A DevOps team first provisions a full MLPS 2.0-compliant enterprise infrastructure (VPC, ECS with auto-scaling, RDS, OSS, SLB with SSL via CAS, Alinux hardening) using Terraform, then extends it with IDaaS for end-user authentication and PAI/Bailian-powered RAG for intelligent document search — delivering a production-ready, regulation-compliant AI-augmented application platform in one workflow.
A DevOps team first provisions a full MLPS 2.0-compliant enterprise infrastructure (VPC, ECS with auto-scaling, RDS, OSS, SLB with SSL via CAS, Alinux hardening) using Terraform, then extends it with IDaaS for end-user authentication and PAI/Bailian-powered RAG for intelligent document search — delivering a production-ready, regulation-compliant AI-augmented application platform in one workflow.
See _combos/terraform-enterprise-auto-scaling-production-sta-bb4815.
See _combos/terraform-enterprise-stack-with-mlps-compliance-1f6a9e.
See _combos/terraform-production-web-stack-with-database-and-3e2c50.
See _combos/ssl-secured-platform-with-dual-layer-security-an-2e08e0.
Q: How do I deploy an MLPS-compliant platform with identity and RAG search? A: The platform is provisioned as a cross-product combination spanning Terraform, IDaaS, PAI, Bailian, OpenSearch, ECS, OSS, RDS, and associated infrastructure services. This integrated stack provides the required architecture for MLPS compliance, identity authentication, and RAG search capabilities.