This article explains how database administrators can monitor system resource usage with commands like top, iostat, and vmstat, and configure MySQL slow query logging, including enabling the log, setting thresholds, viewing logs, and applying best‑practice recommendations for analysis and issue resolution.
Learn step‑by‑step how to deploy the harbor‑exporter, configure Prometheus to scrape Harbor metrics, verify data collection, and add official Grafana dashboards, enabling real‑time monitoring of your Harbor registry for improved stability, security, and performance in cloud‑native environments.
This guide explains how Alibaba's open‑source Golang Agent enables full observability for Go applications without modifying source code, covering download, compilation, endpoint configuration, and examples of trace, metric, and log correlation using Docker and OpenTelemetry.
This article explains how Arkit, a Go‑based unified monitoring agent, collects and parses data from multiple sources, leverages Go plugins for flexible, high‑performance processing, provides custom plugin development guidelines, and discusses the performance benefits and limitations of the plugin system.
The article explains Elasticsearch's thread‑pool architecture, detailing the Search, Write, Generic, and other specialized pools, their purposes, fixed or cached configurations, optimization guidelines, and how to monitor and adjust them via REST APIs and built‑in tools.
This article details how 58 Group’s cloud authentication service introduced an observability framework—optimizing logs, employing distributed tracing, defining SLO/SLA metrics, and implementing burn‑rate alerts—to improve fault detection, reduce false alarms, and achieve faster root‑cause analysis across the system.
This article explains the core concepts of SLA, SLO, and SLI, demonstrates how to set realistic service level objectives, manage alert noise, and apply practical examples—including API, MQ, and scheduled task monitoring—to improve system reliability and performance during high‑traffic events like 11.11 promotions.
This article details how a single‑person startup leverages Kubernetes on AWS EKS to handle load balancing, automatic DNS, TLS, autoscaling, monitoring, alerting, secret management, and CI/CD for a Django‑based SaaS, illustrating practical configurations, code snippets, and infrastructure‑as‑code patterns.
This article compares Zabbix and Prometheus across performance, data collection, visualization, and alerting, highlighting their architectural differences, ecosystem strengths, and suitability for traditional data‑center monitoring versus dynamic cloud‑native workloads.
This article explains how Alibaba Cloud’s observability suite uses tag metadata to organize, monitor, and secure resources across business, endpoints, applications, middleware, and containers, offering best‑practice design principles and real‑world case studies for building scalable, tag‑driven monitoring dashboards.
Learn step‑by‑step how to deploy redis‑exporter, configure Prometheus to scrape Redis metrics, and create a comprehensive Grafana dashboard, enabling you to instantly visualize Redis performance, detect issues early, and maintain high availability in fast‑paced internet environments.
This article introduces a zero‑intrusive compile‑time automatic instrumentation framework for Go, explains its preprocessing and code‑injection mechanisms, and provides modular extension principles with concrete examples such as HTTP header logging, sort algorithm replacement, SQL injection protection, and gRPC traffic control.
This article introduces Nightingale monitoring's final v7.7 release, outlines its new features and major v7 changes, provides step‑by‑step upgrade instructions, and walks through a Docker‑based installation, data‑source integration, dashboard import, and alert‑rule configuration with DingTalk notifications.
Explore comprehensive Spring Boot 3 Actuator capabilities—including enabling CORS, creating custom endpoints, configuring health indicators, HTTP tracing, security auditing, and process monitoring—through detailed explanations, YAML configurations, and full Java code examples, empowering developers to effectively monitor and manage production-ready applications.
This guide walks you through deploying pgpool2_exporter, configuring Prometheus to scrape its metrics, and setting up Grafana dashboards so you can continuously monitor PGPool-II performance and quickly detect issues in a PostgreSQL environment.
This guide explains Linux process fundamentals, including process components, states, job control commands, signal handling, and monitoring tools like ps, top, and htop, with practical examples and step‑by‑step demonstrations for managing foreground and background jobs.
This article shares practical advice for novice project managers, covering the four process groups—initiation, planning, execution, and monitoring—through real‑world examples, stakeholder identification, risk handling, change control, and communication techniques to help them deliver value and grow their teams.
Learn how to deploy postgres_exporter, configure PostgreSQL extensions, set up Prometheus scraping, and create Grafana dashboards for comprehensive PostgreSQL performance monitoring, complete with command-line instructions and tips for verifying data collection and visualizing metrics.
Effective database administration relies on continuous monitoring of system resources—CPU, memory, disk I/O, and network—using tools like top, iostat, and vmstat, alongside logging slow MySQL queries, analyzing performance bottlenecks, and following best practices such as automated monitoring, centralized log management, regular audits, and log backups.
This article describes the design and implementation of a lightweight cloud‑native alert platform, outlining its core features, future enhancements, system architecture, and demo screenshots, offering practical insights for SREs and operations teams handling growing monitoring workloads.
This guide explains how to set up Prometheus and Grafana, create recording‑rules, import ready‑made Kubernetes component dashboards, and fine‑tune them for effective monitoring and visualization of a cloud‑native cluster.
This article introduces ten indispensable Linux operations tools—Shell scripting, Git, Ansible, Prometheus, Grafana, Docker, Kubernetes, Nginx, ELK Stack, and Zabbix—detailing their functions, typical use cases, advantages, and practical examples to help engineers automate and monitor infrastructure efficiently.
This guide walks you through setting up a comprehensive Kubernetes monitoring solution—covering component metrics collection, configuring HAProxy for network access, exposing metrics from kube-proxy, Calico, and kube-state-metrics, and integrating everything into Prometheus for reliable cluster health visibility.
This comprehensive guide walks through ClickHouse write‑performance optimization, covering hardware choices, system and application‑level tuning, async insert settings, Buffer engine configuration, storage compression, real‑world case studies, monitoring queries, and actionable best‑practice recommendations.
This guide presents essential MySQL configuration and monitoring queries—covering connection limits, Binlog/GTID status, InnoDB settings—plus a one‑click script that consolidates these checks, enabling quick health assessments and more efficient routine inspections of MySQL servers.
This guide explains what Node Exporter is, why it’s essential for enterprise monitoring, how to deploy and configure it on Kubernetes, and how to visualize its metrics in Grafana, providing a complete step‑by‑step solution for robust cloud‑native observability.
This article presents a comprehensive step‑by‑step guide for deeply inspecting the health, performance, and configuration of Elasticsearch, Filebeat, Logstash, and Kibana, including API calls, key metrics, DSL queries, Python automation scripts, and cron scheduling to ensure stable EFLK clusters.
This article explains how to use Prometheus together with Spring Boot Actuator and Micrometer to collect, expose, and visualize application metrics, including step‑by‑step dependency configuration, YAML settings, Docker deployment of Prometheus and Grafana, and adding custom metrics for comprehensive monitoring.
This guide walks you through installing Grafana via Helm, configuring its values, deploying the service, verifying the deployment, and adding a Prometheus data source, enabling a fully functional monitoring dashboard for servers and networks.
This article outlines how to correctly create, monitor, and configure Java ThreadPoolExecutor instances, explains why using the Executors factory can cause OOM, recommends separate named pools per business, provides formulas for sizing CPU‑bound and I/O‑bound workloads, and highlights real‑world pitfalls and dynamic‑configuration solutions.
The Flow Replay Platform automates traffic‑rule inspection by recording traffic from all environments, letting engineers define jsonPath‑based interface rules that continuously validate pre‑release and production traffic, instantly alerting anomalies, reducing false positives, accelerating release verification, and cutting manual testing effort, as demonstrated by discovered coupon‑related bugs.
This article shares practical Prometheus best‑practice tips—from understanding its accuracy‑reliability trade‑offs and self‑monitoring, to avoiding NFS storage, managing high‑cardinality metrics, handling rate() and recording‑rule pitfalls, and fine‑tuning alerting—so you can run a stable, low‑cost monitoring stack.
This article examines how test teams can enhance application observability and quality assurance by distinguishing observability from traditional monitoring, defining goals, outlining a monitoring foundation, and proposing module‑level and system‑level strategies for proactive fault detection, data analysis, and alerting.
This article examines how quality assurance engineers can adopt observability principles—distinct from conventional monitoring—to enhance system health detection, root‑cause analysis, and proactive risk mitigation across resources, services, business functions, data, and logs.
This guide walks you through the fundamentals of Prometheus, its architecture, and detailed Helm‑based deployment and validation steps on a Kubernetes cluster, enabling reliable monitoring for cloud‑native environments.
The article presents a comprehensive checklist of critical questions covering API design, system architecture, performance tuning, data consistency, reliability, automation, and advanced features that guide backend developers toward building scalable, secure, and high‑performance services.
This article provides a comprehensive overview of performance testing fundamentals, covering core concepts, key metrics, common testing tools, test design, load generation, result analysis, bottleneck identification, optimization techniques, cloud and micro‑service testing, monitoring, reporting, challenges, and cost‑benefit considerations.
Learn 25 practical Linux performance tuning techniques—from adjusting kernel parameters like swappiness and ulimit to optimizing I/O schedulers, network buffers, and enabling HugePages—each with clear commands and step‑by‑step instructions to help you maximize system responsiveness and throughput.
Effective operations management acknowledges inevitable downtime, emphasizes automation, prioritizes proactive prevention, treats technology as a means rather than an end, integrates closely with development through DevOps, relies on strong communication, and continuously addresses pervasive security challenges to minimize business impact.
This article details how a solo engineer built and operated a SaaS platform on AWS using Kubernetes, covering infrastructure overview, automatic DNS, TLS, load balancing, CI/CD rollouts, autoscaling, caching, secret management, monitoring, logging, error tracking, and cost‑effective operations.
This article introduces ten essential tools for operations engineers—Shell scripts, Git, Ansible, Prometheus, Grafana, Docker, Kubernetes, Nginx, ELK Stack, and Zabbix—detailing each tool's functionality, typical scenarios, advantages, and real‑world examples with code snippets for practical automation and monitoring.
This guide outlines the ten core tool categories—from Linux basics and networking services to scripting, firewalls, monitoring, clustering, and backup—that a Linux operations engineer should master to become an effective sysadmin.
This article shares a ready‑to‑run Oracle SQL*Plus script that lists active sessions with details such as instance ID, username, execution time, SQL text snippet, current event, and wait seconds, plus an example output for immediate performance troubleshooting.
This article explores the DevOps mindset, its core principles such as collaboration, automation, continuous improvement, and customer focus, outlines essential practices like CI/CD, IaC, monitoring, microservices, and provides a step‑by‑step adoption roadmap illustrated with a detailed case study and future trends.
The article outlines the key competencies a DevOps engineer must master—including programming, Linux system knowledge, configuration management, infrastructure-as-code, CI/CD tools, networking and security, monitoring, and cloud services—to guide readers on building a comprehensive skill set for effective DevOps practice.
The article explains the design and implementation of the Serverless Application Engine (SAE) Event Center, highlighting its cloud‑native architecture, the distinction from traditional monitoring, challenges like data explosion and full GC, and the distributed‑cache solution that enables efficient real‑time event aggregation, notification, and future AI‑driven diagnostics.
This article explains how to build real-time monitoring applications using PHP and the WebSocket protocol, covering the fundamentals of WebSocket, setting up a Ratchet server, creating client-side JavaScript connections, and providing complete code examples such as a stock price monitor.
The article clarifies that DevOps is not defined by specific tools like Kubernetes or Jenkins, but by the ability to design robust systems that ensure smooth deployments, effortless scaling, reliable operation, early issue detection, and effective team collaboration, emphasizing enduring principles over changing technologies.
When a Linux server shows performance issues, the first minute is critical; this guide walks you through ten standard command‑line tools—uptime, dmesg, vmstat, mpstat, pidstat, iostat, free, sar, and top—explaining what each metric means and how to interpret the output for quick troubleshooting.
Bilibili rebuilt its monitoring platform to handle explosive metric growth by separating collection, storage, and compute, adopting VictoriaMetrics, zone‑based scheduling, and Flink‑driven pre‑aggregation, which together improved stability, query performance, cloud data quality, and overall observability.
This article details the design and deployment of an intelligent alert attribution system for Ctrip Hotel's front‑end, describing the background challenges, the unified data pool, weighted alert rules, three attribution algorithms, achieved improvements in accuracy and troubleshooting speed, and future enhancement plans.
This guide explains how to optimize Nginx settings and adjust Linux kernel parameters—such as worker processes, connection limits, caching, HTTP/2, rate limiting, and TCP tweaks—to reliably handle massive traffic spikes while maintaining high availability and performance.
This guide explains how to systematically diagnose Linux performance issues using tools such as top, vmstat, perf, and flame graphs, covering CPU, memory, disk I/O, network, and load analysis, and demonstrates a real-world nginx case study with step‑by‑step commands and visualizations.
This guide walks through exposing the nginx‑ingress metrics port, configuring static scrape jobs, and using a ServiceMonitor CRD to dynamically collect ingress metrics with Prometheus in a Kubernetes cluster, including all required YAML snippets and verification steps.
This article explains how Bilibili designed and implemented an Emergency Response Center (ERC) to manage the full fault lifecycle—detection, response, delimitation, localization, mitigation and recovery—using alert rules, automated recall, integrated customer feedback, clear role assignments, mobile support, and data‑driven post‑mortems, ultimately reducing MTTR and improving service reliability.
This article provides a comprehensive guide to Python's standard libraries for Linux, covering file and directory manipulation, process control, socket networking, system information retrieval, date and time handling, logging, file monitoring, compression, and environment variable management with clear code examples.
This article presents a collection of practical Bash scripts that cover file consistency checks, scheduled log management, network traffic monitoring, numeric analysis, FTP downloads, user input handling, Nginx 502 detection, variable assignments, bulk file renaming, text processing, port scanning, word filtering, command menus, SSH automation with Expect, user creation, Apache monitoring, password rotation, iptables rate‑limiting, and IP validation, providing sysadmins with ready‑to‑use solutions for everyday Linux operations.
The article details Bilibili's evolution of its monitoring platform, describing the stability and performance challenges of a Prometheus‑Thanos stack, the redesign using VictoriaMetrics, collection‑storage separation, unit‑level disaster recovery, query‑tree auto‑replacement, Flink‑based pre‑aggregation, Grafana upgrades, and future roadmap for observability.
This guide walks you through setting up a full Prometheus monitoring solution with Exporters, Alertmanager, and Grafana using Docker containers, covering component roles, configuration files, and visualizing host and container metrics on two sample hosts.
This article presents practical techniques for improving Prometheus performance in cloud‑native environments, covering storage retention, block size, scrape intervals, label reduction, query optimization, sharding, high‑availability setups, and alert rule simplification.
Pinterest’s performance program details how the team defines custom Pinner Wait Time metrics, uses real‑user monitoring and fine‑grained alerts to detect regressions quickly, and follows structured root‑cause analysis and ownership processes to prevent performance degradation across web surfaces.
This article explains how to integrate JD's JADE dynamic thread‑pool component with the Wanxiang visualization platform, covering Maven dependencies, configuration files, Spring bean setup, thread‑pool creation, runtime monitoring, underlying source‑code principles, and common pitfalls for stable backend services.
This article compiles ten practical operations‑engineer guidelines—ranging from change rollbacks and safe command aliases to backup verification, monitoring, and cautious automated failover—to help maintain high availability and avoid costly production incidents.
This guide outlines essential strategies to improve release quality in R&D, covering strict testing processes, automated CI/CD pipelines, containerization, real‑time monitoring, alert mechanisms, and feedback loops, while also defining key evaluation metrics and practical steps for effective management of these indicators.
This article demonstrates how to install the prometheus_api_client library, fetch time‑series data from Prometheus with Python, process it using pandas, and create interactive visualizations with Plotly, providing a complete workflow from data collection to insight generation.
Learn how to integrate the open‑source DynamicTp framework into Spring Boot 2.7, configure its core parameters, enable real‑time monitoring, alerts, and Nacos‑based dynamic adjustments, while exploring code examples, dependency setup, and practical usage for robust thread‑pool management.
This article explains what a dynamic thread pool is, why it is needed, how to modify its core parameters at runtime, how to monitor and expose its metrics, and lists open‑source implementations and visualization/alerting options such as Prometheus, Grafana, Hippo4j and Dynamic TP.
The article explains what a dynamic thread pool is, why static pools are problematic, how to modify core parameters such as corePoolSize, maximumPoolSize, and workQueue at runtime, and provides code examples for monitoring, exposing metrics via Spring Boot Actuator, and integrating with Prometheus‑Grafana, while also listing open‑source implementations like Hippo4j and Dynamic TP.
This article examines the migration from Thanos to VictoriaMetrics for large‑scale metric storage, detailing background challenges, VictoriaMetrics architecture and storage engine, data write and read processes, and a comparative analysis of performance, scalability, and operational costs between the two systems.
The article introduces three official Grafana dashboards—Indexer, Searcher, and Metastore—for monitoring Quickwit clusters, provides direct JSON links, shows example screenshots, and explains that they rely on Prometheus metrics collected from Quickwit.
This article explains the node‑exporter conntrack plugin, the metrics it exposes, how to interpret them, set alert thresholds, and the underlying Go collector code that reads Linux proc files to monitor conntrack table usage in firewall or NAT environments.
OPPO transformed its sprawling, manually‑provisioned middleware clusters into a cloud‑native, containerized platform by building custom Kubernetes controllers, IP‑preserving StatefulSets, resource‑isolated containers, automated monitoring and self‑healing workflows, enabling rapid provisioning, efficient utilization, fault‑tolerant scaling and future serverless and service‑mesh integration.
This article walks through a complete, step‑by‑step solution for collecting Nginx access logs, converting them to JSON, shipping them with Promtail to Loki, and visualizing the data in Grafana, including Docker deployment, dashboard import, and world‑map plugin installation.
This article explains the concept of JavaAgent, its underlying mechanism using the JVM instrumentation API, and provides a step‑by‑step guide with code samples to build a JavaAgent that measures method execution time in a Spring application.
This article explains the motivations for upgrading to JDK21, introduces Generational ZGC, details integration steps and monitoring setup, presents performance test results comparing ZGC and Generational ZGC, and outlines future plans for Java services at Zhaozhuan.
This article provides a comprehensive overview of Prometheus, covering its architecture, suitable and unsuitable use cases, data model with TSDB and WAL, metric types, PromQL query language, and practical examples for monitoring CPU, memory, and disk usage in Kubernetes environments.
Shadow testing is a parallel deployment strategy that minimizes the risk of system changes, safeguards user experience, validates performance and data integrity, and provides a controlled environment for comprehensive testing, supported by a suite of modern tools and real‑world case studies.
This article provides a step‑by‑step tutorial on what Grafana is, its common monitoring scenarios, how to install it on Linux, Windows, macOS or via Docker, configure data sources such as Prometheus, and create or import dashboards for system and business metric visualization.
This guide walks through installing Prometheus on a Kubernetes cluster, customizing alert rules, handling service exposure, and diagnosing common Alertmanager connection issues by inspecting CoreDNS and CNI configurations, offering practical solutions for reliable cloud‑native monitoring.
This article shares ten practical operations strategies—including change rollbacks, safe handling of destructive commands, prompt customization, rigorous backup and verification, production environment discipline, careful handovers, robust alerting, cautious automatic failover, meticulous checks, and simplicity—to dramatically improve system reliability and availability.
This article shares engineering insights from Hema’s AI smart customer service deployment, detailing key stability factors for AI agents—including hallucination mitigation, memory integration, RAG enhancement, exception handling, and comprehensive monitoring—to improve reliability and performance in real‑world e‑commerce chatbot scenarios.
This article details how to construct a log‑monitoring platform using the ELK stack, Kafka buffering, and a Python scheduler to collect, process, and alert on error logs, offering practical configuration tips and performance optimizations for production environments.
This article outlines the essential components and design considerations for creating a distributed task scheduling platform, covering triggers, scheduling strategies, executors, task chains, circuit breakers, exception handling, blocking control, service discovery, monitoring, and a management console.
This article explains how modern frontend applications use comprehensive monitoring, real‑time alerts, performance metrics, custom reporting, and scheduled inspections to maintain system stability, improve user experience, and proactively address errors across web, mini‑program, and native platforms.
This article describes how a large enterprise front‑end team implements real‑time monitoring, scheduled inspections, alert strategies, performance metrics, error handling, custom reporting, and mobile/native monitoring to ensure system stability, improve user experience, and continuously optimize application performance.
This comprehensive guide to backend development explains essential system and architecture design principles, networking strategies, fault and exception handling, monitoring and alerting, service governance, testing methodologies, and deployment practices, offering best‑practice advice and highlighting common pitfalls for building reliable, scalable internet services.
This article explains how to deploy Blackbox Exporter in multiple data centers, configure Prometheus to scrape region‑specific HTTP metrics for a target website, validate the setup via queries, and add alerting rules to detect latency or downtime, providing a self‑hosted monitoring solution.
This tutorial shows how to instrument Spring Boot APIs using Actuator, a custom @Monitor annotation with AOP, and Prometheus to collect and visualize method execution times, providing a complete end‑to‑end monitoring solution.
This article details how Bilibili redesigned its monitoring system to overcome explosive metric growth by separating collection and storage, adopting VictoriaMetrics, implementing zone‑based scheduling, automating PromQL query replacement, and using Flink for efficient pre‑aggregation, resulting in dramatically lower latency and higher stability.
The new Monitoring 2.0 architecture separates collection, compute and storage, adopts VictoriaMetrics for compact time‑series storage and a zone‑based scheduler, introduces push‑based ingestion, uses Flink for real‑time pre‑aggregation and automatic PromQL rewrite, delivering ten‑fold query speedups, sub‑300 ms p90 latency, and dramatically higher write and query throughput.
Before launching costly observability initiatives, ensure your monitoring is comprehensive and efficient, covering business, application, component, resource, network, and endpoint metrics, and that you have the data collection, storage, alerting, and event‑distribution capabilities to turn raw signals into actionable insights.
This article explains how modern front‑end teams ensure system stability and high‑quality operation by implementing comprehensive monitoring and automated inspection, covering background, significance, architecture, real‑time and scheduled checks, performance metrics, alert strategies, error handling, custom reporting, and future improvement plans.
This article describes how to use Grafana's Flowcharting plugin and Prometheus metrics to create a dynamic, interactive dashboard that visualizes each logical node of a push notification pipeline, enabling rapid trace‑ID based troubleshooting and reducing manual investigation effort.
This guide outlines a comprehensive, automated strategy for operating more than ten thousand network devices, covering asset documentation, topology planning, unified monitoring, automation scripts, emergency response, security management, regular maintenance, staff training, and visual management tools.
This article presents a Bash script that gathers comprehensive Linux system metrics—including CPU core count, utilization percentages, context switches, interrupts, load averages, memory and swap usage, and disk I/O statistics—explaining each command and its purpose for effective server monitoring.
This article introduces ten indispensable tools for operations engineers, detailing each tool's functionality, ideal use cases, key advantages, and practical examples, while also providing code snippets and visual illustrations to help readers understand and apply them effectively.
This article explains why true observability is essential for modern software, outlines its five core pillars, details a four‑stage maturity model with benefits and drawbacks, and provides practical steps—including data collection, team organization, and AI automation—to advance from basic monitoring to predictive, self‑healing systems.
This article outlines comprehensive best‑practice guidelines for designing robust, secure, and maintainable backend services—covering API path conventions, request handling, parameter design, error codes, dependency management, monitoring, degradation strategies, legacy service handling, encryption, access control, and tamper‑proof mechanisms, with practical code examples.
Alibaba Taotian’s testing platform now lets business owners self‑service reliable environments by binding accounts to isolated routes, monitoring lightweight health metrics with automated self‑healing, accelerating deployments via code caching and JVM tricks, and enabling rapid “time‑travel” scenario testing, while planning tighter observability and production alignment.
This article outlines the most frequent Kubernetes pitfalls—such as missing resource requests, omitted health checks, using the :latest tag, over‑privileged containers, insufficient monitoring, default namespace misuse, weak security settings, absent PodDisruptionBudgets, lack of pod anti‑affinity, and improper load‑balancing—and provides concrete commands, YAML examples, and best‑practice recommendations to prevent them.
