feat: Production readiness — monitoring, alerting, SLOs, runbooks, data retention, pentest, UAT#3
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…ta retention, pentest, UAT Monitoring & Alerting: - Grafana dashboards: Transfer Operations (14 panels) + Infrastructure (11 panels) - Prometheus alerting: 20 rules across 5 groups (financial, SLA, infra, compliance, settlement) - Alertmanager config: PagerDuty (critical), Opsgenie (warning), Slack (info) - Docker Compose monitoring stack (Prometheus + Grafana + Alertmanager) SLO Definitions: - 12 SLOs: fund delivery 99.9%, API availability 99.95%, ledger integrity 100% - Settlement latency targets per rail (M-Pesa 10s, NIBSS 30s, SEPA 4h, SWIFT 48h) - Error budget policy with escalation levels (25%/50%/75%/100% consumed) Incident Response: - 6 runbooks: ledger imbalance, stuck transfers, rail provider down, slow delivery, low success rate, sanctions screening down - Incident response procedure with severity classification (SEV1-4) - On-call schedule template and communication templates Data Retention: - GDPR/NDPR/POPIA/PDPA compliant retention policy - 8 data categories with specific retention periods and deletion procedures - DSAR implementation (right to access, erasure, portability) - Automated retention jobs (weekly anonymization, monthly archival) QA Additions: - Authenticated penetration test runner (BOLA, privilege escalation, rate limiting) - UAT scenarios for 5 stakeholder journeys (diaspora worker, merchant, employer, DeFi, agent) Co-Authored-By: Patrick Munis <pmunis@gmail.com>
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Summary
Adds the remaining 8 production readiness items: monitoring stack, alerting rules, SLO definitions, incident response runbooks, data retention policy, authenticated penetration testing, and UAT scenarios. 2,506 lines across 21 files.
New structure:
Key design decisions:
QA additions:
qa/security/pentest-authenticated.sh— BOLA, privilege escalation, rate limiting, SSRF, XSS, financial limit bypass testsqa/uat/uat-scenarios.sh— 5 stakeholder journeys (diaspora worker, merchant, employer, DeFi user, agent)Link to Devin session: https://app.devin.ai/sessions/64d054ae77da41e9a2b74d8593fa635c
Requested by: @munisp