Amazon SageMaker Service
amazonaws · Cloud
Provides APIs for creating and managing SageMaker resources. Other Resources: SageMaker Developer Guide Amazon Augmented AI Runtime API Reference
Authentication
Sample Requests
Lists the actions in your account and their properties.
Hover any highlighted part to learn what it does
| X-Amz-Target | SageMaker.ListActions |
curl -X POST "https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListActions?NextToken=example&MaxResults=example" \ -H "X-Amz-Target: SageMaker.ListActions"
import requests
params = {
"NextToken": "example",
"MaxResults": "example"
}
headers = {
"X-Amz-Target": "SageMaker.ListActions"
}
response = requests.post(
"https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListActions",
params=params,
headers=headers,
)
print(response.json())const url = new URL('https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListActions');
url.searchParams.set('NextToken', 'example');
url.searchParams.set('MaxResults', 'example');
const response = await fetch(url, {
method: 'POST',
headers: {
'X-Amz-Target': 'SageMaker.ListActions'
},
});
const data = await response.json();
console.log(data);package main
import (
"fmt"
"io"
"net/http"
"net/url"
)
func main() {
baseURL, _ := url.Parse("https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListActions")
q := baseURL.Query()
q.Set("NextToken", "example")
q.Set("MaxResults", "example")
baseURL.RawQuery = q.Encode()
targetURL := baseURL.String()
req, _ := http.NewRequest("POST", targetURL, nil)
req.Header.Set("X-Amz-Target", "SageMaker.ListActions")
client := &http.Client{}
resp, _ := client.Do(req)
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}require "net/http"
require "json"
uri = URI("https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListActions")
uri.query = URI.encode_www_form({
"NextToken" => "example",
"MaxResults" => "example"
})
http = Net::HTTP.new(uri.host, uri.port)
http.use_ssl = uri.scheme == "https"
req = Net::HTTP::Post.new(uri)
req["X-Amz-Target"] = "SageMaker.ListActions"
res = http.request(req)
puts JSON.parse(res.body)<?php
$url = "https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListActions?" . http_build_query([
"NextToken" => "example",
"MaxResults" => "example"
]);
$opts = ["http" => [
"method" => "POST",
"header" => implode("\r\n", [
"X-Amz-Target: SageMaker.ListActions"
]),
]];
$ctx = stream_context_create($opts);
$res = file_get_contents($url, false, $ctx);
print_r(json_decode($res, true));Lists the machine learning algorithms that have been created.
Hover any highlighted part to learn what it does
| X-Amz-Target | SageMaker.ListAlgorithms |
curl -X POST "https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListAlgorithms?NextToken=example&MaxResults=example" \ -H "X-Amz-Target: SageMaker.ListAlgorithms"
import requests
params = {
"NextToken": "example",
"MaxResults": "example"
}
headers = {
"X-Amz-Target": "SageMaker.ListAlgorithms"
}
response = requests.post(
"https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListAlgorithms",
params=params,
headers=headers,
)
print(response.json())const url = new URL('https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListAlgorithms');
url.searchParams.set('NextToken', 'example');
url.searchParams.set('MaxResults', 'example');
const response = await fetch(url, {
method: 'POST',
headers: {
'X-Amz-Target': 'SageMaker.ListAlgorithms'
},
});
const data = await response.json();
console.log(data);package main
import (
"fmt"
"io"
"net/http"
"net/url"
)
func main() {
baseURL, _ := url.Parse("https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListAlgorithms")
q := baseURL.Query()
q.Set("NextToken", "example")
q.Set("MaxResults", "example")
baseURL.RawQuery = q.Encode()
targetURL := baseURL.String()
req, _ := http.NewRequest("POST", targetURL, nil)
req.Header.Set("X-Amz-Target", "SageMaker.ListAlgorithms")
client := &http.Client{}
resp, _ := client.Do(req)
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}require "net/http"
require "json"
uri = URI("https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListAlgorithms")
uri.query = URI.encode_www_form({
"NextToken" => "example",
"MaxResults" => "example"
})
http = Net::HTTP.new(uri.host, uri.port)
http.use_ssl = uri.scheme == "https"
req = Net::HTTP::Post.new(uri)
req["X-Amz-Target"] = "SageMaker.ListAlgorithms"
res = http.request(req)
puts JSON.parse(res.body)<?php
$url = "https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListAlgorithms?" . http_build_query([
"NextToken" => "example",
"MaxResults" => "example"
]);
$opts = ["http" => [
"method" => "POST",
"header" => implode("\r\n", [
"X-Amz-Target: SageMaker.ListAlgorithms"
]),
]];
$ctx = stream_context_create($opts);
$res = file_get_contents($url, false, $ctx);
print_r(json_decode($res, true));Lists the aliases of a specified image or image version.
Hover any highlighted part to learn what it does
| X-Amz-Target | SageMaker.ListAliases |
curl -X POST "https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListAliases?NextToken=example&MaxResults=example" \ -H "X-Amz-Target: SageMaker.ListAliases"
import requests
params = {
"NextToken": "example",
"MaxResults": "example"
}
headers = {
"X-Amz-Target": "SageMaker.ListAliases"
}
response = requests.post(
"https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListAliases",
params=params,
headers=headers,
)
print(response.json())const url = new URL('https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListAliases');
url.searchParams.set('NextToken', 'example');
url.searchParams.set('MaxResults', 'example');
const response = await fetch(url, {
method: 'POST',
headers: {
'X-Amz-Target': 'SageMaker.ListAliases'
},
});
const data = await response.json();
console.log(data);package main
import (
"fmt"
"io"
"net/http"
"net/url"
)
func main() {
baseURL, _ := url.Parse("https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListAliases")
q := baseURL.Query()
q.Set("NextToken", "example")
q.Set("MaxResults", "example")
baseURL.RawQuery = q.Encode()
targetURL := baseURL.String()
req, _ := http.NewRequest("POST", targetURL, nil)
req.Header.Set("X-Amz-Target", "SageMaker.ListAliases")
client := &http.Client{}
resp, _ := client.Do(req)
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}require "net/http"
require "json"
uri = URI("https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListAliases")
uri.query = URI.encode_www_form({
"NextToken" => "example",
"MaxResults" => "example"
})
http = Net::HTTP.new(uri.host, uri.port)
http.use_ssl = uri.scheme == "https"
req = Net::HTTP::Post.new(uri)
req["X-Amz-Target"] = "SageMaker.ListAliases"
res = http.request(req)
puts JSON.parse(res.body)<?php
$url = "https://api.apis.guru/v2/specs/amazonaws.com/sagemaker/2017-07-24/#X-Amz-Target=SageMaker.ListAliases?" . http_build_query([
"NextToken" => "example",
"MaxResults" => "example"
]);
$opts = ["http" => [
"method" => "POST",
"header" => implode("\r\n", [
"X-Amz-Target: SageMaker.ListAliases"
]),
]];
$ctx = stream_context_create($opts);
$res = file_get_contents($url, false, $ctx);
print_r(json_decode($res, true));Postman Setup Guide
- See official documentation for authentication and setup.
What can you build with Amazon SageMaker Service?
Amazon SageMaker Service is a Cloud API. Developers commonly use cloud APIs for:
- provisioning and managing cloud infrastructure
- automating deployments and container orchestration
- monitoring uptime and performance metrics
- managing storage buckets and databases
- setting up auto-scaling and load balancing
No authentication required. This API is open — no signup or key needed. Ideal for quick prototypes and public-facing features. Amazon SageMaker Service is free to use, making it a low-risk choice to experiment with.
New to APIs? Read our beginner's guide