The Sharding Pattern: Scaling Data Stores Horizontally
Divide your data store into horizontal partitions to improve scalability and performance. Learn how sharding distributes data across multiple servers to handle massive volumes.
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The Sidecar Pattern: Extending Applications Without Touching Code
Deploy supporting components alongside your application in separate containers. Learn how the Sidecar pattern enables isolation, encapsulation, and heterogeneous technology stacks.
Strangler Fig Pattern: Pattern or Strategy?
Incrementally migrate legacy systems by gradually replacing functionality with new services. But is Strangler Fig truly a pattern, or is it a migration strategy? Let's explore this architectural approach and its philosophical classification.
Materialized View 模式：通过预先计算的数据优化查询性能
了解 Materialized View 模式如何通过预先计算并以特定查询优化的格式存储数据来提升查询性能，以及它与数据库 materialized view 的差异。
Materialized View Pattern: Optimizing Query Performance Through Precomputed Data
Learn how the Materialized View pattern improves query performance by precomputing and storing data in formats optimized for specific queries, and how it differs from database materialized views.
Materialized View 模式：透過預先計算的資料優化查詢效能
了解 Materialized View 模式如何透過預先計算並以特定查詢優化的格式儲存資料來提升查詢效能，以及它與資料庫 materialized view 的差異。
The Claim-Check Pattern: Handling Large Messages in Distributed Systems
Learn how the Claim-Check pattern solves the challenge of transferring large payloads in messaging systems by storing data externally and passing lightweight tokens instead.
Retry Pattern: Building Resilient Applications
Learn how the Retry pattern helps applications handle transient failures gracefully, improving stability and user experience in distributed systems.
Anti-Corruption Layer Pattern: Protecting Your Modern Architecture
Learn how the Anti-Corruption Layer pattern helps you integrate legacy systems with modern applications without compromising your clean architecture design.
Rate Limiting Pattern: Efficiently Managing Throttled Services
Learn how the rate limiting pattern helps you avoid throttling errors and improve throughput when working with services that impose usage limits.