Propose Architecture Methodology for a Retail Inventory Platform

Problem Description

Stockwise is a retail inventory management platform for mid-sized retail chains. It enables warehouse managers to track stock levels across locations, trigger automated purchase orders, and reconcile inventory against point-of-sale data in near real time.

Phase 1 requirements gathering has been completed and accepted. The team now needs to move into Phase 2: selecting an architecture pattern that fits the requirements and team context, establishing the high-level component structure, and agreeing on the technology stack.

Your task is to act as the architecture agent and produce the Phase 2 architecture methodology output, then update the project state to reflect completion of this phase.

Output Specification

Produce the following files:

• .arch/phase2-methodology.md — the architecture methodology document covering the selected pattern, component map, and technology choices
• .arch/state.json — updated to reflect the state after Phase 2 completion

Input Files

The following files are provided as inputs. Extract them before beginning.

=============== FILE: .arch/state.json =============== { "current_phase": "methodology", "phases": { "evaluation": {"status": "accepted"}, "methodology": { "status": "in_progress", "sub_phase": "pattern", "pattern_accepted": false, "components_overview_accepted": false, "cross_cutting_accepted": false }, "components": {"status": "not_started"}, "finalization": {"status": "not_started"} }, "components": [], "decision_count": 8, "reopens": {"count": 0, "max": 2} }

=============== FILE: .arch/phase1-evaluation.md ===============

Phase 1: Requirements Evaluation — Stockwise

Functional Requirements

1. Track stock levels across multiple warehouse locations in real time
2. Generate automated purchase orders when stock falls below configurable reorder thresholds
3. Reconcile inventory against POS data (batch, up to 4× daily)
4. Support barcode scanning for physical stocktake workflows
5. Role-based access: warehouse managers (read/write), buyers (purchase orders only), auditors (read-only)
6. Reporting: stock movement history, purchase order history, discrepancy reports
7. Integration with 3 external ERP systems (SAP, Oracle NetSuite, and a custom in-house system)

Non-Functional Requirements

• Availability: 99.5% uptime during warehouse operating hours (06:00–22:00 local time); planned maintenance window 22:00–02:00
• Performance: Inventory queries must return in under 2 seconds; reconciliation batch jobs may run up to 30 minutes
• Security: Role-based access control; full audit trail for all inventory mutations; data encrypted in transit and at rest
• Cost: Cloud hosting budget capped at $5,000/month
• Monitoring: All reconciliation jobs must emit structured logs; on-call alerting for failed jobs within 5 minutes

Constraints

• Must integrate with 3 existing ERP systems over REST and EDI protocols
• Team: 5 engineers (3 backend, 1 frontend, 1 DevOps)
• Cloud provider: AWS (company mandate)
• Timeline: 9 months to first production deployment

Risks

1. ERP integration complexity — the custom in-house system has poorly documented schemas
2. POS reconciliation volume may spike significantly during peak trading periods
3. Single DevOps engineer limits the team's capacity to operate many independently deployed services