Java architect and Raspberry Pi enthusiast, dedicated to writing high-quality technical articles; the same name is used across major platforms.
This article walks through the symptoms, root cause analysis, and step‑by‑step solutions for uneven CPU usage across Java service instances, highlighting how mismatched Kafka partition counts and thread or GC issues can lead to load imbalance and how to resolve them.
The article reviews the most common distributed transaction patterns—TCC, Saga, reliable messaging, 2PC, and Seata's AT mode—explaining their principles, ideal use‑cases, implementation details, and trade‑offs so architects can select the most suitable solution for their microservice systems.
This article outlines a comprehensive, risk‑controlled SOP for migrating business data—including model changes, storage shifts, incremental dual‑write, back‑filling, full and incremental consistency checks, read‑switching, and final decommissioning—backed by concrete SQL examples and visual diagrams.
During a holiday break the author used AI programming assistants Kiro and OpenCode to create a complete Java‑backed, Jamstack‑based full‑stack application that scrapes Epic Games' free‑game listings, generates static JSON/HTML pages, and deploys automatically to Cloudflare Pages, demonstrating AI‑driven development efficiency.
This article provides a comprehensive guide to gray releases and A/B testing, covering common scenarios, implementation methods, layered experiment design, hash-based bucket allocation, data collection workflows, statistical analysis, and practical Java and SQL code examples for reliable feature validation.
Backend developers need to understand both offline and real-time data warehouses; this guide explains data collection, layering, partitioning, typical use cases, archiving strategies, and how to build a real-time warehouse with Flink, covering practical steps, examples, and key considerations for efficient data processing.
This article explains the principles and implementation details of common rate‑limiting algorithms—token bucket and sliding‑window counting—including their core concepts, key processes, Java code examples, and how to extend them to distributed scenarios with Redis Lua scripts.
This article compares three Java rate‑limiting approaches—Guava RateLimiter for single‑node control, Sentinel for both single‑node and cluster scenarios, and Redisson RateLimiter for distributed limits—detailing their usage, advantages, disadvantages, and code examples to help developers choose the right solution for their traffic management needs.
This article systematically compares four cache update patterns—cache‑aside, asynchronous write‑back, read/write‑through, and ongoing optimizations—detailing their implementation steps, suitable scenarios, advantages, drawbacks, and practical tips such as delayed double deletion and proactive cache refreshing to balance performance and consistency.
This article explains why cross‑system data inconsistencies occur, defines key reconciliation metrics—completeness, timeliness, and automatic repair—and provides step‑by‑step designs for both real‑time (seconds‑to‑minutes) and offline (hour‑to‑day) reconciliation, including message‑driven triggers, batch processing, and SQL examples for detecting and fixing mismatches.
