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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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Why you must extend Zero Trust to public cloud workloads

CIO

Today, many organizations are embracing the power of the public cloud by shifting their workloads to them. A recent study shows that 98% of IT leaders 1 have adopted a public cloud infrastructure. It is estimated by the end of 2023, 31% of organizations expect to run 75% of their workloads 2 in the cloud. 8 Complexity.

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AI-Driven API and Microservice Architecture Design for Cloud

Dzone - DevOps

Incorporating AI into API and microservice architecture design for the Cloud can bring numerous benefits. Dynamic load balancing : AI algorithms can dynamically balance incoming requests across multiple microservices based on real-time traffic patterns, optimizing performance and reliability.

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

AWS Machine Learning - AI

Load balancer – Another option is to use a load balancer that exposes an HTTPS endpoint and routes the request to the orchestrator. You can use AWS services such as Application Load Balancer to implement this approach. As a result, building such a solution is often a significant undertaking for IT teams.

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Building Resilient Public Networking on AWS: Part 4

Xebia

It provides Infrastructure as Code (IaC) using AWS Cloud Development Kit (CDK), allowing you to deploy and manage the necessary infrastructure effortlessly. Architecture Overview The accompanying diagram visually represents our infrastructure’s architecture, highlighting the relationships between key components.

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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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Microservices Architectural Design by using Spring Boot

Perficient

What is Microservices Architecture? Microservices Architecture Software development follows an architectural and organizational approach where small independent services communicate with each other through well-defined APIs. with DevOps tools like Jenkins with CI/CD, Docker, Ansible, Kubernetes, or other tools.