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 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.
This article examines the technical and operational challenges of the 618 shopping festival, presenting data‑driven insights and detailed strategies—including modular deployment, monitoring, logging, fast‑failure, rate limiting, database and cache optimizations, and emergency response plans—to help teams maintain system stability under massive traffic spikes.
This article explains the fundamental differences between traditional and cloud‑native monitoring systems, outlines the challenges each faces, and details JD.com's evolution from physical servers to JDOS 2.0, describing its modular architecture, deployment model, and ongoing optimization efforts.
Since Gartner introduced AIOps in 2016, the IT operations landscape has evolved through five stages—from manual scripting to standardized tools, platform automation, DevOps, and now AI-driven AIOps—enabling real-time anomaly detection, root‑cause analysis, noise reduction, and predictive maintenance through big data and machine learning.
During JD.com’s 11.11 Global Shopping Festival, the JD Cloud Log Service handled petabyte‑scale log data, delivering real‑time monitoring, cost‑effective storage, high‑availability architecture, circuit‑breaking, rate‑limiting, auto‑scaling and comprehensive dashboards to ensure stable operation of the massive traffic surge.
This article reveals how JD's Zhilian Cloud prepares for the massive 11.11 shopping festival by rapidly mobilizing teams, defining protection scopes, estimating resources, implementing high‑availability across regions and AZs, applying business degradation and elastic scaling, and establishing comprehensive monitoring and rehearsal practices to ensure a smooth, resilient promotion.
This article introduces JD Cloud’s self‑built time‑series database HoraeDB, explaining its core concepts, typical use cases, architectural layers, high‑performance features, down‑sampling strategies, compression techniques, and stability measures for handling massive, 24‑hour monitoring data at scale.
This article explores obscure Android thread issues—including uncontrolled thread creation, stack memory leaks, and the impact of thread‑priority settings—while presenting monitoring techniques, a pthread hook implementation, and performance considerations to help developers detect and resolve thread‑related crashes.
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 guide outlines the purpose, scope, principles, and detailed specifications for log management—including file naming, retention periods, content rules, security handling, and monitoring—to ensure reliable issue tracing, data safety, and regulatory compliance across all system development projects.
This comprehensive guide introduces distributed tracing challenges in large microservice systems, explains what Apache SkyWalking is, compares it with Zipkin, Pinpoint and CAT, details performance test results, walks through installation, configuration, custom tracing, log integration, alerting, and high‑availability deployment.
This article provides an overview of five leading observability solutions—Datadog, Grafana, Instana, New Relic, and Prometheus—detailing their core features, supported data sources, deployment models, and how they help teams monitor cloud‑native applications, infrastructure, and services to ensure reliability and performance.
This article explains what logging is, why it matters, when to log, the principles and level conventions, common log formats, and a comprehensive set of mandatory and recommended best‑practice rules for writing robust, secure, and maintainable backend logs.