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Amazon SageMaker Runtime

Amazon SageMaker Runtime

UpOpen Sourcecloudby Amazon Web Services62· JavaScript· MIT

The Amazon SageMaker runtime API.

Visit site ↗Source ↗Health checked 11h ago
Use it when

Supports real-time model inference

Watch for

Check the docs depth and real endpoint shape before assuming production fit.

First check

To start, obtain appropriate authentication credentials as the auth type is unknown. Use the API to invoke SageMaker model endpoints for inference.

Auth
CORS
No
HTTPS
Yes
Signup
?
Latency
10 ms
Protocol
REST
Pricing
Stars
62

Uptime · 30-day window

Probes: 9Uptime: 100%Avg latency: 46ms

GitHub activity

62JavaScriptMIT17 open issuesLast commit 118d ago
01

About this API

Amazon SageMaker Runtime provides an interface to invoke machine learning models deployed on the Amazon SageMaker platform. It allows developers to send inference requests to models hosted in the cloud and receive predictions in real time.

This API is primarily used by developers and data scientists who want to integrate machine learning predictions into their applications without managing the underlying infrastructure. It supports scalable and low-latency inference, making it suitable for production environments.

While the input description is limited, the API is relevant for cloud-based ML workflows where real-time model invocation is required. Authentication details are not specified, so users should refer to official Amazon SageMaker documentation for setup and security requirements.

02

What you can build

  • 1Invoke machine learning model endpoints
  • 2Manage real-time inference requests
  • 3Integrate ML predictions into applications
03

Strengths & limitations

Strengths

  • Supports real-time model inference
  • Integrates with Amazon SageMaker models
  • Cloud-based scalable runtime
04

Example request

curl https://github.com/mermade/aws2openapi/<endpoint>
05

Getting started

To start, obtain appropriate authentication credentials as the auth type is unknown. Use the API to invoke SageMaker model endpoints for inference.

06

FAQ

Do I need an API key to use Amazon SageMaker Runtime?+

Authentication details are not specified; typically, AWS credentials are required.

Can I use this API for real-time predictions?+

Yes, it supports real-time model inference requests.

Is HTTPS required to access the API?+

While not specified, AWS APIs generally require HTTPS for secure communication.

Can I invoke the API directly from a browser?+

Direct browser use is uncommon due to authentication and security requirements.

07

Technical details

CORS: NoHTTPS: YesSignup: ?Open source: Yes
Auth type
unknown
Pricing
unknown
Protocols
REST
Response time
10 ms
Last health check
5/20/2026, 8:19:43 AM
08

Tags

09

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