I. Unitized Architecture and Horizontal Scalability
Multi-Data Center Deployment: Adopts unitized technology to deploy functionally consistent application units across multiple IDCs. Each unit processes a customer-dimensioned data shard. With global routing coordination, the system enables “data-center-level” horizontal scalability to support growth to tens of millions of customers.
Elastic Expansion Mechanism: Implements data sharding using a Consistent Hash algorithm. Adding a new unit requires migrating only part of the data, shortening the expansion cycle and reducing the risk of business interruption.
II. Customer Data Consolidation and Standardization
Data Governance and Modeling: Consolidates fragmented customer data across the bank, establishes unified data standards and models, and normalizes fields such as ID type and mobile number to eliminate data silos.
Standardized Service Publication: Encapsulates customer information into standardized services such as query, update, and authentication for consumption by various business systems, ensuring consistent data usage.
III. Unified Customer Identification and Intelligent Routing
Multi-Dimensional Identification: Supports multiple identification methods, including customer ID, three-factor ID verification, and mobile number. Utilizes Redis for data storage to achieve millisecond-level response times.
Global Routing: Based on identification results combined with Consistent Hash algorithms, the system automatically locates the customer’s corresponding unit and routes requests accurately, reducing cross-center calls and improving efficiency.
IV. Cross-Unit Transactions and Data Consistency
Distributed Transaction Processing: For cross-unit operations such as customer consolidation, the system adopts an “eventual consistency” strategy, ensuring data integrity through idempotent design and service retries.
Data Synchronization Mechanism: Supports Redis cross-IDC strong synchronization (RPO = 0) or asynchronous replication (RPO < a few seconds) to ensure consistency between routing identification data and business data.
V. High-Reliability Disaster Recovery and Rapid Failover
Multi-Level Disaster Recovery: Supports a “Two-Region, Three-Center” architecture, with strong synchronization between units in the same city (RPO = 0) and asynchronous replication to remote disaster recovery sites, meeting different DR requirements.
Intelligent Failover: Provides DNS-based automatic failover (<10 minutes) and device-level automatic failover (<1 minute). Combined with stateless service design, the system enables rapid fault recovery and minimizes RTO.
VI. Microservices Architecture and O&M Optimization
Business Domain Partitioning: Splits microservices by customer type (e.g., retail, corporate), enabling independent deployment and database-level logical isolation to reduce overall system complexity.
Distributed Task Scheduling: Supports decomposition, distribution, and result aggregation of batch tasks such as mass account openings. Combined with NAS shared file systems, this delivers highly efficient batch operations.
