Remove Architecture Remove Load Balancer Remove Scalability
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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

The solution we explore consists of two main components: a Python application for the UI and an AWS deployment architecture for hosting and serving the application securely. The AWS deployment architecture makes sure the Python application is hosted and accessible from the internet to authenticated users. See the README.md

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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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What is the Difference between Network Architecture and Application Architecture?

The Crazy Programmer

When you are planning to build your network, there is a possibility you may come across two terms “Network Architecture and Application Architecture.” In today’s blog, we will look at the difference between network architecture and application architecture in complete detail.

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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? This flexibility allows for efficient resource management and cost savings.

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

AWS Machine Learning - AI

Amazon Bedrocks broad choice of FMs from leading AI companies, along with its scalability and security features, made it an ideal solution for MaestroQA. MaestroQA integrated Amazon Bedrock into their existing architecture using Amazon Elastic Container Service (Amazon ECS).

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Ngrok, a service to help devs deploy sites, services and apps, raises $50M

TechCrunch

Effectively, Ngrok adds connectivity, security and observability features to existing apps without requiring any code changes, including features like load balancing and encryption. A developer can deliver their app to users in a secure and scalable manner with one click or a single line of code.”

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