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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

In this post, we explore a practical solution that uses Streamlit , a Python library for building interactive data applications, and AWS services like Amazon Elastic Container Service (Amazon ECS), Amazon Cognito , and the AWS Cloud Development Kit (AWS CDK) to create a user-friendly generative AI application with authentication and deployment.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

It contains services used to onboard, manage, and operate the environment, for example, to onboard and off-board tenants, users, and models, assign quotas to different tenants, and authentication and authorization microservices. You can use AWS services such as Application Load Balancer to implement this approach.

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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

By implementing this architectural pattern, organizations that use Google Workspace can empower their workforce to access groundbreaking AI solutions powered by Amazon Web Services (AWS) and make informed decisions without leaving their collaboration tool. In the following sections, we explain how to deploy this architecture.

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Understanding Microservices Architecture: Benefits and Challenges Explained

Perficient

Understanding Microservices Architecture: Benefits and Challenges Explained Microservices architecture is a transformative approach in backend development that has gained immense popularity in recent years. What is Monolithic Architecture?

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Revolutionizing customer service: MaestroQA’s integration with Amazon Bedrock for actionable insight

AWS Machine Learning - AI

MaestroQA integrated Amazon Bedrock into their existing architecture using Amazon Elastic Container Service (Amazon ECS). The following architecture diagram demonstrates the request flow for AskAI. The customer interaction transcripts are stored in an Amazon Simple Storage Service (Amazon S3) bucket.

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Security Reference Architecture Summary for Cloudera Data Platform

Cloudera

This blog will summarise the security architecture of a CDP Private Cloud Base cluster. The architecture reflects the four pillars of security engineering best practice, Perimeter, Data, Access and Visibility. Configured for authentication, authorization, and auditing. Security Architecture Improvements. Authentication.

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Comparing API Architectural Styles: SOAP vs REST vs GraphQL vs RPC

Altexsoft

These specifications make up the API architecture. Over time, different API architectural styles have been released. A pull of choices raises endless debates as to which architectural style is best. SOAP message-level security: authentication data in the header element and encrypted body. How RPC works. SOAP use cases.