Remove Accountability Remove APIs Remove Management
article thumbnail

Implement secure API access to your Amazon Q Business applications with IAM federation user access management

AWS Machine Learning

AWS recommends using AWS IAM Identity Center when you have a large number of users in order to achieve a seamless user access management experience for multiple Amazon Q Business applications across many AWS accounts in AWS Organizations. illustrate how the administrators can automate Steps 2 and 3 using AWS APIs.

APIs 79
article thumbnail

Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning

In this post, we guide you through integrating Amazon Bedrock Agents with enterprise data APIs to create more personalized and effective customer support experiences. An automotive retailer might use inventory management APIs to track stock levels and catalog APIs for vehicle compatibility and specifications.

APIs 128
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Streamline workflow orchestration of a system of enterprise APIs using chaining with Amazon Bedrock Agents

AWS Machine Learning

Intricate workflows that require dynamic and complex API orchestration can often be complex to manage. Using natural language processing (NLP) and OpenAPI specs, Amazon Bedrock Agents dynamically manages API sequences, minimizing dependency management complexities.

APIs 132
article thumbnail

Track, allocate, and manage your generative AI cost and usage with Amazon Bedrock

AWS Machine Learning

As enterprises increasingly embrace generative AI , they face challenges in managing the associated costs. This limitation has added complexity to cost management for generative AI initiatives. anthropic.claude-3-sonnet-20240229-v1:0", "inferenceProfileId": "us-1.anthropic.claude-3-sonnet-20240229-v1:0",

APIs 134
article thumbnail

Secure Amazon SageMaker Studio presigned URLs Part 3: Multi-account private API access to Studio

AWS Machine Learning

One important aspect of this foundation is to organize their AWS environment following a multi-account strategy. In this post, we show how you can extend that architecture to multiple accounts to support multiple LOBs. In this post, we show how you can extend that architecture to multiple accounts to support multiple LOBs.

APIs 82
article thumbnail

Use the ApplyGuardrail API with long-context inputs and streaming outputs in Amazon Bedrock

AWS Machine Learning

The new ApplyGuardrail API enables you to assess any text using your preconfigured guardrails in Amazon Bedrock, without invoking the FMs. In this post, we demonstrate how to use the ApplyGuardrail API with long-context inputs and streaming outputs. For example, you can now use the API with models hosted on Amazon SageMaker.

APIs 125
article thumbnail

Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments

AWS Machine Learning

For a multi-account environment, you can track costs at an AWS account level to associate expenses. A combination of an AWS account and tags provides the best results. Implementing a cost allocation strategy early is critical for managing your expenses and future optimization activities that will reduce your spend.