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

AWS Machine Learning - AI

The custom header value is a security token that CloudFront uses to authenticate on the load balancer. By using Streamlit and AWS services, data scientists can focus on their core expertise while still delivering secure, scalable, and accessible applications to business users. Choose a different stack name for each application.

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

AWS Machine Learning - AI

API Gateway is serverless and hence automatically scales with traffic. 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.

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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning - AI

That’s where the new Amazon EMR Serverless application integration in Amazon SageMaker Studio can help. In this post, we demonstrate how to leverage the new EMR Serverless integration with SageMaker Studio to streamline your data processing and machine learning workflows.

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

TechCrunch

An open source package that grew into a distributed platform, Ngrok aims to collapse various networking technologies into a unified layer, letting developers deliver apps the same way regardless of whether they’re deployed to the public cloud, serverless platforms, their own data center or internet of things devices.

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How to Deploy Tomcat App using AWS ECS Fargate with Load Balancer

Perficient

Amazon Elastic Container Service (ECS): It is a highly scalable, high-performance container management service that supports Docker containers and allows to run applications easily on a managed cluster of Amazon EC2 instances. Before that let’s create a load balancer by performing the following steps.

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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. Customers can select the model that best aligns with their specific use case, finding the right balance between performance and price.

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Responsible AI in action: How Data Reply red teaming supports generative AI safety on AWS

AWS Machine Learning - AI

This UI directs traffic through an Application Load Balancer (ALB), facilitating seamless user interactions and allowing red team members to explore, interact, and stress-test models in real time. Amine is passionate about GenAI, serverless architectures, and helping organizations unlock business value through modern data platforms.