proposal-system/docs/adr/0001-bedrock-vector-store-aurora-pgvector.md

# ADR 0001 — Bedrock Knowledge Base vector store: Aurora PostgreSQL + pgvector

- **Status:** Accepted (2026-06-12)
- **Decision owner:** Adam Moussa
- **Scope:** `proposal-system` infrastructure (foundation + compute stacks), v1 PR3

## Context

The proposal system's RAG pipeline uses an Amazon Bedrock Knowledge Base (Titan Embed
v2) over historical proposals. The original vector store was **OpenSearch Serverless
(AOSS)**, which:

- carries a minimum ~2-OCU billing floor (~$175–350/mo) even at near-zero query volume —
  the dominant line item of the monthly bill for an internal tool;
- is VPC-only, which forces the NAT gateway and a `oss-index-creator` bootstrap Lambda
  that exists purely to pre-create the vector index while an IAM access policy propagates.

The database is a small RDS PostgreSQL instance. The v1 assessment flagged AOSS as
over-built for the corpus size and recommended a pgvector store on the existing database.

## Decision

Migrate the database from **RDS PostgreSQL 15 → Aurora PostgreSQL Serverless v2** and use
**pgvector** as the Bedrock KB vector store.

Aurora is required because **Bedrock Knowledge Bases support Aurora PostgreSQL
Serverless v2 (with the RDS Data API) as a pgvector store, but not a plain RDS
instance.** A standard RDS instance cannot back a Bedrock KB, so "pgvector on the
existing RDS" was infeasible without the Aurora move.

Implementation:

- Aurora Serverless v2 (min 0.5 / max 4 ACU), `enableDataApi: true`, `defaultDatabaseName:
  'proposals'`. The cluster also serves the .NET API's application data (one database).
- A bootstrap custom-resource Lambda (`aurora-pgvector-init`, via the RDS Data API)
  enables `vector`, creates the `bedrock_integration.bedrock_kb` table
  (`vector(1024)` for Titan v2 + HNSW cosine + GIN indexes) and a dedicated
  `bedrock_user` role. This **replaces** `oss-index-creator` — the bootstrap is swapped,
  not eliminated.
- `CfnKnowledgeBase.storageConfiguration` → `type: 'RDS'` with `rdsConfiguration`
  (cluster ARN, `bedrock_user` secret, `bedrock_integration.bedrock_kb`, field mapping
  `id`/`embedding`/`chunks`/`metadata`). KB role IAM swaps `aoss:APIAccessAll` →
  scoped `rds-data` + secret read.
- All AOSS constructs (collection, policies, VPC endpoint, index-creator) are deleted.

## Consequences

- **Cost:** eliminates the AOSS OCU floor (~$175–350/mo). Aurora Serverless v2 at
  0.5 ACU min is ~$43/mo and scales toward zero idle — a net reduction.
- **Simplification:** one data engine (Aurora) instead of RDS + AOSS; fewer constructs.
  A bootstrap Lambda remains (now for pgvector schema rather than the AOSS index).
- **NAT:** kept for now — Lambdas and the KB's Data API path still need AWS-service
  egress. Dropping NAT would require VPC interface endpoints; tracked separately.
- **Migration:** the RDS→Aurora swap is a CloudFormation replacement. The deployed stacks
  are **test-only with no production data**, so this is a clean redeploy.

## Alternatives considered

- **Keep AOSS:** rejected — the cost floor is the single biggest waste for the scale.
- **S3 Vectors:** viable Bedrock backend, but Aurora unifies app data + vectors and was
  the owner's preference (also cheaper than AOSS).
- **pgvector on the existing RDS instance:** infeasible — Bedrock KB does not support a
  plain RDS instance as a vector store.

## References

- [Using Aurora PostgreSQL as a Bedrock Knowledge Base](https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/AuroraPostgreSQL.VectorDB.html)
- [Bedrock KB vector-store prerequisites](https://docs.aws.amazon.com/bedrock/latest/userguide/knowledge-base-setup.html)