from Nova 1 to Nova 2 on Amazon Bedrock. We cover model mapping, API changes, code examples using the Converse API, guidance on configuring new capabilities, and a summary of use cases. We conclude with a migration checklist to help you plan and execute your transition.

This blog post provides step-by-step guidance on implementing an offline feature store using SageMaker Catalog within a SageMaker Unified Studio domain. By adopting a publish-subscribe pattern, data producers can use this solution to publish curated, versioned feature tables—while data consumers can securely discover, subscribe to, and reuse them for model development.

Today, we’re announcing two new Amazon CloudWatch metrics for Amazon Bedrock, TimeToFirstToken and EstimatedTPMQuotaUsage. In this post, we cover how these work and how to set alarms, establish baselines, and proactively manage capacity using them.

In this post, you will understand how Policy in Amazon Bedrock AgentCore creates a deterministic enforcement layer that operates independently of the agent’s own reasoning. You will learn how to turn natural language descriptions of your business rules into Cedar policies, then use those policies to enforce fine-grained, identity-aware controls so that agents only access the tools and data that their users are authorized to use. You will also see how to apply Policy through AgentCore Gateway, intercepting and evaluating every agent-to-tool request at runtime.

This post shows you how to build a scalable multimodal video search system that enables natural language search across large video datasets using Amazon Nova models and Amazon OpenSearch Service. You will learn how to move beyond manual tagging and keyword-based searches to enable semantic search that captures the full richness of video content.

In this post, we walk through a multi-developer CI/CD pipeline for Amazon Lex that enables isolated development environments, automated testing, and streamlined deployments. We show you how to set up the solution and share real-world results from teams using this approach.