QBased on everything you've covered in both parts of your blog, here's a comprehensive summary that captures both the **fundamentals** and the **AI-specific capabilities** of OpenTelemetry.
Exam Decision Table
Requirement Choose Reason
Intent-based chatbot Amazon Lex Purpose-built for conversational workflows
Multi-turn slot filling Amazon Lex Native dialog management
Retrieve order status AWS Lambda Calls enterprise systems securely
Generate natural explanations Amazon Bedrock LLM reasoning and text generation
Summarize conversations Amazon Bedrock LLM summarization
Execute business logic AWS Lambda Orchestration and integration
Build a customer support bot with both transactional and generative capabilities Lex + Lambda + Bedrock Best of both worlds
An exam tip
A useful way to think about these services is:
Amazon Lex = How do I conduct the conversation? (intents, slots, dialog flow)
AWS Lambda = How do I retrieve or update enterprise data?
Amazon Bedrock = How do I reason over information or generate natural language?
If a scenario emphasizes structured conversations, slot filling, and predictable workflows, Lex is usually the stronger choice. If it emphasizes open-ended questions, summarization, content generation, or reasoning, Bedrock becomes the key service. Many real-world AWS architectures combine all three.
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