The leading WeChat public account for Elasticsearch fundamentals, advanced topics, and hands‑on practice. Join us to dive deep into the ELK Stack (Elasticsearch, Logstash, Kibana, Beats).
This guide explains how to integrate the lightweight Cerebro monitoring tool with Easysearch, covering core features, configuration steps, and detailed solutions for frequent issues such as Java version conflicts, SSL certificate errors, and authentication mismatches.
This guide details the EasySearch rule syntax, covering rule structure, logical operators, field constraints, regular expressions, distance matching, numeric range matching, three practical tagging scenarios, common errors, special‑character escaping, and concise best‑practice recommendations.
The article walks through EasySearch's Rules plugin, showing how its high‑performance C++ rule engine can automatically match and tag documents during the ingest pipeline, enabling zero‑latency content classification for scenarios like regional, sentiment, and entity tagging.
This article guides you through enabling Easysearch's audit log, configuring the security.audit.type parameter, verifying settings in the management UI, and using the audit records to identify external IPs, failed logins, and SSL handshake failures in a production environment.
The article analyzes why large‑language models like Claude, GPT‑4, and Gemini repeatedly generate nearly identical web designs, identifies four convergence dimensions (typography, color, motion, background), and presents a reusable "Skills" mechanism that injects expert design context to produce distinctive, high‑quality frontend outputs.
This article breaks down Andrew Ng and Anthropic’s Agent Skills course, explaining how organized skill folders give general AI agents domain expertise, repeatable workflows, and new capabilities, while using portable, composable design and progressive disclosure to make agents reliable, scalable, and industrial‑grade.
This article walks through building a practical Elasticsearch demo that lets users type a single query like “nearby clean coffee shop” and get results by combining dense‑vector semantic search, geo filtering, BM25, and a hybrid RRF‑style ranking, with both LLM‑based structuring and a fallback hash‑based embedding.
This guide walks through five systematic checks—indexing delay vs refresh, thread‑pool rejections, segment merges and I/O, bulk size and refresh settings, and mapping/_source configuration—to pinpoint and resolve Elasticsearch write‑performance bottlenecks.
This article shows how to create an Easysearch intelligent assistant that lets users manage indexes, write data, search and aggregate documents using Chinese natural language, by combining the DeepSeek large‑language model with OpenAI‑compatible function calling (Tool Use) and a lightweight Node.js executor.
This article walks through converting the Easysearch command‑line assistant into a web‑based tool by adding an Express API layer, reusing shared logic, and building a lightweight HTML/CSS/JS front‑end, while preserving the original CLI capabilities.
