AWS SageMaker

Sagemaker allows users to host any ML model on their own AWS infrastructure. With Obiguard you can manage/restrict access, log requests, and more.

Provider Slug. sagemaker

Obiguard SDK Integration with AWS Sagemaker

1. Install the Obiguard SDK

Add the Obiguard SDK to your application to interact with Sagemaker’s API through Obiguard’s gateway.

Python SDK

pip install obiguard

2. Initialize Obiguard with a Virtual Key

There are multiple ways to integrate Sagemaker with Obiguard. You can use your AWS credentials, or use an assumed role. In this example we will create a virtual key and use it to interact with Sagemaker. This helps you restrict access (specific models, few endpoints, etc).

Here’s how to find your AWS credentials:

AWS Access Key

Use your AWS Secret Access Key, AWS Access Key Id, and AWS Region to create your Virtual key.

Integration Guide

AWS Assumed Role

Take your AWS Assumed Role ARN and AWS Region to create the virtual key.

Create a virtual key in the Obiguard dashboard in the virtual keys section. You can select sagemaker as the provider, and fill in deployment details. Initialize the Obiguard SDK with the virtual key. (If you are using the REST API, skip to next step)

Python SDK

from obiguard import Obiguard

client = Obiguard(
  obiguard_api_key="sk-obg***", # Your Obiguard API key
  virtual_key="VIRTUAL_KEY" # Replace with your Sagemaker Virtual Key
)

3. Invoke the Sagemaker model

Python SDK
REST API

response = client.post(
  url="endpoints/{endpoint_name}/invocations",
  # You can pass any key value pair required by the model, apart from `url`, they are passed as kwargs to the Sagemaker endpoint
  inputs="my_custom_value",
  my_custom_key="my_custom_value",
)

print(response)

curl --location 'https://gateway.obiguard.ai/v1/endpoints/{endpoint_name}/invocations' \
  --header 'x-obiguard-virtual-key: {VIRTUAL_KEY}' \
  --header 'x-obiguard-api-key: {OBIGUARD_API_KEY}' \
  --header 'Content-Type: application/json' \
  --data '{
    # You can pass any key value pair required by the model, they are passed as kwargs to the Sagemaker endpoint
    "inputs": "my_custom_value",
    "my_custom_key": "my_custom_value"
  }'

Making Requests without Virtual Keys

If you do not want to add your AWS details to Obiguard vault, you can also directly pass them while instantiating the Obiguard client. These are the supported headers/parameters for Sagemaker (Not required if you’re using a virtual key):

Node SDK	Python SDK	REST Headers
awsAccessKeyId	aws_access_key_id	x-obiguard-aws-access-key-id
awsSecretAccessKey	aws_secret_access_key	x-obiguard-aws-secret-access-key
awsRegion	aws_region	x-obiguard-aws-region
awsSessionToken	aws_session_token	x-obiguard-aws-session-token
sagemakerCustomAttributes	sagemaker_custom_attributes	x-obiguard-amzn-sagemaker-custom-attributes
sagemakerTargetModel	sagemaker_target_model	x-obiguard-amzn-sagemaker-target-model
sagemakerTargetVariant	sagemaker_target_variant	x-obiguard-amzn-sagemaker-target-variant
sagemakerTargetContainerHostname	sagemaker_target_container_hostname	x-obiguard-amzn-sagemaker-target-container-hostname
sagemakerInferenceId	sagemaker_inference_id	x-obiguard-amzn-sagemaker-inference-id
sagemakerEnableExplanations	sagemaker_enable_explanations	x-obiguard-amzn-sagemaker-enable-explanations
sagemakerInferenceComponent	sagemaker_inference_component	x-obiguard-amzn-sagemaker-inference-component
sagemakerSessionId	sagemaker_session_id	x-obiguard-amzn-sagemaker-session-id
sagemakerModelName	sagemaker_model_name	x-obiguard-amzn-sagemaker-model-name

Example

Python SDK
cURL

from obiguard import Obiguard

client = Obiguard(
  obiguard_api_key="sk-obg***", # Your Obiguard API key
  provider="sagemaker",
  aws_region="us-east-1", # Replace with your AWS region
  aws_access_key_id="AWS_ACCESS_KEY_ID", # Replace with your AWS access key id
  aws_secret_access_key="AWS_SECRET_ACCESS_KEY", # Replace with your AWS secret access key
  amzn_sagemaker_inference_component="SAGEMAKER_INFERENCE_COMPONENT" # Replace with your Sagemaker inference component
)

response = client.post(
  url="endpoints/{endpoint_name}/invocations",
  # You can pass any key value pair required by the model, apart from `url`, they are passed as kwargs to the Sagemaker endpoint
  inputs="my_custom_value",
  my_custom_key="my_custom_value"
)

print(response)

curl "https://gateway.obiguard.ai/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "x-obiguard-api-key: $OBIGUARD_API_KEY" \
  -H "x-obiguard-provider: sagemaker" \
  -H "x-obiguard-aws-access-key-id: $AWS_ACCESS_KEY_ID" \
  -H "x-obiguard-aws-secret-access-key: $AWS_SECRET_ACCESS_KEY" \
  -H "x-obiguard-aws-region: $AWS_REGION" \
  -H "x-obiguard-amzn-sagemaker-inference-component: $SAGEMAKER_INFERENCE_COMPONENT" \
  -d '{
    # You can pass any key value pair apart from `url` required by the model, they are passed as kwargs to the Sagemaker endpoint
    "inputs": "my_custom_value",
    "my_custom_key": "my_custom_value"
  }'

Next Steps

The complete list of features supported in the SDK are available on the link below.

Ecosystem

AI Apps

Agents

LLMs

Vector Databases

Obiguard SDK Integration with AWS Sagemaker

1. Install the Obiguard SDK

2. Initialize Obiguard with a Virtual Key

AWS Access Key

AWS Assumed Role

3. Invoke the Sagemaker model

Making Requests without Virtual Keys

Example

Next Steps

SDK

​Obiguard SDK Integration with AWS Sagemaker

​1. Install the Obiguard SDK

​2. Initialize Obiguard with a Virtual Key

AWS Access Key

AWS Assumed Role

​3. Invoke the Sagemaker model

​Making Requests without Virtual Keys

​Example

​Next Steps

SDK

Obiguard SDK Integration with AWS Sagemaker

1. Install the Obiguard SDK

2. Initialize Obiguard with a Virtual Key

3. Invoke the Sagemaker model

Making Requests without Virtual Keys

Example

Next Steps