aws / aws/sagemaker-python-sdk
Native GRPC Support for Endpoints
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- Python
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描述
**Describe the feature you'd like**
Add support for making `GRPC` calls to sagemaker endpoints for model serving/batch transform. Currently, only `REST` is supported.
**How would this feature be used? Please describe.**
If one plans to deploy a model in an environment where clients make GRPC calls, it is currently not possible to use sagemaker to deploy models. REST is not an option in some deployment environments.
**Describe alternatives you've considered**
I understand there is the option to serialize the request/response data into recordio/protobuf and make a REST call but if clients are expecting to make GRPC calls, this is not an option.
If production clients will make GRPC calls it is not really worth the effort to implement a REST `serve` entrypoint in images, as it won't match how the model is called in production. This results in two different images and custom frameworks around serving/batch transformation. It would greatly improve the experience if data scientists are able to test a model with GRPC then directly deploy it via sagemaker.
**Additional context**
Getting a feeler out here for if this may be eventually supported. Is this something that could potentially be implemented in the sdk alone or would it require changes to proprietary apis? Basically, wondering if this is something that could be implemented by the community.
贡献指南
调研方向
该 issue 未指出 SageMaker endpoint 和 batch-transform 路径对应的 SDK 文件、测试或入口点。首先确定是否可以在 Python SDK 中实现原生 GRPC 支持,还是需要修改专有的 SageMaker API;完成的标准是客户端可以为模型服务和批量转换发起 GRPC 调用。
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评估
- 技术栈
- aws, grpc, python
- 领域
- api, cloud, machine-learning
- Issue 类型
- 功能
- 难度
- 5/5
- 预计耗时
- 一周以上
- 活跃度
- 停滞
- 描述清晰度
- 需要澄清
- 新手友好度
- 20/100