Remove Architecture Remove Authentication Remove Lambda Remove Scalability
article thumbnail

CBRE and AWS perform natural language queries of structured data using Amazon Bedrock

AWS Machine Learning - AI

In this post, we describe how CBRE partnered with AWS Prototyping to develop a custom query environment allowing natural language query (NLQ) prompts by using Amazon Bedrock, AWS Lambda , Amazon Relational Database Service (Amazon RDS), and Amazon OpenSearch Service. A Lambda function with business logic invokes the primary Lambda function.

AWS 93
article thumbnail

Accenture creates a regulatory document authoring solution using AWS generative AI services

AWS Machine Learning - AI

The following diagram illustrates the solution architecture. The React application uses the Amplify authentication library to detect whether the user is authenticated. The React application uses the Amplify authentication library to detect whether the user is authenticated. The response data is stored in DynamoDB.

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

Build scalable Low-Code backends with Booster

The Agile Monkey

However, these tools may not be suitable for more complex data or situations requiring scalability and robust business logic. In short, Booster is a Low-Code TypeScript framework that allows you to quickly and easily create a backend application in the cloud that is highly efficient, scalable, and reliable. protocol for authentication.

article thumbnail

Automate the process to change image backgrounds using Amazon Bedrock and AWS Step Functions

AWS Machine Learning - AI

The following diagram provides a simplified view of the solution architecture and highlights the key elements. The DynamoDB update triggers an AWS Lambda function, which starts a Step Functions workflow. The Step Functions workflow invokes a Lambda function to generate a status report.

AWS 112
article thumbnail

Build an internal SaaS service with cost and usage tracking for foundation models on Amazon Bedrock

AWS Machine Learning - AI

API gateways can provide loose coupling between model consumers and the model endpoint service, and flexibility to adapt to changing model, architectures, and invocation methods. In this post, we show you how to build an internal SaaS layer to access foundation models with Amazon Bedrock in a multi-tenant (team) architecture.

Lambda 123
article thumbnail

Automatically scale self-hosted runners in AWS to meet demand

CircleCI

Self-hosted runners allow you to host your own scalable execution environments in your private cloud or on-premises, giving you more flexibility to customize and control your CI/CD infrastructure. Once you have created the resource class, take note of the authentication token generated for it. It will not be shown again.

AWS 98
article thumbnail

Understanding Multi-tenancy, the Keystone of SaaS

CloudGeometry

Behind the curtain, selling essentially the same software to different users and companies, again and again, relies on a distinct product architecture: secure multi-tenancy. Tenant isolation is the keystone of the SaaS architecture, holding it all together and keeping it up and running. Let’s take a closer look.