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Ray's Galactic Tech

Practice together, never alone. We cover programming languages, development tools, learning methods, and pitfall notes. We simplify complex topics, guiding you from beginner to advanced. Weekly practical content—let's grow together!

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Latest from Ray's Galactic Tech

100 recent articles max

Ray's Galactic Tech

Apr 4, 2026 · Backend Development

How to Build a High‑Concurrency Story Creation Platform with AgentScope Java

This article presents a step‑by‑step engineering guide for constructing a production‑grade, high‑throughput story generation platform using AgentScope Java, Spring Boot, Kafka, Redis, PostgreSQL, and Kubernetes, covering architecture, task modeling, DAG orchestration, code organization, scalability, observability, and deployment best practices.

JavaKafkaSpring Boot

0 likes · 39 min read

How to Build a High‑Concurrency Story Creation Platform with AgentScope Java

Ray's Galactic Tech

Apr 4, 2026 · Backend Development

How to Turn go-zero’s DB Automation into Production‑Ready CRUD

This guide explains why go-zero’s database automation is an engineering standard rather than a shortcut, outlines the problems it solves for large Go back‑ends, details the generation pipeline, shows how to integrate caching, and provides production‑grade practices such as custom queries, transactions, high‑concurrency tuning, testing, and deployment for an e‑commerce order service.

Database Automationbackendcode generation

0 likes · 29 min read

How to Turn go-zero’s DB Automation into Production‑Ready CRUD

Ray's Galactic Tech

Apr 3, 2026 · Artificial Intelligence

Building a Production‑Ready High‑Concurrency Story Generation System with Spring AI Alibaba

This article explains how to design and implement a scalable multi‑agent architecture for AI‑driven story creation using Spring AI Alibaba, covering core design principles, engineering optimizations, orchestration, high‑concurrency handling, observability, and deployment best practices.

KubernetesObservabilitymulti-agent architecture

0 likes · 29 min read

Building a Production‑Ready High‑Concurrency Story Generation System with Spring AI Alibaba

Ray's Galactic Tech

Apr 3, 2026 · Backend Development

How to Master Go Module Management for Scalable Distributed Systems

This comprehensive guide explains why Go module management is an architectural concern in distributed systems, outlines real‑world e‑commerce scenarios, details the underlying mechanisms like MVS, and provides practical strategies—including repository layout, versioning, CI/CD checks, Docker optimizations, and common pitfalls—to evolve from a chaotic setup to a well‑governed, production‑ready environment.

CI/CDGodistributed-systems

0 likes · 35 min read

How to Master Go Module Management for Scalable Distributed Systems

Ray's Galactic Tech

Apr 2, 2026 · Backend Development

How to Build Scalable Enterprise LLM Applications in Go with the Eino Framework

This guide walks through why enterprise‑grade LLM services need a dedicated Go framework, explains Eino’s four‑layer architecture, shows production‑ready code for model gateways, tools, RAG pipelines and graph orchestration, and provides best‑practice recommendations for performance, observability, security, testing, and deployment.

AIEinoLLM

0 likes · 47 min read

How to Build Scalable Enterprise LLM Applications in Go with the Eino Framework

Ray's Galactic Tech

Apr 1, 2026 · Operations

High‑Availability Log Platform for Ten‑Million‑Level Concurrency

This article presents a comprehensive, production‑grade design for a log collection and analysis pipeline that can reliably handle ten‑million‑level concurrent writes by combining Filebeat, Redis, Logstash, and Elasticsearch with careful buffering, scaling, and observability strategies.

LogstashRediselk

0 likes · 32 min read

High‑Availability Log Platform for Ten‑Million‑Level Concurrency

Ray's Galactic Tech

Apr 1, 2026 · Backend Development

Error Handling in Go Gin: Unified Responses for High Concurrency

This article presents a comprehensive, production‑grade error‑handling framework for Go services using Gin, covering error classification, unified response contracts, middleware ordering, stack trace management, high‑concurrency performance considerations, and practical code examples that integrate logging, tracing, retry, and circuit‑breaker strategies to improve observability and system stability.

Error HandlingGinGo

0 likes · 33 min read

Error Handling in Go Gin: Unified Responses for High Concurrency

Ray's Galactic Tech

Mar 31, 2026 · Artificial Intelligence

From Single-Node RAG to Scalable Go AI Services: A Hands‑On Architecture Blueprint

This comprehensive guide walks Go engineers through the evolution from a prototype Retrieval‑Augmented Generation (RAG) service to a production‑grade, distributed AI platform, covering architecture, component boundaries, caching strategies, async indexing, observability, security, and step‑by‑step deployment.

AI architectureBackend DevelopmentGo

0 likes · 42 min read

From Single-Node RAG to Scalable Go AI Services: A Hands‑On Architecture Blueprint

Ray's Galactic Tech

Mar 30, 2026 · Backend Development

Build a Production-Ready Go Microservice with Gin: Architecture & Scaling

This comprehensive guide walks through designing, implementing, and operating a production-grade Go microservice using Gin, covering architecture layers, domain modeling, reliable messaging, observability, CI/CD pipelines, GitOps deployment, high‑concurrency safeguards, security measures, and best‑practice testing to ensure stability, scalability, and maintainability in real‑world e‑commerce scenarios.

CI/CDGinGo

0 likes · 58 min read

Build a Production-Ready Go Microservice with Gin: Architecture & Scaling

Ray's Galactic Tech

Mar 30, 2026 · Artificial Intelligence

From Demo to Production: Building an Enterprise‑Grade RAG System with Spring AI & PGVector

This comprehensive guide explains how to design, implement, and operate a production‑ready Retrieval‑Augmented Generation (RAG) platform using Spring AI and PostgreSQL PGVector, covering architecture, indexing, hybrid retrieval, prompt engineering, scaling, security, observability, deployment, and common pitfalls for enterprise knowledge‑base applications.

Enterprise AIObservabilityPgVector

0 likes · 42 min read

From Demo to Production: Building an Enterprise‑Grade RAG System with Spring AI & PGVector