Practical overview
When it fits
Use it when you need an implementation reference for an AWS generative AI stack and can select and adapt an individual sample to your requirements.
Who it is for
- Developers building generative AI backends on AWS.
- Teams comparing patterns for SageMaker model hosting, Bedrock agents, retrieval-augmented applications, or MCP servers.
Documented uses
- Study a CDK pattern for deploying a model endpoint and routing inference requests through Lambda.
- Explore examples that connect Bedrock agents or knowledge bases with S3 and OpenSearch.
- Use a sample application as a starting point for a generative AI workflow such as RFP response generation or contract analysis.
Requirements & limits
The repository is public and lists an Apache-2.0 license.
- Examples vary in purpose, model, infrastructure and language; choose the sample matching the intended workload.
- Several SageMaker examples deploy model endpoints and pair them with Lambda inference functions, while Bedrock samples demonstrate different agent and retrieval patterns.
- Some entries are described as prototypes or sample applications rather than general-purpose products.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Review a SageMaker JumpStart model deployment sample
Identify the components in the TypeScript sample for deploying a Llama 2 real-time endpoint and an inference function.
Before you start
- AWS Generative AI CDK Constructs sample repository
Steps
Open the SageMaker JumpStart model sample linked from the repository README.
Review the sample as a TypeScript backend application.
Note that the sample describes a SageMaker real-time endpoint hosting a Llama 2 model from Amazon JumpStart and an AWS Lambda function that sends inference requests to the endpoint.
Expected outcome
You can identify the sample’s stated model-hosting and inference components.
Guide limitations
- The README does not provide setup or deployment instructions, invocation details, or verification steps.
Compare options for Model inference and serving
These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| Generative AI Cdk Constructs Samples | Study a CDK pattern for deploying a model endpoint and routing inference requests through Lambda. | Cloud, Server | The repository is public and lists an Apache-2.0 license. |
| Hyperpose | Customize pose-estimation architectures and datasets. | Docker, Linux, macOS, Windows | |
| Multi Task Nlp | Define multiple tasks and their data and model settings in a YAML file. | Linux, macOS, Windows | The project is an open-source library under the Apache-2.0 license, distributed through its public GitHub repository. |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 16 October 2026
- Original website title
- aws-samples/generative-ai-cdk-constructs-samples · Official homepage title · retained in its source language

