A DevOps team first uses Terraform to provision a complete MLPS 2.0-hardened production infrastructure (VPC, ECS cluster, OSS, RDS, SLB with CAS-managed HTTPS certificates), then executes a database migration pipeline that imports on-premises backups through OSS into RDS as a staging layer, fans out to OceanBase for distributed OLTP, and layers Elasticsearch on top to power a RAG-based semantic search application — all running on the Terraform-managed compliant foundation.
A DevOps team first uses Terraform to provision a complete MLPS 2.0-hardened production infrastructure (VPC, ECS cluster, OSS, RDS, SLB with CAS-managed HTTPS certificates), then executes a database migration pipeline that imports on-premises backups through OSS into RDS as a staging layer, fans out to OceanBase for distributed OLTP, and layers Elasticsearch on top to power a RAG-based semantic search application — all running on the Terraform-managed compliant foundation.
See _combos/on-prem-db-migration-to-full-stack-search-applic-25dd1c.
See _combos/on-prem-db-to-oceanbase-and-elasticsearch-87de98.
See _combos/full-production-stack-with-ssl-and-rag-search-50664b.
See _combos/secure-app-with-structured-and-semantic-search-469afa.
Q: How do I deploy a Terraform-managed production stack and migrate an on-premises database with RAG-based semantic search? A: You can accomplish this by using Terraform to provision an MLPS 2.0-hardened infrastructure and then executing a migration pipeline that imports on-premises backups into RDS, fans out to OceanBase, and layers Elasticsearch to power a RAG-based semantic search application. The Terraform-managed foundation automatically provisions the required VPC, ECS cluster, OSS, RDS, and SLB with CAS-managed HTTPS certificates. This compliant setup seamlessly bridges initial infrastructure deployment with a fully operational search system.