The article defines R&D efficiency as the effective use of human and time resources to deliver high‑quality software quickly, and outlines a systematic, multi‑dimensional approach—including culture, structure, architecture, process design, engineering systems, and measurement—to enhance it.
This article explains Douyin’s growth‑analysis methodology, how to construct a comprehensive growth‑metric system with North‑Star indicators and hierarchical metric layers, the end‑to‑end analysis loop, new scenario‑driven metric applications, and a detailed case study on improving video‑submission rates.
This article explains why metrics are essential, defines what a metric is, describes the four essential elements of metric design, outlines the three‑step design process, discusses measurement scales and time characteristics, and provides criteria for evaluating good metrics.
Xiaohongshu’s observability team rebuilt its Prometheus‑based metrics platform using vmagent, dual‑active HA clusters, query push‑down, high‑cardinality governance and multi‑cloud active‑active design, delivering ten‑fold collection speed, up to 70× query capacity, massive CPU‑memory‑storage savings and fully automated scaling.
While A/B testing is widely used for data-driven decisions, short-term experimental results often diverge from long-term impacts, leading to misguided strategies; this article examines why such inconsistencies arise and reviews major methods—including extended experiments, holdout groups, post‑analysis, CCD, and surrogate‑metric modeling—to reliably estimate long‑term effects.
This article outlines the essential steps for embracing DevOps culture, emphasizing tailored strategies, deep understanding of CI/CD, clear role assignments, extensive automation, key performance metrics, and the critical role of quality assurance to achieve faster, reliable software delivery.
This article explains how to build a data‑driven metric system—from defining end‑to‑start metrics and combining business and data drivers, to applying statistical analysis, machine‑learning, causal inference, and practical case studies for alerting, diagnosing, and strategizing product performance.
This study analyzes JD e‑commerce operational data from February to April 2018, employing Python and SQL to compute key metrics such as PV, UV, conversion rates, attrition, purchase frequency, time‑based behavior, funnel analysis, retention, product sales, and RFM segmentation, and provides actionable recommendations for improving user engagement and sales performance.
This article outlines typical interview questions about handling a growing number of business metrics, structuring and managing metric definitions, providing unified services, and performing anomaly detection and attribution analysis, offering practical guidance for data‑focused roles.
This article explains the INP (Interaction to Next Paint) performance metric, its calculation method, satisfaction thresholds, differences from FID, and provides practical guidance on measuring INP using Chrome's CrUX, PageSpeed Insights, the web‑vitals library, Chrome extensions, and custom console scripts.
This article details the design and implementation of the Pylon APM monitoring platform for NetEase Cloud Music, covering background challenges, the choice of Pinpoint, extensions to trace models, tail‑based exception sampling, Prometheus integration, automated JStack collection, and the resulting APM product features.
Dongguan Securities' "Zhangzhengbao" service platform passed the China Academy of Information and Communications Technology's DevOps Continuous Delivery Level 3 assessment, demonstrating how standardized processes, automation, and metric‑driven improvements can boost efficiency, reduce costs, and enhance competitiveness in the financial sector.
This article explains what metrics are, categorizes them, describes how to design effective metrics for R&D teams, outlines criteria for judging their quality, and provides practical guidance for tracking, reviewing, and continuously improving them.
This article explores why logs are essential in software development, outlines when to record them, discusses the value of logging in large-scale distributed systems, and examines the capabilities required of log‑operation tools such as APM, metrics, tracing, ELK, Prometheus, and custom batch querying solutions.
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 explains how Kuaishou's e‑commerce team built a unified OLAP‑based data platform—covering data ingestion, consistent dimensional and fact layers, metric management, and real‑time services—to address rapid growth, metric inconsistency, and operational inefficiencies across multiple business scenarios.
This article visually dissects Prometheus, explaining its architecture, core features, data collection methods, exporter role, PromQL query language, and alerting workflow, while contrasting it with ELK and highlighting practical configuration examples for real‑world monitoring.
This article explains why web performance matters, introduces key user‑centric metrics such as First Contentful Paint, Largest Contentful Paint and Cumulative Layout Shift, describes how to measure them with tools like Chrome DevTools, Lighthouse and ftwo, and provides practical optimization techniques including gzip, HTTP/2, CDN, image handling, code splitting and Vue router lazy‑loading.
This article explains how to combine OKR and agile activities to set measurable business goals, avoid common pitfalls, and create a continuous loop of planning, execution, review, and optimization that aligns strategic objectives with day‑to‑day value delivery in R&D projects.
The article explains how misleading metrics like “watermelon‑type” KPIs can mask poor system availability, introduces the OKRa framework that adds activities to traditional OKRs, and promotes a nationally certified DevOps engineering program to improve end‑to‑end R&D efficiency.
This guide explains how to enable OpenTelemetry in Apache Airflow, configure an OTel collector, use Prometheus as a metrics backend, set up Grafana dashboards, and visualize sample DAG metrics, providing a complete observability stack for Airflow pipelines.
This article explains how SaaS companies can quantify and deliver customer value by defining, measuring, and optimizing key success metrics such as ROI, adoption rates, time‑to‑value, and lifecycle duration, while emphasizing continuous communication and expectation management throughout the customer journey.
The article explains what metrics are, why they matter, how they can be classified, the structured process for creating effective R&D metrics, criteria for judging good metrics, and practical methods for tracking, reporting, and periodically reviewing them to ensure continuous improvement.
DevOps testing integrates continuous, automated testing throughout the software development lifecycle, shifting left from traditional isolated testing, emphasizing automation, appropriate tool selection, metric tracking, documentation, and dedicated test automation engineers to ensure high‑quality, rapid software delivery.
This article explains the fundamentals of metrics, introduces dimensional metrics, compares Prometheus, OpenMetrics, and OpenTelemetry standards, and provides detailed guidance on the four Prometheus metric types—Counters, Gauges, Histograms, and Summaries—including their use‑cases, PromQL queries, and Python client examples.
The presentation details Hello’s end‑to‑end R&D efficiency platform, covering its digital resource‑strategy system, custom iteration model, integrated MRD/PRD workflow, metric dashboards, and concrete savings of up to 400 man‑days in project management and 1,400 man‑days in development operations.
Didi’s observability platform leverages non‑intrusive eBPF probes to automatically capture and validate service‑to‑service call tuples, supplement missing SDK data, achieve roughly 80 % core‑path coverage, and address verification challenges while planning future user‑space VM hooks and deeper MTL integration.
This article introduces the fundamentals of metrics in IT monitoring, explains the structure of metric data points, explores dimensional metrics, and provides an in‑depth guide to Prometheus metric types—Counters, Gauges, Histograms, and Summaries—along with practical code examples and usage considerations in cloud‑native environments.
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.
Learn step‑by‑step how to set up Prometheus and Grafana with a Spring Boot 2.4.12 application, configure dependencies, expose metrics via Actuator, customize meters, and monitor database connection pools, providing a complete observability solution for Java backend services.
The article explains how Google measures and improves software quality before release by separating development and operations responsibilities, using monorepo and trunk‑based development, daily release candidates, automated testing, performance benchmarks, and a comprehensive Project Health (pH) metric system that balances speed, reliability, and quality.
This article compares six open‑source log management platforms—OpenObserve, Grafana Loki, SigNoz, Graylog, Syslog‑ng, and Highlight.io—detailing their features, deployment options, advantages, and drawbacks to help you choose the most suitable solution for effective observability and system performance.
To give the business team a global, application‑level view of Pulsar performance, the team built a SkyWalking Java‑Agent plugin that automatically collects producer and consumer metrics from the Pulsar client, exposing latency, backlog and failure counts via Prometheus without modifying the client code.
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 define, measure, and improve microservice reliability using availability metrics, the four golden signals, RED and USE methods, and practical SLI/SLO and MTTR practices, offering concrete guidance for effective service governance.
This article explains why measuring software development productivity is challenging, introduces the concept of DevOps metrics, details the four DORA indicators and their performance levels, and discusses additional metrics such as cycle time, quality, customer and employee satisfaction, CI/CD health, uptime, and service level indicators to help teams monitor progress and identify problems.
The article explains why relying solely on SQL optimization often fails to resolve deep database performance problems, illustrating with real Oracle and domestic PostgreSQL‑compatible cases where I/O configuration, shared buffers, and system‑level metrics were essential to achieve stability.
This article examines Dewu Technology’s SQC (Supplier‑Quality‑Customer) quality management model, detailing its AI‑driven inspection and authentication, the comprehensive quality assurance system built on mechanisms, processes, methods and tools, the “Quality Month” initiative, the iteration quality score model, automation testing and traffic‑replay platforms, and the measurable improvements in software quality and production reliability.
This tutorial explains how to use Docker to deploy DBLE, Prometheus, and Grafana, configure JMX Exporter for JVM metrics, and create a monitoring dashboard that visualizes CPU, memory pool, GC, and thread statistics of DBLE instances.
The article analyses why many organizations stall during DevOps adoption, explains the underlying causes, discusses metric design and second‑order changes, and proposes organizational and technical strategies to cross the gap and achieve sustainable continuous delivery.
The article outlines a practical framework for business‑level monitoring in banking systems, describing three evolution stages, key metrics such as transaction success rates and volume spikes, concrete alert rules, and the technical challenges of data collection, standardization, and massive parameter management.
This article explains how Dubbo3’s new observability starter provides visual cluster metrics, full‑link tracing, multi‑dimensional monitoring, Prometheus/Grafana integration, and log management, offering practical steps and configurations for building a robust cloud‑native microservice observability platform.
This article describes Anjuke's R&D efficiency measurement framework, detailing its quality and efficiency metrics across project phases, the data collection and processing architecture, visualization dashboards, and analysis methods used to monitor and improve development productivity, reliability, and continuous delivery.
This comprehensive guide explains Prometheus fundamentals, its ecosystem, metric collection models, configuration, PromQL querying, custom exporters, Grafana visualization, and Alertmanager setup, providing step‑by‑step instructions and code examples for effective system monitoring and alerting.
This article shares practical experience building a payment data analysis system from scratch, explaining why data analysis matters, outlining a five‑stage framework, detailing metric design, and presenting common analytical methods such as funnel, multi‑dimensional, trend, comparison, Pareto, and cross analysis to drive product decisions.
This article summarizes a technical talk on the challenges of cloud‑native transformation, the design of an application‑centric observability platform using CMDB, Prometheus, Thanos and VictoriaMetrics, practical solutions for high‑cardinality metrics and alerting, and future directions such as eBPF and AI‑driven fault detection.
This guide explains how to set up Alibaba Cloud Observability Prometheus edition to monitor ClickHouse, covering ClickHouse fundamentals, metric collection, dashboard templates, alert rules, troubleshooting steps, and deployment options for both ACK and ECS environments.
Enterprise Architecture (EA) tools bring order to sprawling IT environments by cataloguing assets, breaking down silos, providing measurable metrics, automating data collection, and serving as a single source of truth, helping organizations make informed decisions while acknowledging the need for human oversight and data interpretation.
The article details how Shenwan Hongyuan Securities leveraged standardized DevOps practices and a continuous delivery pipeline to attain Level 3 maturity, improve security, accelerate delivery, and enhance overall competitiveness, illustrated through a Q&A session and key performance metrics.
This article explains performance monitoring concepts, lists essential metrics such as response time and CPU utilization, introduces popular monitoring tools like Prometheus and New Relic, and outlines a step‑by‑step process for selecting, configuring, visualizing, alerting, and continuously improving system performance.
The article details Taobao’s data‑driven approach to redesigning logistics information display and self‑service tickets—defining problems, preparing subjective and objective data, creating metrics, analyzing pain points, implementing timed soothing messages and proactive tickets, and showing through A/B tests reduced help volume and improved user satisfaction.
This article explains how HuoLaLa’s stability team tackled the challenge of proving their work’s value by designing and implementing a comprehensive stability metric system from scratch, detailing the motivations, principles, step‑by‑step construction, data platform, cultural adoption, measurable results, and future plans.
MyPerf4J is a Java‑agent based, low‑overhead performance monitoring library that provides real‑time method, memory, GC and class metrics for high‑concurrency, low‑latency applications, offering quick start, configurable properties, and detailed statistical reports for both development and production environments.
The author reflects on the shortcomings of current logging, metrics, and tracing practices, explains why they become costly and unscalable, and offers concrete recommendations—including log level discipline, structured logging, metric aggregation, and the use of tools like Prometheus, Cortex, and Thanos—to build a more efficient observability stack.
This article explains what an indicator system is, how to design and analyze metrics, methods for managing them, and the right mindset for using indicator systems to improve business decision‑making and operational efficiency.
This article examines the fairness of recommendation systems from both consumer and provider viewpoints, discussing sources of bias, definitions of equality and equity, measurement metrics such as CGF and MMF, causal embedding techniques, experimental results on MovieLens and Yelp, and future research directions.
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.
ICBC‑RS Fund Management’s Transaction Management Platform passed the China Academy of Information and Communications Technology’s DevOps Continuous Delivery Level 3 assessment, showcasing significant improvements in build times, release cycles, and organizational efficiency while highlighting the cultural and tooling benefits of standardized DevOps practices.
This article details how Shanghai Financial Futures' technology subsidiary passed the Level 3 Continuous Delivery assessment of the national DevOps maturity model, showcasing the platform’s cloud‑native architecture, metric‑driven improvements, challenges faced, and future plans for scaling DevOps practices across the exchange.
MyPerf4J is a Java‑agent based, low‑overhead monitoring solution that provides real‑time method, memory, GC and class metrics, enabling developers to quickly locate performance bottlenecks and assess service capacity in both development and production environments.
This article provides a comprehensive overview of enterprise architecture (EA) governance, covering its definition, context, framework components, guiding principles, organizational structure, roles and responsibilities, processes, classification, metrics, and tool selection to help organizations align IT with business strategy and achieve cost savings and compliance.
The article presents Tencent Oula's comprehensive data‑asset platform that integrates data collection, integration, warehouse and metric modeling, unified services, and a governance engine to create trustworthy, low‑entropy data assets while addressing common data‑governance challenges and outlining future AI‑for‑BI possibilities.
This article explains why tag scoring is essential for data governance, outlines a five‑dimensional scoring model—including usage, attention, quality, continuous optimization, and security—and demonstrates how the scores can drive dashboards, alerts, and resource‑saving decisions.
This article details JD's end‑to‑end H5 observability solution, covering the challenges of hybrid app development, the design of a three‑stage UEM platform, deep active and passive monitoring, automated quality gates, and real‑world case studies that demonstrate cost savings and performance improvements.
This guide explains how to use mimirtool to extract the list of metrics used in Grafana dashboards and Prometheus rule files, compare them with all metrics in a Prometheus instance, and generate files of used and unused metrics to help optimize monitoring in a Kubernetes environment.
This article explains what metrics are, outlines the four essential elements of a good metric, evaluates metrics across effectiveness, credibility, sensitivity, and operability, and provides a practical guide for building and applying a comprehensive data metric system, while also promoting a related ebook.
This article details Bilibili's journey from rapid data growth to a structured big‑data governance framework, describing the challenges of fragmented ownership, the "Wanglou" project launch, asset metadata modeling, metric design, user engagement strategies, automation tools, and the shift from reactive to proactive, multi‑dimensional resource management.
This tutorial explains how to gather build data from Jenkins pipelines, store the metrics in InfluxDB deployed on Kubernetes, and visualize the information using Grafana dashboards, providing a complete end‑to‑end solution for continuous delivery measurement and feedback.
An experienced Tencent backend engineer outlines five practical methodologies—quantification of technical and business metrics, systematic comparison of performance data, thorough documentation and defined processes, consistent standardization across code and tools, and extensive automation via CI/CD and testing—to boost efficiency, quality, and reliability in backend development.
This article explains why observability is critical in cloud‑native architectures and describes how Baidu’s search middle‑platform handles hundred‑billion‑level traffic by implementing low‑cost real‑time metrics, distributed tracing, log querying and topology analysis, while tackling challenges of massive microservice scale, scenario‑level monitoring, and efficient resource usage.
This article provides a detailed analysis of the OMS community edition 3.3.1 architecture, explains each internal process, describes the migration workflow and monitoring metrics, and offers practical optimization tips to improve data migration performance.
This article explains how to measure and improve R&D efficiency by defining core factors, building data‑driven analysis models, presenting practical case studies on human productivity, code‑review processes and workflow bottlenecks, and describing the technical architecture of a digital platform that turns metrics into actionable decisions.
This article explains the essential front‑end performance metrics—FCP, Speed Index, LCP, TBT, and CLS—detailing their definitions, target values, and practical optimization techniques to improve page load speed and visual stability.
This article explains how to design and implement a comprehensive front‑end monitoring solution that captures errors, performance metrics, and client data, covering data collection, tracing, transmission, storage, and analysis to help developers quickly locate and resolve issues.
This article explains what logs are, when to record them, their value in large‑scale architectures, and how to build effective logging, metrics, and tracing platforms using tools such as ELK, Prometheus, and SkyWalking, while also presenting good and bad logging practices and sample batch‑log retrieval code.
This article explains what logs are, when and why to record them, their value in large‑scale systems, the challenges of log management in micro‑service architectures, and how to design observability platforms using metrics, logging, tracing, and tools such as ELK, Prometheus, OpenTracing, and SkyWalking.
This article explains the fundamentals of A/B testing, why it is essential for data‑driven product decisions, how to design and run experiments—including hypothesis formulation, metric selection, sample size calculation, traffic segmentation, and duration planning—and how to analyze results using T‑tests, P‑values, and structured decision processes.
The article reflects on the 2020‑2022 subsidy wars in community e‑commerce, exposing classic growth misconceptions, the limits of traffic‑centric strategies, the pitfalls of single‑metric thinking, and the need for holistic, value‑driven product management to achieve sustainable user growth.
This article explores Kubernetes horizontal pod autoscaling mechanisms, comparing HPA and KEDA, their implementation principles, limitations, and practical deployment scenarios for cloud-native applications.
This article reviews G Bank's multi‑year journey to standardize application monitoring, detailing the methodology, models, metrics, automation mechanisms, and quantitative evaluation that together improve visibility, early fault detection, and overall operations management for both traditional and distributed systems.
This article explores why logs are essential in software development, when to record them, their value for debugging, performance, security and business decisions, and how distributed architectures require robust log‑operation tools such as ELK, Prometheus, tracing systems to achieve effective observability.
This article explains why data product value assessment is essential, outlines common usage scenarios and a DBA evaluation framework, describes quantitative methods such as usage, business, and data‑driven metrics, and offers practical ways to enhance data product value through metric optimization, high‑value direction selection, and resource allocation.
This article details Cloud Music's year‑long data assetization journey, covering the background, practical achievements, governance methods, and future roadmap for turning massive data warehouses into high‑value, well‑governed assets that drive cost reduction and business insight.
This article clarifies the often‑confused concepts of system stability, high availability, reliability and availability, explains their metrics such as MTBF, MTTR and MTTF, and shows how they interrelate to guide engineers in building resilient services.
The article examines Go’s database/sql connection pool implementation, showing how reusing connections cuts latency, explains idle/in‑use/closed state transitions, details configuration parameters such as MaxIdleConns and MaxOpenConns, demonstrates metric collection via Gorm DBStats for monitoring, and provides a stress‑test illustrating the impact of proper tuning.
This article details Kuashou's metric middle platform, covering its role as a semantic layer, the unified architecture of OneMetric and OneService, metric standardization processes, automated modeling techniques, the Headless BI concept, and future directions for intelligent modeling and acceleration.
This article shares practical insights from a data product expert on the problems faced by content‑oriented data products, outlines a comprehensive governance methodology—including DAMA, Huawei, and Alibaba frameworks—and demonstrates how to operationalize these ideas through concrete examples such as event‑tracking and metric governance.
This article benchmarks Alibaba Cloud Prometheus against the open‑source Prometheus across multiple cluster sizes, churn rates, and query patterns, revealing that while the open‑source version remains stable under light load, its CPU and memory usage grow non‑linearly with high cardinality, whereas Alibaba's managed service delivers higher compatibility, better query performance, and more predictable scaling.
This article explains essential front‑end performance metrics such as FP, FCP, LCP, TTI, FID, TBT and CLS, and provides a comprehensive set of network, code, CSS, image, and build‑time optimization techniques—including gzip, HTTP/2, lazy loading, SSR, debouncing, and tree‑shaking—to dramatically shorten white‑screen time and improve user experience on H5 pages.
This guide explains essential Redis monitoring metrics, the tools and commands for collecting performance, memory, activity, persistence, and error data, and shows how to use INFO, slowlog, and redis-benchmark to assess and improve database operations.
This article presents the JD Retail search data‑science team's practical approaches to e‑commerce search, covering the scene’s unique data characteristics, order attribution methods, AB experiment design, causal‑inference frameworks, variance‑reduction techniques, quasi‑experimental evaluations, and metric design for traffic distribution, all illustrated with real‑world examples and visualizations.
The article examines common pitfalls when introducing performance metrics in software development teams, offering five key considerations—metric selection, implementation cost, proper usage, clear value, and team consensus—to ensure metrics drive improvement without adding unnecessary burden.
Facing the challenges of distributed microservice architectures, a financial services company implemented a unified observability platform that combines metrics, tracing, and logging via OpenTelemetry and custom agents, enabling real‑time visualization, anomaly detection, and performance analysis across seven core business middle‑platforms.
The article reviews traditional availability metrics such as Success‑Ratio, Error‑Budget, MTTR/MTTF, SLA/SLO, and highlights their limitations, then introduces Google’s User‑Uptime and Windowed User‑Uptime metrics, explains their definitions, challenges, experimental results, and why they provide a more user‑centric view of service reliability.
The platform centralizes message‑center management for e‑commerce by adding end‑to‑end tracing, real‑time metrics, and unified logging, enabling business users to query message links, view dashboards, automate retries and approvals, dramatically reducing manual monitoring, improving completion rates above 90%, and paving the way for cost‑optimized, data‑driven operations.
The article outlines JD's data‑driven business development strategy, describing the current challenges of its business data marketplace, the governance framework—including layered architecture, standardization, ClickHouse dictionary refresh, and optimization measures—and the resulting performance improvements and future outlook.
The paper presents a two‑stage e‑commerce search framework where the coarse‑ranking stage is redesigned with multi‑objective optimization, expanded negative sampling, and listwise distillation—guided by a new global transaction hitrate metric—enabling it to surpass fine‑ranking on large candidate sets and boost overall GMV by about one percent.
This article explains how to design effective Prometheus metrics, choose appropriate labels and buckets, and leverage Grafana visualizations to monitor online services, offline processing, and batch jobs, offering concrete examples and best‑practice recommendations for reliable application observability.
This article examines how fragmented metrics and local optimizations can harm overall software quality, discussing the bug‑vs‑feature debate, various measurement approaches, and the importance of viewing quality as a collective team capability rather than an individual or departmental responsibility.
This article summarizes four years of agile transformation in the JD Cloud Platform R&D department, detailing cultural building, continuous agile practices, practical guidelines, effectiveness measurement, and insight analysis across five key areas to improve organizational, technical, and project agility.
