Agentic-AI-and-GeN-AI-Cloud-Stack-AWS-GCP-Azure and LLMOps-and-AIOps-Work

These are ecosystem siblings—both are educational repositories by the same author demonstrating overlapping agentic AI frameworks (LangChain, LangGraph, RAG) with one focused on cloud architecture patterns (A) and the other emphasizing operational deployment and monitoring infrastructure (B).

Agentic-AI-and-GeN-AI-Cloud-Stack-AWS-GCP-Azure
32
Emerging
LLMOps-and-AIOps-Work
25
Experimental
Maintenance 10/25
Adoption 1/25
Maturity 9/25
Community 12/25
Maintenance 13/25
Adoption 3/25
Maturity 9/25
Community 0/25
Stars: 1
Forks: 1
Downloads: —
Commits (30d): 0
Language: —
License: MIT
Stars: 4
Forks: —
Downloads: —
Commits (30d): 0
Language: —
License: MIT
No Package No Dependents
No Package No Dependents

About Agentic-AI-and-GeN-AI-Cloud-Stack-AWS-GCP-Azure

Ratnesh-181998/Agentic-AI-and-GeN-AI-Cloud-Stack-AWS-GCP-Azure

Agentic AI and Generative AI implementations using LangChain, LangGraph, CrewAI, AutoGen, and advanced RAG architectures. Includes LLM orchestration, multi-agent workflows, vector databases, CI/CD pipelines, observability, and cloud-native deployment on AWS , Azure and GCP.

About LLMOps-and-AIOps-Work

Ratnesh-181998/LLMOps-and-AIOps-Work

Agenetic AI & GenAI (Groq, Mistral, LangChain, LangGraph, RAG, Vector DBs), Cloud (GCP, AWS, Kubernetes, GKE, ECS Fargate), DevOps/LLMOps (Docker, Jenkins, GitOps, ArgoCD, Prometheus, Grafana, ELK Stack), CI/CD, Security, and Observability.

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Agentic-AI-and-GeN-AI-Cloud-Stack-AWS-GCP-Azure and AI-Engineer

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