This article reviews four ELK deployment patterns, compares their strengths and weaknesses, and demonstrates how ELK can be applied to big‑data operations such as log aggregation, system monitoring, fault diagnosis, and performance analysis with practical examples.
This guide walks through the complete installation, configuration, and integration of the ELK stack components—Logstash, Redis, Elasticsearch, and Kibana—providing command‑line examples, configuration snippets, testing procedures, and visual verification using Kibana and the Kopf plugin.
This guide introduces Logstash as an open‑source data collection engine, explains its core input‑filter‑output architecture, walks through installation, and demonstrates three practical examples: console I/O, output to Elasticsearch, and reading from Redis with real‑time output.
This article reviews major open‑source log collection tools—Chukwa, Scribe, Flume, Logstash, Kafka, and TT—examining their architectures, strengths, and limitations to help engineers select the most suitable solution for high‑volume, low‑latency data pipelines.
This guide walks through configuring the firewall, installing Kibana, Logstash, and Elasticsearch, setting up SSL certificates, forwarding ports, deploying Filebeat to client servers, and verifying the ELK stack operation on Linux, complete with command examples and screenshots.
This article walks through the full ELK Stack installation on a Linux test environment, covering component overview, host planning, required packages, detailed command‑line steps for Elasticsearch, Logstash, Kibana and Filebeat, and the necessary firewall and service checks.
This guide explains what the ELK Stack is, outlines its key advantages, and provides detailed, command-line instructions for installing JDK, Elasticsearch 2.2.0, Kibana 4.4.1, and Logstash on Linux, along with testing, Log4j integration, and a common startup permission fix.
This guide walks you through centralized log collection, explains the roles of Elasticsearch, Logstash, and Kibana, and provides step‑by‑step commands to install, configure, and verify a complete ELK logging pipeline for Linux servers.
This article reviews major data collection platforms—including Apache Flume, Fluentd, Logstash, Chukwa, Scribe, and Splunk Forwarder—explaining their architectures, strengths, and limitations to help engineers select the most reliable and scalable solution for big‑data pipelines.
This article shares the author's experience and lessons learned while building a log‑monitoring framework with the ELK stack, discussing performance issues, configuration of Logstash filters using Grok, and practical tips for deploying ElasticSearch, Logstash, and Kibana in production environments.
This guide walks you through the fundamentals of big‑data characteristics, the challenges of log management for small‑scale operations, and provides a detailed, step‑by‑step tutorial for installing and configuring the ELK stack (Elasticsearch, Logstash, Kibana) on a CentOS 6.6 server, including all required dependencies.
This article explores how the ELK stack can transform large‑scale log processing into fast, flexible, and interactive analysis for troubleshooting, security auditing, and monitoring, sharing practical examples, common pitfalls, and best‑practice recommendations from real‑world deployments at Sina.
This guide explains why log analysis is critical, outlines common challenges, compares heavyweight trace systems with the lightweight LEK stack, and provides step‑by‑step installation, configuration, and best‑practice tips for Logstash, Elasticsearch, and Kibana.
