This article explains what Druid Monitor and Druid Admin are, why cluster‑level monitoring is needed in microservice architectures, and provides a complete Spring Cloud starter implementation with configuration examples, code snippets, and usage limitations.
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.
This article explains the concept of observability, details Prometheus metric definitions and types, and provides Go code examples for exposing, defining, generating, and scraping business‑level metrics in a Kubernetes‑based cloud‑native environment.
This article outlines the core responsibilities of IT operations, examines the current state and management goals, and provides a detailed roadmap for automating tasks such as server provisioning, environment definition, deployment, monitoring, and version release across multiple maturity stages.
This article explains how to design and implement Prometheus metrics for application monitoring, covering the selection of monitoring targets, golden metrics, label conventions, naming rules, histogram bucket choices, and Grafana visualization tricks to help engineers build reliable observability pipelines.
This guide explains monitoring fundamentals, clears common misconceptions, compares black‑box and white‑box approaches, outlines key metrics such as latency, traffic, errors and saturation, and provides a deep dive into Prometheus architecture, data model, query language, and practical examples for CPU, memory, and disk monitoring.
This article explains how to use Prometheus to monitor business‑level metrics in a Kubernetes environment, covering observability fundamentals, metric definitions, metric types, exposing metrics via a /metrics endpoint, and practical Go code examples for defining, recording, and scraping custom metrics.
This article walks through practical methods for troubleshooting slow service alerts, diagnosing Redis performance bottlenecks, and reproducing issues with local demos and load simulations, offering concrete metrics, command‑line checks, and mitigation strategies such as scaling, rate‑limiting, and pipeline optimization.
This article explains how metrics are used to monitor software performance, introduces basic metric components and dimensional metrics, compares Prometheus, OpenMetrics and OpenTelemetry standards, and provides detailed guidance on Prometheus metric types—Counter, Gauge, Histogram, and Summary—with code examples and query patterns.
This guide explains how to design effective Prometheus metrics, choose appropriate monitoring objects, labels, and buckets, and leverage Grafana visualizations to gain deep insight into application performance across online services, offline processing, and batch jobs.
This article explains how to design effective Prometheus metrics for various application types, covering golden metrics, label selection, naming conventions, bucket choices, and Grafana visualization tips to help engineers build reliable observability solutions.
ByteDance’s cloud‑native big data operations platform consolidates logging, monitoring, and alerting across heterogeneous environments, using unified log collection (intrusive and Filebeat), dynamic alert rules, customizable notification plugins, and scalable monitoring pipelines, thereby reducing operational complexity, shielding users from infrastructure differences, and enhancing multi‑tenant efficiency.
This article outlines the background, objectives, and implementation framework of AIOps at a major bank, detailing data consolidation, analysis engines, scenario ecosystems, practical case studies, and future directions for intelligent, proactive IT operations.
This comprehensive guide explains MongoDB cluster architecture, component roles, common use cases, monitoring commands, essential maintenance operations, data migration steps, troubleshooting of typical production issues, and practical optimization recommendations for high‑performance deployments.
This article details China Mobile Information's interview about their centralized AIOps platform, the recent excellent‑level assessment by the China Academy of Information and Communications Technology, the system's key modules, future plans, and the broader significance of AI‑driven IT operations.
This article explains how to design effective Prometheus metrics, choose appropriate vectors, labels, buckets, and naming conventions, and offers Grafana usage tricks to help engineers monitor online services, batch jobs, and offline processing systems with clear, actionable insights.
This article explains how to use the Prometheus HTTP API to query instant and range metrics, interpret the JSON responses, and fetch data programmatically with Python, providing code examples and details on request parameters, error handling, and practical usage.
This comprehensive guide explains Linux performance optimization by defining key metrics such as throughput and latency, interpreting average load, analyzing CPU context switches, memory management, and I/O behavior, and recommending practical tools and techniques—including vmstat, pidstat, perf, and dstat—to identify and resolve bottlenecks.
This guide details key Redis monitoring metrics—including performance, memory, activity, persistence, and error indicators—along with practical commands, configuration settings, and code snippets to help operators efficiently track and troubleshoot Redis instances.
This article outlines the essential components of operational monitoring, covering monitoring objectives, methods, core processes, key tools, metrics for hardware, system, application, network, and business layers, as well as alerting, handling, and best practices for building a comprehensive, reliable monitoring solution.