Basic Information
| Field | Details |
|---|---|
| English name | Amazon Bedrock |
| Full name | Amazon Bedrock |
| Chinese description | 生成式 AI 基础模型平台 |
| Japanese description | 生成 AI 基盤モデル |
| Exam frequency | ⭐⭐⭐ |
| Often confused with | SageMaker |
In one sentence
Use foundation models through managed APIs to build generative-AI applications without managing model infrastructure.
Key points
- It supports generation, summarization, question answering, content creation, and enterprise-knowledge use cases.
- Applications still need IAM, data permissions, encryption, auditing, output validation, and human review.
- Bedrock is for building your own generative-AI applications; Amazon Q is a ready-made assistant.
Exam focus
- Foundation models, managed APIs, and generative-AI apps point to Bedrock.
- Choose SageMaker for a fully custom ML training and deployment lifecycle.
Common pitfalls
- Do not choose by product name alone; confirm data type, latency, control, operations, and cost constraints.
Remember
Bedrock builds with foundation models; Amazon Q provides the assistant.