Best Practices

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Build a conversational data assistant, Part 1: Text-to-SQL with Amazon Bedrock Agents

Advanced (300), Amazon Bedrock, Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, Amazon QuickSight, Amazon Redshift, Artificial Intelligence, Best Practices /

What if you could replace hours of data analysis with a minute-long conversation? Large language models can transform how we bridge the gap between business questions and actionable data insights. For most organizations, this gap remains stubbornly wide, with business teams trapped in endless cycles—decoding metric definitions and hunting for the correct data sources to […]

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Optimize RAG in production environments using Amazon SageMaker JumpStart and Amazon OpenSearch Service

Amazon OpenSearch Service, Amazon SageMaker Lakehouse, Best Practices, Intermediate (200) /

Generative AI has revolutionized customer interactions across industries by offering personalized, intuitive experiences powered by unprecedented access to information. This transformation is further enhanced by Retrieval Augmented Generation (RAG), a technique that allows large language models (LLMs) to reference external knowledge sources beyond their training data. RAG has gained popularity for its ability to improve

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Advancing AI agent governance with Boomi and AWS: A unified approach to observability and compliance

Amazon Bedrock, Amazon Bedrock Agents, Amazon CloudWatch, Amazon Data Firehose, Best Practices, Customer Solutions, Intermediate (200) /

Just as APIs became the standard for integration, AI agents are transforming workflow automation through intelligent task coordination. AI agents are already enhancing decision-making and streamlining operations across enterprises. But as adoption accelerates, organizations face growing complexity in managing them at scale. Organizations struggle with observability and lifecycle management, finding it difficult to monitor performance

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Build AWS architecture diagrams using Amazon Q CLI and MCP

AI/ML, Amazon Q Developer, Best Practices, Generative AI, Technical How-to /

Creating professional AWS architecture diagrams is a fundamental task for solutions architects, developers, and technical teams. These diagrams serve as essential communication tools for stakeholders, documentation of compliance requirements, and blueprints for implementation teams. However, traditional diagramming approaches present several challenges: Time-consuming process – Creating detailed architecture diagrams manually can take hours or even days

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AWS costs estimation using Amazon Q CLI and AWS Cost Analysis MCP

Amazon Q Developer, Best Practices, Generative AI, Technical How-to /

Managing and optimizing AWS infrastructure costs is a critical challenge for organizations of all sizes. Traditional cost analysis approaches often involve the following: Complex spreadsheets – Creating and maintaining detailed cost models, which requires significant effort Multiple tools – Switching between the AWS Pricing Calculator, AWS Cost Explorer, and third-party tools Specialized knowledge – Understanding

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Tailor responsible AI with new safeguard tiers in Amazon Bedrock Guardrails

Amazon Bedrock, Amazon Bedrock Guardrails, Artificial Intelligence, Best Practices, Generative AI, Responsible AI, Technical How-to, Thought Leadership /

Amazon Bedrock Guardrails provides configurable safeguards to help build trusted generative AI applications at scale. It provides organizations with integrated safety and privacy safeguards that work across multiple foundation models (FMs), including models available in Amazon Bedrock, as well as models hosted outside Amazon Bedrock from other model providers and cloud providers. With the standalone

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Structured data response with Amazon Bedrock: Prompt Engineering and Tool Use

Amazon Bedrock, Best Practices, Generative AI, Intermediate (200), Technical How-to /

Generative AI is revolutionizing industries by streamlining operations and enabling innovation. While textual chat interactions with GenAI remain popular, real-world applications often depend on structured data for APIs, databases, data-driven workloads, and rich user interfaces. Structured data can also enhance conversational AI, enabling more reliable and actionable outputs. A key challenge is that LLMs (Large

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Effective cost optimization strategies for Amazon Bedrock

Amazon Bedrock, Best Practices, Cloud Cost Optimization, Generative AI /

Customers are increasingly using generative AI to enhance efficiency, personalize experiences, and drive innovation across various industries. For instance, generative AI can be used to perform text summarization, facilitate personalized marketing strategies, create business-critical chat-based assistants, and so on. However, as generative AI adoption grows, associated costs can escalate in several areas including cost in

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Build a serverless audio summarization solution with Amazon Bedrock and Whisper

Amazon API Gateway, Amazon Bedrock, Amazon Bedrock Guardrails, Amazon EventBridge, Application Integration, Architecture, AWS Step Functions, Best Practices, Generative AI, Technical How-to /

Recordings of business meetings, interviews, and customer interactions have become essential for preserving important information. However, transcribing and summarizing these recordings manually is often time-consuming and labor-intensive. With the progress in generative AI and automatic speech recognition (ASR), automated solutions have emerged to make this process faster and more efficient. Protecting personally identifiable information (PII)

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Implement semantic video search using open source large vision models on Amazon SageMaker and Amazon OpenSearch Serverless

Amazon Machine Learning, Amazon OpenSearch Service, Amazon SageMaker, Amazon SageMaker AI, Best Practices, Generative AI, Technical How-to, Video analysis /

As companies and individual users deal with constantly growing amounts of video content, the ability to perform low-effort search to retrieve videos or video segments using natural language becomes increasingly valuable. Semantic video search offers a powerful solution to this problem, so users can search for relevant video content based on textual queries or descriptions.

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