Detailed Design & Implementation
Data Design and Migration Strategy
Source of Truth and Ownership
During transition, Hub remains the authoritative source for core transactional domain data. Downstream systems maintain consumer-specific projections built from event notifications and query-driven retrieval.
Data Movement Patterns
- Event notification communicates that a change occurred.
- GraphQL retrieval provides consumer-specific field selection for synchronization.
- REST commands provide controlled write-back into Hub for approved use cases.
Reference flow per domain transaction:
- Domain write is committed in Hub.
- Event is published with identifiers and correlation metadata.
- Consumer receives event and requests a targeted GraphQL projection.
- Consumer stores its projection and records event processing checkpoint.
- Reconciliation jobs periodically compare authoritative and projection state.
Data Integrity Controls
- Idempotent event consumption using event identifiers and deduplication checkpoints.
- Correlation IDs propagated across event, query, and command flows.
- Replay/reconciliation capability for failed or delayed synchronization.
- Validation-on-write in Hub to ensure domain invariants remain enforced.
Migration Approach
- Baseline load: seed consumer stores from current state snapshots.
- Incremental sync: apply event-driven updates post-baseline.
- Reconciliation windows: scheduled consistency checks and automated drift reporting.
- Cutover readiness: objective criteria for each domain before switching system ownership.
Suggested cutover readiness checklist per domain:
| Criterion | Target |
|---|---|
| Baseline load completion | 100% of in-scope entities loaded |
| Event processing reliability | >= 99.9% successful handling over agreed observation window |
| Data drift | 0 critical drift defects and agreed non-critical threshold |
| Operational readiness | Runbooks, alerts, and on-call ownership signed off |
| Rollback readiness | Rollback drill completed successfully |
API and Interface Specifications
Event Contracts
Event envelope should include:
- Event ID, event type, version, and timestamp.
- Aggregate/entity identifier.
- Tenant/context metadata.
- Correlation and causation identifiers.
Event payload should remain compact and stable, providing enough information for consumers to fetch enriched data as required.
Example event envelope:
{
"eventId": "7f3e5f6b-95b8-4f90-9d30-0f54af0b2a17",
"eventType": "Hub.CustomerUpdated.v1",
"occurredAtUtc": "2026-04-22T09:15:00Z",
"tenantId": "tenant-a",
"aggregateType": "Customer",
"aggregateId": "C12345",
"correlationId": "c4f0b3aa-0bde-4e6b-9f0e-8936a4f63f89",
"causationId": "9b6f5c5a-5f3a-4511-b2c9-c3c7d1c47ab8",
"payload": {
"changedFields": ["email", "status"],
"version": 18
}
}GraphQL Query Surface
Design goals:
- Consumer-selected fields to avoid over-fetching.
- Query authorization by role and tenant scope.
- Schema evolution with backward-compatible deprecations.
- Pagination and filtering for high-volume domains.
Example consumer query:
query CustomerSyncProjection($id: ID!) {
customer(id: $id) {
id
status
email
updatedAtUtc
billingProfile {
tier
isActive
}
}
}REST Command Surface
Design goals:
- Explicit resource and command semantics for create/update/delete operations.
- Standardized error contract and validation response model.
- Idempotency support where retry behavior is expected.
- Contract versioning strategy with deprecation windows.
Example command request:
PATCH /api/customers/C12345
Authorization: Bearer <token>
Idempotency-Key: 536f0ef5-b95e-4a2f-8d8b-f4f10d7aa2d6
Content-Type: application/json
{
"status": "Active",
"email": "new.email@example.com"
}
Standard error payload shape:
{
"code": "ValidationFailed",
"message": "Request contains invalid fields.",
"correlationId": "c4f0b3aa-0bde-4e6b-9f0e-8936a4f63f89",
"errors": [
{
"field": "email",
"reason": "InvalidFormat"
}
]
}Security and Compliance Controls
Identity and Access
- Modern authentication for all integration clients.
- Role- and scope-based authorization for query and command endpoints.
- Principle of least privilege for service identities.
Data Protection
- Encryption in transit for all APIs and event transport channels.
- Encryption at rest for persisted operational and projection data.
- Controlled handling of sensitive data in logs and telemetry.
Audit and Traceability
- Immutable audit trail for command operations.
- Event lineage traceability from producer through consumers.
- End-to-end request tracing with correlation IDs.
Compliance Readiness
- Retention and deletion controls aligned with policy requirements.
- Data minimization in event payloads and API responses.
- Security review gates before production rollout milestones.
Implementation Sequence
- Establish cross-cutting foundations (identity, telemetry, correlation, contract governance).
- Introduce event publication for selected low-risk domains.
- Deliver GraphQL read models for consumer pull integration.
- Expose modernized REST command endpoints for controlled write-back.
- Expand domain coverage iteratively with domain-specific cutover criteria.
- Decommission legacy integration pathways as replacement coverage reaches target thresholds.
Delivery governance at each step should include:
- Architecture sign-off for contract and compatibility implications.
- Security sign-off for identity, authorization, and data handling controls.
- Operations sign-off for monitoring, alerting, and rollback coverage.
Acceptance Criteria
The implementation is considered complete when all of the following are true:
- Critical domain events are published with required metadata and schema validation.
- Consumer sync projections are demonstrably current within agreed freshness SLO.
- Command API contracts pass functional, security, and backward-compatibility tests.
- Reconciliation jobs report no unresolved critical drift defects.
- Production runbooks, dashboards, and alert routes are validated in drills.
Non-Functional Expectations
- Reliability: graceful degradation and retry-safe integration patterns.
- Performance: bounded latency for event-to-consumer synchronization.
- Scalability: horizontal scale for query and event consumer workloads.
- Supportability: operational dashboards and alerts aligned to SLOs.