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

AWS Machine Learning - AI

Traditionally, building frontend and backend applications has required knowledge of web development frameworks and infrastructure management, which can be daunting for those with expertise primarily in data science and machine learning.

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Can we trust Google Cloud Load Balancing?

Xebia

With Cloud getting a more prominent place in the digital world and with that Cloud Service Providers (CSP), it triggered the question on how secure our data with Google Cloud actually is when looking at their Cloud Load Balancing offering. Applicability may be inferred to other CSP’s as well, but is not validated.

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

AWS Machine Learning - AI

The workflow includes the following steps: The process begins when a user sends a message through Google Chat, either in a direct message or in a chat space where the application is installed. After it’s authenticated, the request is forwarded to another Lambda function that contains our core application logic.

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Cloud Load Balancing- Facilitating Performance & Efficiency of Cloud Resources

RapidValue

Cloud load balancing is the process of distributing workloads and computing resources within a cloud environment. Cloud load balancing also involves hosting the distribution of workload traffic within the internet. Cloud load balancing also involves hosting the distribution of workload traffic within the internet.

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VM-Series Virtual Firewalls Integrate With AWS Gateway Load Balancer

Palo Alto Networks

The just-announced general availability of the integration between VM-Series virtual firewalls and the new AWS Gateway Load Balancer (GWLB) introduces customers to massive security scaling and performance acceleration – while bypassing the awkward complexities traditionally associated with inserting virtual appliances in public cloud environments.

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One Year of Load Balancing

Algolia

From the beginning at Algolia, we decided not to place any load balancing infrastructure between our users and our search API servers. An Algolia application runs on top of the following infrastructure components: a cluster of 3 servers which process both indexing and search queries, some DSNs servers (not DNS).

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

AWS Machine Learning - AI

AWS Trainium and AWS Inferentia based instances, combined with Amazon Elastic Kubernetes Service (Amazon EKS), provide a performant and low cost framework to run LLMs efficiently in a containerized environment. We also demonstrate how to test the solution and monitor performance, and discuss options for scaling and multi-tenancy.

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