Enterprise Platform with Auth, ML, and Custom RAG

Scenario

A DevOps team uses Terraform to provision MLPS 2.0-compliant infrastructure (VPC, ECS, RDS, OSS, Elasticsearch), layers IDaaS for end-user authentication and PAI for ML model training, then deploys a fully custom RAG system with fine-tuned domain LLM and embedding models—delivering a complete enterprise intelligent search platform with secure user login from infrastructure to inference.

How the products combine

1. alinux · compliant-enterprise-infra-custom-rag-stack-08191c — Compliant Enterprise Infra + Custom RAG Stack

See _combos/compliant-enterprise-infra-custom-rag-stack-08191c.

2. alinux · full-production-stack-with-ssl-and-rag-search-50664b — Full Production Stack with SSL and RAG Search

See _combos/full-production-stack-with-ssl-and-rag-search-50664b.

3. alinux · terraform-enterprise-stack-with-ssl-search-and-c-5ec574 — Terraform Enterprise Stack with SSL, Search, and Compliance

See _combos/terraform-enterprise-stack-with-ssl-search-and-c-5ec574.

4. alinux · compliant-infra-with-ml-search-and-identity-148b67 — Compliant Infra with ML Search and Identity

See _combos/compliant-infra-with-ml-search-and-identity-148b67.

Typical questions

• deploy enterprise platform with auth and custom RAG
• Terraform provision full stack plus IDaaS plus fine-tuned RAG
• 一键部署合规平台加身份认证加自定义大模型RAG
• MLPS 2.0 compliant app with user login and ML search pipeline
• Terraform部署企业平台加用户认证加定制RAG
• full enterprise IaC with identity and custom trained search
• deploy compliant infra then add IDaaS PAI and RAG
• provision secure stack with authentication and fine-tuned RAG

Q: How do I deploy an MLPS 2.0-compliant enterprise platform with authentication and a custom RAG system? A: You can provision this environment by using Terraform to build MLPS 2.0-compliant infrastructure and layer IDaaS for user authentication alongside PAI for machine learning. This workflow automatically sets up core resources like VPC, ECS, RDS, OSS, and Elasticsearch before deploying a fully custom RAG system with fine-tuned domain LLMs and embedding models. The integrated stack delivers a complete enterprise intelligent search platform with secure user login spanning from infrastructure to inference.