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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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Deploy Meta Llama 3.1-8B on AWS Inferentia using Amazon EKS and vLLM

AWS Machine Learning - AI

Before running the following commands, make sure you authenticate towards AWS : export AWS_REGION=us-east-1 export CLUSTER_NAME=my-cluster export EKS_VERSION=1.30 Before running the following commands, make sure you authenticate towards AWS : export AWS_REGION=us-east-1 export CLUSTER_NAME=my-cluster export EKS_VERSION=1.30

AWS 103
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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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Build a custom UI for Amazon Q Business

AWS Machine Learning - AI

The workflow includes the following steps: The user accesses the chatbot application, which is hosted behind an Application Load Balancer. After the user logs in, they’re redirected to the Amazon Cognito login page for authentication. Additionally, it creates and configures those services to run the end-to-end demonstration.

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SaaS Platfrom Development – How to Start

Existek

The global SaaS market is surging forward due to increasing benefits and is expected to reach a volume of $793bn by 2029. It’s never been only about technically solid products, as every business also looks for solutions that customers need and use. The main goal is to tailor your future product to users’ demands.

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Why you must extend Zero Trust to public cloud workloads

CIO

Due to the current economic circumstances security teams operate under budget constraints. With Zscaler Workload Communications, organizations can effortlessly shift from traditional perimeter-based approaches to a zero-trust framework and establish granular control, strong authentication, and continuous monitoring. Operational costs.

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AWS vs. Azure vs. Google Cloud: Comparing Cloud Platforms

Kaseya

The public cloud infrastructure is heavily based on virtualization technologies to provide efficient, scalable computing power and storage. In addition, you can also take advantage of the reliability of multiple cloud data centers as well as responsive and customizable load balancing that evolves with your changing demands.