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Layer 4 of 20
Data Fabric
Data models and persistence across stores: consistency strategy, partitioning/sharding, caching layers, and data lifecycle controls.
Responsibilities
- Define the data model boundaries and consistency strategy.
- Provide storage patterns (OLTP/OLAP/cache/search) with clear ownership.
- Control retention, privacy, and lifecycle policies.
Key interfaces
- Data access contracts (repositories, query APIs, schema versioning).
- Caching and invalidation mechanisms.
- Migration and backfill workflows with rollback strategy.
Operational signals
These are the measurements that tell you whether this layer is healthy in production.
- Read/write latency, lock contention, and connection pool saturation.
- Replication lag, queue/backlog size (if streaming).
- Cache hit rate and eviction churn.
Failure modes
- Hot partitions / uneven load distribution.
- Schema drift and broken migrations.
- Data leaks via over-broad access or missing redaction.
Production readiness checklist
- Define SLOs per datastore and enforce backpressure.
- Test migrations in shadow environments; keep rollbacks ready.
- Implement data classification and least-privilege access controls.