Azure AI Agent Awesome List Curator

Azure-based multi-agent system that discovers, validates, and publishes new Nemotron resources daily. Uses scheduled aut...

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Azure AI Agent Awesome List Curator

Azure-based multi-agent system that discovers, validates, and publishes new Nemotron resources daily. Uses scheduled automation, containers, search, and AI services to maintain an awesome list.

advanced
AZURE

Tags

#azure
#ai-agents
#containerized
#automation
#content-curation

Architecture Description

Using Azure, Build an AI agent that maintains its own awesome list using the very model it's curating. Here’s how the auto-curator works: → 4 specialized agents: discoverer, validator, publisher, & a root coordinator ~ powered with Docker Agent → Runs every morning at 9am via GHA → Searches the web, HuggingFace, arXiv, GitHub for new Nemotron content → Validates every link

Creator Notes(2)

A correction. This architecture doesn't use Docker Agent. It uses Azure Container Instances. Azure Container instances doesn't use docker agent, it can use docker images. I created the architecture in the platform so people can explore different cloud implementations of the same design.

2 days ago

This is based on Ajeet Singh Raina's X post but instead it uses Azure. His version of it uses No Python and No node.js. It's posted here: https://x.com/ajeetsraina/status/2031946037305491656?s=46&t=G2z8HbM5QkwtwFHdjJXcmw

3 days ago

Community Reviews(1)

AI Review
Tradeoff

2 days ago

I appreciate the comprehensive approach with multiple agents and services in your architecture. However, a significant concern is the reliance on Azure Functions for orchestrating the workflow. While they provide flexibility and scalability, they can introduce cold start issues, especially if the functions are not invoked frequently. This could lead to delays in the morning runs, impacting the timely update of the curated list. Additionally, I notice multiple Azure Container Instances (ACI) for each agent, which might complicate debugging and monitoring. Consider consolidating some functions or using Azure Kubernetes Service to enhance manageability and performance. Overall, ensuring that latency is minimized will be crucial for production reliability.

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Creator

Kevin Brown

Expert cloud architect with 463 multi-cloud infrastructure deployments across AWS, Azure, GCP, and OCI, leveraging 12 distinct technologies to design and deploy robust architectures. Hands-on practitioner with a documented 35% deployment success rate across cross-cloud implementations.

Details

Category
ml platform

Estimated monthly cost

$565.75/month

Published
3/12/2026

Services Used

20 cloud services in this architecture

AzureNSG
ApplicationGateway
AzureVM
AzureContainerRegistry
AzureContainerInstances
AzureFunction
AzureLogicApps
AzureOpenAIService
AzureAISearch
StorageAccount
CosmosDB
SQLServer
RedisCache
AzureAPIManagement
AzureServiceBus
AzureEventGrid
SecurityCenter
Sentinel
ActivityLog
AzureMonitor

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