docs: add ADR 0005 for Glow-to-NLDS warehouse connector#602
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Research spike recommending an S3 data-lake intermediary (bucket sited in the NLDS account) to connect Glow learning data to the NLDS warehouse. Evaluates five options — S3 intermediary, DB replica via PrivateLink, DB replica via VPC peering, AWS DMS, and RDS snapshot export — across cost, security, freshness, and operational effort, with explicit rejection reasons for the non-chosen approaches. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Clarify that the chosen S3 data-lake intermediary can carry a whole-database export as readily as curated slices, making it a superset of the rejected snapshot-export option; curated-only exposure is a deliberate governance choice, not a technical limit of the pattern. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…n requirement Glow's learning data is not sensitive and NLDS decides how to use it, so there is no requirement to curate what is sent — the connector exports the whole database via an RDS snapshot export to the S3 intermediary. Drop the stage/refinement framing; curation becomes an optional future re-exploration within the same architecture. Batch freshness is daily (hourly removed). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
santosral
approved these changes
Jul 3, 2026
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🚀 Summary
Resolves #597 — a research spike (no implementation) producing a documented, recommended approach for connecting Glow learning data to the NLDS data warehouse for centralized analytics and reporting.
The ADR (
docs/decisions/0005-glow-nlds-warehouse-connector.md, MADR 4.0, statusaccepted) recommends an S3 data-lake intermediary with RDS snapshot export as the producer: Glow's database exports whole-database snapshots to S3 as Parquet (no export code), landing cross-account in a scoped prefix of a bucket sited in the NLDS account; NLDS ingests natively within its own account on its own schedule.There is no requirement to curate what is sent — Glow's learning data is not sensitive and NLDS decides how to use it — so the connector exports the whole database. Curating to specific datasets can be re-explored later; because that would only swap the producer within the same S3 pattern, it would stay within this decision rather than supersede it.
Decision rests on the established constraints: batch freshness is acceptable (no near-real-time need), Glow and NLDS are separate AWS accounts in the same AWS Organization, and no policy mandates a particular network posture.
✏️ Changes
docs/decisions/0005-glow-nlds-warehouse-connector.md— evaluates five options across the rubric dimensions (cost, security, freshness/latency, implementation/operational effort, coupling):bucket-owner-enforcedto avoid the cross-account object-ownership trap), a Mermaid data-flow diagram, and a deferred-patterns note (federated query, streaming CDC, app-level extract API).docs/decisions/README.md.Notes
accepted— signed off by the Glow engineering and NLDS Product Ops reps.🤖 Generated with Claude Code