Discover how to transform nightly disk‑space alerts into automated self‑healing workflows, covering prerequisite standards, multi‑dimensional monitoring, CMDB integration, script‑based remediation, and multi‑channel notifications to scale operations across thousands of servers without manual intervention.
This article describes how a bank’s IT team transformed its performance testing by defining intelligent platform capabilities, designing a modular architecture, and implementing features such as automated risk identification, smart test case generation, data synthesis, multi‑protocol support, chaos injection, and automated result analysis using JMeter, Prometheus, and custom plugins.
This article reviews several popular open‑source monitoring tools—Cacti, Nagios, Zabbix, Prometheus, Grafana, Nightingale, and Open‑Falcon—detailing their core features, data collection methods, visualization capabilities, and typical use cases for IT operations.
This article explains why traditional manual responses to alerts are insufficient, outlines the concept of fault self‑healing, and provides a step‑by‑step guide on establishing standards, monitoring dimensions, a unified CMDB, automation tools, and notification channels to achieve automated recovery at scale.
This article explains how to build a comprehensive monitoring system using the concise USE (Utilization, Saturation, Errors) method, outlines key system and application metrics, and demonstrates practical implementation with Prometheus, Grafana, full‑link tracing, and ELK for observability and performance troubleshooting.
This guide walks you through practical Linux operations—from using xargs for efficient file handling and running commands in the background, to monitoring high‑memory and high‑CPU processes, viewing multiple logs with multitail, continuous ping logging, checking TCP states, identifying top IPs on port 80, and leveraging SSH for port forwarding.
This guide explains why Loki is a lightweight alternative to EFK/ELK, walks through installing Loki and Promtail binaries, configuring them with YAML files, and visualizing logs in Grafana using LogQL, providing a complete end‑to‑end log management solution.
This article details Dada Group’s implementation of an intelligent elastic scaling architecture that automatically adjusts capacity during peak promotions and low‑traffic periods, improving delivery reliability, reducing costs, and supporting multi‑cloud and multi‑runtime environments through sophisticated monitoring and auto‑scaler mechanisms.
This article explains how internet companies can reduce soaring manual operations costs by applying intelligent monitoring techniques—such as pattern recognition and statistical anomaly detection—to automatically identify abnormal nodes among thousands of servers, streamline fault diagnosis, and improve service quality.
This article outlines Qunar's operational strategy for reducing failures and extending uptime through precise fault detection, rapid recovery, and AI-powered predictive health management, detailing the evolution of their OPS processes, practical implementations, and future challenges in applying PHM to internet services.
In this talk, Tencent’s infrastructure lead explains how their team created an AI‑driven, three‑minute fault detection and recovery pipeline—combining high‑precision Meshping monitoring, multi‑KPI analytics, and automated Moveout isolation—to dramatically shorten network outage resolution from hours to minutes.
This article summarizes the design and evolution of a MySQL cloud DBaaS platform, covering MySQL 8.0 features, the need for DBaaS, multi‑generation architecture, service and data availability strategies, monitoring, DTS design, and upcoming roadmap for broader database support and hybrid cloud deployment.
This article explains how Alibaba’s Sunfire monitoring platform processes terabytes of logs per minute, uses a pull‑based architecture with Brain‑Reduce‑Map roles, tackles scalability and reliability challenges, and outlines future directions such as MQL standardization and intelligent baselines.
This guide explains how to monitor Longhorn storage in Kubernetes by collecting metrics with Prometheus, configuring scraping, verifying data collection, and visualizing everything in Grafana, enabling proactive performance tuning and reliable operations.
This guide explains how to store Kubernetes event data in Elasticsearch, configure Logstash and Ruby filters for timestamp correction, and create a Grafana dashboard to visualize and analyze cluster events for improved monitoring and troubleshooting.
Learn step‑by‑step how to deploy the Elasticsearch‑exporter via Helm, configure Prometheus to scrape its metrics, and visualize them in Grafana, enabling comprehensive monitoring of Elasticsearch clusters for performance, health, and early issue detection in Kubernetes environments.
This guide shows how to enable Nacos metrics, configure Prometheus to scrape them, and visualize the data with a Grafana dashboard, providing a centralized view across different departments for enterprise monitoring and decision‑making.
This article explains what Redis hotspot keys are, the performance and stability issues they cause, common causes, how to monitor and identify them, and practical mitigation strategies such as cluster scaling, key sharding, and multi‑level caching.
This article provides a systematic overview of monitoring fundamentals, compares three popular open‑source monitoring solutions—Zabbix, Open‑Falcon, and Prometheus—and offers practical guidance for selecting the most suitable system based on scale, features, and operational needs.
This guide walks you through SFTP server planning, user naming conventions, directory structures, SSH configuration, account creation, permission setup, client usage, log auditing, rotation, connection limits, monitoring, and high‑availability deployment across multiple servers, providing ready‑to‑run commands and scripts.