This article explains a complete, reusable solution for recording operation logs in Java backend applications using Spring AOP, custom annotations, callback interfaces, and a user‑adapter to bridge third‑party logging libraries with the main program, enabling flexible storage and auditing.
The article presents a decoupled business operation log management architecture that uses Alibaba’s Canal to capture MySQL binlog changes, streams them through Kafka, and stores structured before‑and‑after records in Elasticsearch with nested mappings, enabling multi‑table correlation via transaction IDs, visual querying, and reliable rollback without modifying application code.
This article walks through the design and implementation of a decoupled, high‑performance business operation log solution that captures MySQL binlog changes via Canal, streams them through Kafka, and stores and queries them in Elasticsearch, addressing challenges such as batch operations, multi‑table transactions, and non‑business data filtering.
This article explains how to implement clean, decoupled operation logs in Java applications using AOP, SpEL, custom annotations, and dynamic templates, covering use cases, implementation methods, code examples, parsing logic, context handling, and integration with Spring Boot.
The article demonstrates how to implement elegant, business‑logic‑independent operation logging in Java back‑ends by using AOP‑driven annotations, SpEL dynamic templates, custom parse functions, thread‑local context, and a Spring Boot starter, offering flexible persistence and automatic operator retrieval.
This article examines common operation‑log types and compares two implementation approaches—traditional AOP with annotations and a database binlog‑based solution—detailing their advantages, drawbacks, code examples, database design, future enhancements, and practical deployment considerations.
