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observability

1324 articles · Page 14 of 14
JD Retail Technology
JD Retail Technology
Jul 24, 2018 · Operations

Stability and Operational Practices for Large‑Scale Kubernetes Clusters

This article shares practical experience and best‑practice guidelines for operating large‑scale Kubernetes clusters, covering stability checks, component failure impact, recovery strategies, alerting mechanisms, data collection, visualization, and the suite of operational tools that help ensure reliable, high‑performance cloud‑native infrastructure.

Cluster OperationsKuberneteshigh availability
0 likes · 10 min read
Stability and Operational Practices for Large‑Scale Kubernetes Clusters
UCloud Tech
UCloud Tech
Jul 18, 2018 · Operations

How to Build a Unified Monitoring System for Microservices: Key Dimensions & Scenarios

This article explains how microservice architectures require a comprehensive monitoring system, covering data, resource, and code dimensions, and describes eight atomic monitoring scenarios such as URL, host, product, component, custom, resource, APM, and event monitoring to help engineers design effective observability solutions.

APMOperationscloud-native
0 likes · 7 min read
How to Build a Unified Monitoring System for Microservices: Key Dimensions & Scenarios
Architecture Digest
Architecture Digest
May 8, 2018 · Backend Development

Design and Comparison of Distributed Tracing Systems

The article explains the concept, functions, design goals, data models, log collection, and deployment considerations of distributed tracing systems, and compares several open‑source and proprietary solutions such as Dapper, Zipkin, Pinpoint, Alibaba Eagle Eye, and JD Hydra to guide the selection of an appropriate tracing platform.

BackendMicroservicesPerformance Monitoring
0 likes · 16 min read
Design and Comparison of Distributed Tracing Systems
dbaplus Community
dbaplus Community
Apr 24, 2018 · Cloud Native

How Istio Simplifies Service Mesh Management for Kubernetes Microservices

This article explains why microservice architectures need reliable communication, load balancing, fault tolerance, monitoring, tracing and circuit breaking, and shows how Istio—a cloud‑native service mesh built on Envoy—provides these capabilities, enabling blue‑green and canary deployments, traffic routing, retries, and observability within Kubernetes.

Blue-Green DeploymentIstioKubernetes
0 likes · 8 min read
How Istio Simplifies Service Mesh Management for Kubernetes Microservices
Efficient Ops
Efficient Ops
Apr 2, 2018 · Operations

How Bilibili Revamped Its Monitoring Architecture: From Zabbix to Dapper

An in‑depth look at Bilibili’s multi‑layer monitoring overhaul, detailing the shift from a monolithic Zabbix setup to micro‑service‑based ELK, Dapper, Misaka, Traceon and Lancer systems, and how layered observability improves fault detection across business, application, and infrastructure levels.

MicroservicesOperationsdistributed tracing
0 likes · 10 min read
How Bilibili Revamped Its Monitoring Architecture: From Zabbix to Dapper
Programmer DD
Programmer DD
Feb 23, 2018 · Operations

How Zipkin Collects and Processes Sleuth Tracing Data – Deep Dive into Spans

This article explains Zipkin’s data model, how Spring Cloud Sleuth generates and sends Span and Annotation information, the message‑channel listener that converts Sleuth spans to Zipkin spans, debugging techniques to observe the collected data, and why the number of spans shown in Zipkin’s UI can differ from the raw count.

MicroservicesSpring Cloud SleuthZipkin
0 likes · 17 min read
How Zipkin Collects and Processes Sleuth Tracing Data – Deep Dive into Spans
Hujiang Technology
Hujiang Technology
Jan 29, 2018 · Operations

Design and Implementation of a Low‑Impact Distributed Tracing System for Service Calls

This article describes the background, design goals, architecture, implementation details, and lessons learned from building a low‑overhead, low‑intrusion distributed tracing system using Kafka, Elasticsearch, and OpenTracing to monitor microservice interactions and support performance analysis and DevOps decision‑making.

ElasticsearchKafkaMicroservices
0 likes · 9 min read
Design and Implementation of a Low‑Impact Distributed Tracing System for Service Calls
Node Underground
Node Underground
Jan 12, 2018 · Backend Development

Unlocking Pandora.js: Manageable, Measurable, Traceable Node.js Applications

Pandora.js, the Alibaba Midway team's first open-source project, consolidates years of production-grade Node.js operations by offering three core capabilities—manageable application and process control, comprehensive metrics, and Open-Tracing-based request tracing—exposed via RESTful APIs and logs for easy integration.

BackendNode.jsOpenTracing
0 likes · 2 min read
Unlocking Pandora.js: Manageable, Measurable, Traceable Node.js Applications
Taobao Frontend Technology
Taobao Frontend Technology
Jan 5, 2018 · Operations

Why Metrics Matter: A Deep Dive into Pandora.js’s Measurement System

Metrics act as health checks for applications, enabling developers to monitor performance, track changes, and assess stability; this article explains Pandora.js’s metric naming conventions, types like Gauge, Counter, Histogram, and Meter, and provides practical Node.js code examples for implementing these measurements.

Performancemetricsmonitoring
0 likes · 13 min read
Why Metrics Matter: A Deep Dive into Pandora.js’s Measurement System
Efficient Ops
Efficient Ops
Dec 18, 2017 · Operations

How WiFi Key Built a Million‑User Monitoring Platform: Architecture and Best Practices

This article describes how WiFi 万能钥匙 designed and implemented the Roma monitoring platform to handle billions of daily requests, covering background challenges, architectural principles, component design, data collection, transmission, storage, alerting, and future directions for large‑scale observability.

ArchitectureMicroservicesOperations
0 likes · 16 min read
How WiFi Key Built a Million‑User Monitoring Platform: Architecture and Best Practices
Tencent Database Technology
Tencent Database Technology
Nov 21, 2017 · Operations

Introduction to ELKB: Architecture, Components, and Typical Use Cases of Elasticsearch, Logstash, Kibana, and Beats

The article introduces the ELKB stack—a combination of Elasticsearch, Logstash, Kibana, and Beats—explaining its background, user needs, architecture, component functions, typical scenarios, and the team’s practical implementations for real‑time log and time‑series data processing.

BeatsELKElasticsearch
0 likes · 10 min read
Introduction to ELKB: Architecture, Components, and Typical Use Cases of Elasticsearch, Logstash, Kibana, and Beats
Dada Group Technology
Dada Group Technology
Oct 27, 2017 · Operations

Pinpoint Overview and Plugin Development Guide

Pinpoint is a full‑stack, non‑intrusive tracing platform that visualizes service topology, active threads, request latency, and application health, and this article explains its architecture, data model, and step‑by‑step process for creating custom plugins—including ServiceLoader configuration, TraceMetadataProvider, and ProfilerPlugin implementations with code examples.

APMJavaPinpoint
0 likes · 22 min read
Pinpoint Overview and Plugin Development Guide
Qunar Tech Salon
Qunar Tech Salon
Oct 26, 2017 · Operations

Evolution of Pinterest's Monitoring System: From Time-Series Metrics to Distributed Tracing

Over seven years, Pinterest’s monitoring team built and refined a three‑pronged observability platform—time‑series metrics, log search, and distributed tracing—scaling from a single‑machine system to handling millions of data points per second across tens of thousands of AWS VMs, while addressing reliability, cost, and usability challenges.

Cloud InfrastructureSREdistributed tracing
0 likes · 19 min read
Evolution of Pinterest's Monitoring System: From Time-Series Metrics to Distributed Tracing
Meitu Technology
Meitu Technology
Sep 28, 2017 · Operations

Inside Meipai’s 3‑D Monitoring System: Scaling 150M Users with Unified Observability

This article examines how Meipai, a popular live‑streaming and short‑video platform with over 150 million monthly active users, engineered a comprehensive, three‑dimensional monitoring architecture that spans client to server, integrates unified dashboards, and leverages both private and public cloud resources to ensure reliable, scalable operations.

DevOpsInfrastructureMeipai
0 likes · 3 min read
Inside Meipai’s 3‑D Monitoring System: Scaling 150M Users with Unified Observability
Qunar Tech Salon
Qunar Tech Salon
Aug 14, 2017 · Backend Development

Introduction to QTracer: An Internal Distributed Tracing System at Qunar

QTracer is Qunar’s internal distributed tracing system that generates a global TraceID for each request, records operations across services, and provides features such as execution chain visualization, log correlation, conditional search, service dependency analysis, database statistics, transparent data propagation, and low‑overhead instrumentation for debugging and performance monitoring.

BackendQTracerdistributed tracing
0 likes · 20 min read
Introduction to QTracer: An Internal Distributed Tracing System at Qunar
Ctrip Technology
Ctrip Technology
Aug 10, 2017 · Operations

QTracer: An In‑Depth Overview of Qunar’s Distributed Tracing System

This article provides a comprehensive technical overview of QTracer, Qunar’s internal distributed tracing platform, covering its architecture, core concepts, key features such as execution‑chain queries, log association, conditional searches, data storage, non‑intrusive instrumentation, bytecode injection, and the QTracer Debug tool for online breakpoint debugging.

BackendJavaQTracer
0 likes · 19 min read
QTracer: An In‑Depth Overview of Qunar’s Distributed Tracing System
Beike Product & Technology
Beike Product & Technology
Jul 16, 2017 · Industry Insights

How Lianjia Built LTrace: A Low‑Overhead, Scalable Distributed Tracing Platform

This article explains how Lianjia designed and implemented LTrace, a zero‑intrusion, high‑performance distributed tracing system that captures full request chains across heterogeneous services, supports multi‑language environments, offers flexible sampling, and enables rapid fault isolation and performance optimization.

ArchitectureLow Overheaddistributed tracing
0 likes · 12 min read
How Lianjia Built LTrace: A Low‑Overhead, Scalable Distributed Tracing Platform
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Jun 20, 2017 · Cloud Native

How Uber Built Jaeger: From In‑House Tracing to a Cloud‑Native Open‑Source Platform

Uber’s engineering team chronicles the evolution of its distributed tracing system—from the early Merckx pull‑based solution and TChannel integration to the open‑source Jaeger platform—detailing architectural shifts, sampling strategies, multi‑language client libraries, and the move toward a fully cloud‑native, end‑to‑end observability stack.

Cloud NativeJaegerMicroservices
0 likes · 17 min read
How Uber Built Jaeger: From In‑House Tracing to a Cloud‑Native Open‑Source Platform
Efficient Ops
Efficient Ops
Mar 1, 2017 · Operations

How Metrics-Driven Development Transforms Software Iteration and Ops

Metrics‑Driven Development (MDD) extends test‑driven principles by embedding real‑time monitoring into design, enabling rapid, precise, and granular software iterations, improving early problem detection, decision support, and aligning development with DevOps culture.

metricsmonitoringobservability
0 likes · 13 min read
How Metrics-Driven Development Transforms Software Iteration and Ops
Node Underground
Node Underground
Jan 24, 2017 · Operations

11 Essential Practices to Master Node.js Application Monitoring

Effective Node.js monitoring boosts competitiveness, user experience, and cost efficiency, and this guide outlines eleven key recommendations—from tracking downtime and response thresholds to linking performance with business metrics and leveraging third‑party APM tools—ensuring robust, noise‑free alerts and secure, scalable applications.

APMDevOpsNode.js
0 likes · 3 min read
11 Essential Practices to Master Node.js Application Monitoring
dbaplus Community
dbaplus Community
May 11, 2016 · Operations

Inside Twitter’s Massive Monitoring Stack: Architecture, Metrics, and Lessons Learned

Twitter’s internal monitoring team built a full‑stack observability platform that handles billions of metric writes per minute, supports distributed tracing, log aggregation, visual dashboards, and alerting across data centers and public clouds, and shares the architecture, components, and key lessons learned.

AlertingTwitterdistributed tracing
0 likes · 18 min read
Inside Twitter’s Massive Monitoring Stack: Architecture, Metrics, and Lessons Learned
dbaplus Community
dbaplus Community
Apr 11, 2016 · Operations

Can External Quality Acceptance Drive DevOps Monitoring and Eliminate Technical Debt?

This article explains how focusing on non‑functional quality during external acceptance testing can drive DevOps teams to improve system monitorability, reduce technical debt, and establish concrete change‑control, acceptance, and performance verification processes for both operational and business‑level observability.

DevOpschange managementobservability
0 likes · 15 min read
Can External Quality Acceptance Drive DevOps Monitoring and Eliminate Technical Debt?
21CTO
21CTO
Mar 20, 2016 · Operations

How CAT Powers Real‑Time Distributed Monitoring at Scale

This article introduces CAT, a Java‑based open‑source distributed real‑time monitoring system, covering its origins, design goals, architecture, message processing pipeline, instrumentation model, and how it achieves high availability, scalability, and low‑latency analytics for large‑scale internet services.

ArchitectureCATDistributed Monitoring
0 likes · 17 min read
How CAT Powers Real‑Time Distributed Monitoring at Scale