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MaGe Linux Operations
MaGe Linux Operations
Sep 28, 2022 · Operations

Mastering System and Application Monitoring with the USE Method and Prometheus

Effective monitoring combines comprehensive system and application metrics—using the USE (Utilization, Saturation, Errors) method to pinpoint resource bottlenecks, and leveraging tools like Prometheus, Grafana, and ELK stacks for data collection, storage, querying, alerting, visualization, and full‑stack tracing across distributed services.

ELKPrometheusUSE
0 likes · 14 min read
Mastering System and Application Monitoring with the USE Method and Prometheus
Huolala Tech
Huolala Tech
Sep 22, 2022 · Operations

How HuoLala Engineered a Scalable, High‑Availability Monitoring System for Multi‑Cloud

This article details the evolution of monitoring technologies, HuoLala's three‑phase monitoring architecture, the integration of Prometheus, VictoriaMetrics and SkyWalking, zero‑intrusion bytecode instrumentation, full‑link trace sampling, visual dashboards, metric‑trace‑log correlation, and future plans for root‑cause analysis and intelligent alerting.

Operationsbytecodecloud
0 likes · 24 min read
How HuoLala Engineered a Scalable, High‑Availability Monitoring System for Multi‑Cloud
Baidu Geek Talk
Baidu Geek Talk
Sep 14, 2022 · Mobile Development

How Baidu Boosted Android App Startup Using Perfetto and Auto-Instrumentation

This article details Baidu's comprehensive approach to improving Android app launch performance by evaluating existing tracing tools, selecting Perfetto, developing a Gradle-based automatic instrumentation plugin, handling trace collection and analysis with Trace Processor, and implementing automated detection of regressions, lock contention, and method-level CPU and wall‑time degradations.

AndroidInstrumentationPerfetto
0 likes · 28 min read
How Baidu Boosted Android App Startup Using Perfetto and Auto-Instrumentation
Efficient Ops
Efficient Ops
Sep 7, 2022 · Operations

How DeepFlow Automates Full‑Stack Observability for Cloud‑Native Environments

This article presents DeepFlow, an open‑source, highly automated observability platform that uses eBPF to provide zero‑code AutoMetrics and AutoTracing, integrates with Prometheus, OpenTelemetry and SkyWalking, and enables SRE, DevOps and NewOps teams to build full‑stack metrics and blind‑spot‑free tracing for cloud‑native applications.

DevOpsMetricscloud-native
0 likes · 20 min read
How DeepFlow Automates Full‑Stack Observability for Cloud‑Native Environments
Tencent Cloud Developer
Tencent Cloud Developer
Sep 7, 2022 · Cloud Native

Why Build Probe Capabilities Based on OpenTelemetry for Cloud‑Native Observability

Building probe capabilities on OpenTelemetry gives cloud‑native teams a vendor‑neutral, standardized way to extend monitoring into full observability—supporting large‑scale, language‑specific instrumentation, plug‑and‑play plugins, and seamless integration with APM backends—so developers and operators can detect, debug, and predict faults across distributed containers.

APMCloud NativeNode.js
0 likes · 15 min read
Why Build Probe Capabilities Based on OpenTelemetry for Cloud‑Native Observability
dbaplus Community
dbaplus Community
Aug 24, 2022 · Backend Development

From Monolith to Microservices: Transforming an Online Supermarket

This article walks through the evolution of an online supermarket from a simple monolithic web app to a fully fledged microservice architecture, detailing the motivations, design decisions, component breakdown, common pitfalls, and essential practices such as monitoring, tracing, logging, service discovery, resilience patterns, testing, and the role of service meshes.

MicroservicesService Meshcircuit breaker
0 likes · 24 min read
From Monolith to Microservices: Transforming an Online Supermarket
Baidu Geek Talk
Baidu Geek Talk
Jul 19, 2022 · Cloud Native

How OpenTelemetry and Jaeger Power Cloud‑Native Tracing

This article explains cloud‑native observability, defines its three pillars—metrics, tracing, and logging—details the OpenTelemetry tracing data model and Span structure, reviews industry implementations such as Jaeger and Alibaba Eagle Eye, and shares practical challenges and solutions from real‑world production use.

Alibaba Eagle EyeCloud NativeDistributed Systems
0 likes · 11 min read
How OpenTelemetry and Jaeger Power Cloud‑Native Tracing
Cognitive Technology Team
Cognitive Technology Team
Jun 17, 2022 · Backend Development

Why CompletableFuture’s Asynchronous Methods Should Use an Explicitly Provided Thread Pool

The article explains that CompletableFuture offers paired asynchronous methods—one using the default ForkJoinPool and another accepting a custom executor—and argues that providing an explicit thread pool avoids shared‑pool contention, loss of tracing information, ThreadLocal leakage, and class‑loader issues in Java backend applications.

AsynchronousCompletableFutureSpring Cloud
0 likes · 5 min read
Why CompletableFuture’s Asynchronous Methods Should Use an Explicitly Provided Thread Pool
Top Architect
Top Architect
Jun 2, 2022 · Cloud Native

A Beginner's Guide to Designing, Implementing, and Deploying Microservices on Kubernetes

This article walks readers through the complete lifecycle of a microservice system—from architectural design and Java Spring Boot implementation to Kubernetes deployment, high‑availability setup, monitoring with Prometheus/Grafana, tracing with Zipkin, and flow‑control with Sentinel—providing practical code snippets and step‑by‑step instructions.

KubernetesMicroservicescloud-native
0 likes · 21 min read
A Beginner's Guide to Designing, Implementing, and Deploying Microservices on Kubernetes
Ops Development Stories
Ops Development Stories
May 18, 2022 · Cloud Native

Mastering K8s Application Lifecycle: Health Checks, Graceful Shutdown, Metrics & Tracing

This article explains how developers and operators should prepare a Go‑based service for Kubernetes by implementing health‑check endpoints, graceful shutdown handling, metrics exposure, tracing integration, standardized logging, and operational best practices such as stateless design, high availability, self‑healing, and HTTPS configuration.

DevOpsGraceful ShutdownKubernetes
0 likes · 20 min read
Mastering K8s Application Lifecycle: Health Checks, Graceful Shutdown, Metrics & Tracing
Cognitive Technology Team
Cognitive Technology Team
Apr 29, 2022 · Backend Development

Spring Cloud Managed Thread Pools Are Automatically Wrapped with Trace Information to Preserve Context

This article explains how Spring Cloud automatically wraps container‑managed thread pool beans with tracing proxies to preserve distributed‑trace information, details the ExecutorBeanPostProcessor implementation, shows the relevant code for detecting and instrumenting executors, and notes when manual wrapping is required.

Spring BootSpring Cloudjava
0 likes · 6 min read
Spring Cloud Managed Thread Pools Are Automatically Wrapped with Trace Information to Preserve Context
DevOps
DevOps
Apr 12, 2022 · Operations

Understanding Observability: Core Concepts, SRE Methodology, AIOps, and Business Architecture

The article explains the rising importance of observability in modern operations, defines its control‑theory roots, breaks it down into metrics, traces and logs, and argues that successful implementation requires three pillars—SRE practices, AIOps algorithms, and deep business‑architecture knowledge—together with well‑designed SLOs and critical‑path mapping.

SREaiopsbusiness architecture
0 likes · 10 min read
Understanding Observability: Core Concepts, SRE Methodology, AIOps, and Business Architecture
StarRocks
StarRocks
Mar 28, 2022 · Backend Development

Scaling Microservice Tracing with Zipkin and StarRocks: A Practical Guide

This article explains how Sohu Smart Media built a high‑performance tracing system for microservices by integrating Zipkin for data collection with StarRocks for storage and analytics, covering architecture, data models, SQL queries, Flink processing, and real‑world results that boost observability and engineering efficiency.

FlinkMicroservicesStarRocks
0 likes · 31 min read
Scaling Microservice Tracing with Zipkin and StarRocks: A Practical Guide
Efficient Ops
Efficient Ops
Mar 2, 2022 · Operations

Mastering System & Application Monitoring with the USE Method and Prometheus

This article explains how to build a comprehensive monitoring system for both infrastructure and applications, introducing the USE (Utilization‑Saturation‑Errors) method, key performance metrics, and practical components such as Prometheus, Grafana, full‑link tracing, and the ELK stack to detect and diagnose performance bottlenecks.

MetricsPrometheusUSE method
0 likes · 13 min read
Mastering System & Application Monitoring with the USE Method and Prometheus
MaGe Linux Operations
MaGe Linux Operations
Jan 22, 2022 · Operations

Introducing RTLA: The New Real‑Time Linux Analysis Tool in Kernel 5.17

RTLA (real‑time Linux analysis tool), developed by Red Hat kernel engineer Daniel Bristot de Oliveira, has been merged into the Linux 5.17 source tree, offering kernel‑level tracing of OS noise and timer latency, command‑line options for high‑priority task delay reporting, and trace output for debugging real‑time performance.

Real-Timeperformancertla
0 likes · 3 min read
Introducing RTLA: The New Real‑Time Linux Analysis Tool in Kernel 5.17
Tencent Cloud Developer
Tencent Cloud Developer
Dec 23, 2021 · Cloud Native

An Overview of OpenTelemetry: Origins, Architecture, and Instrumentation

OpenTelemetry unifies tracing, metrics, and logs by merging OpenTracing and OpenCensus into a cross‑language specification, collector, language SDKs, and instrumentation libraries, offering vendor‑agnostic, low‑maintenance telemetry collection that separates data gathering from business logic while requiring external back‑ends for storage and analysis.

Cloud NativeCollectorInstrumentation
0 likes · 10 min read
An Overview of OpenTelemetry: Origins, Architecture, and Instrumentation
Alibaba Cloud Native
Alibaba Cloud Native
Dec 7, 2021 · Cloud Native

Unlocking the Third Way of Distributed Tracing: Post‑Aggregation Link Analysis Explained

This article introduces the third, post‑aggregation approach to link tracing—link analysis—showing how real‑time aggregation of stored trace data can quickly pinpoint uneven traffic, single‑machine failures, slow interfaces, business‑level traffic shifts, and gray‑release anomalies while outlining its practical constraints.

APMCloud NativeLink Analysis
0 likes · 11 min read
Unlocking the Third Way of Distributed Tracing: Post‑Aggregation Link Analysis Explained
Baidu Intelligent Testing
Baidu Intelligent Testing
Sep 9, 2021 · Cloud Native

Observability Practices in Baidu Search Platform: Real‑time Metrics, Tracing, Logging, and Topology at Hundred‑Billion Scale

This article explains how Baidu's search middle‑platform adopts cloud‑native observability—covering metrics, distributed tracing, log querying, and topology analysis—to ensure high availability, performance, and controllability for a system handling hundreds of billions of requests across millions of micro‑service instances.

loggingobservabilitytopology
0 likes · 12 min read
Observability Practices in Baidu Search Platform: Real‑time Metrics, Tracing, Logging, and Topology at Hundred‑Billion Scale
Java Interview Crash Guide
Java Interview Crash Guide
Jul 23, 2021 · Operations

How to Build a Scalable APM System: Inside the Dog Architecture

This article explains what an APM system is, compares logs, traces and metrics, reviews popular tools, and then details the design and implementation of the in‑house Dog APM platform—including client data models, Kafka pipelines, processing pipelines, storage in ClickHouse/Cassandra, and UI visualizations.

APMKafkaMetrics
0 likes · 28 min read
How to Build a Scalable APM System: Inside the Dog Architecture
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Jul 14, 2021 · Backend Development

Adaptive Sampling: Dynamically Tuning Tracing to Cut Overhead

This article explains how adaptive sampling reduces the performance and storage impact of full‑link tracing by dynamically adjusting the sampling rate based on application QPS, outlines the mathematical model, discusses implementation details such as warm‑up, QPS lag, concurrency, and provides a Java reference sampler.

Adaptive SamplingQPSreservoir-sampling
0 likes · 9 min read
Adaptive Sampling: Dynamically Tuning Tracing to Cut Overhead
21CTO
21CTO
Jul 11, 2021 · Operations

How Baidu Achieved 5‑9+ Availability: Inside Its Tracing and Observability Innovations

This article examines Baidu Search's massive micro‑service architecture and reveals the detailed observability, tracing, and metrics techniques—Kepler 1.0, Kepler 2.0, and Prometheus integration—that enable five‑nine‑plus availability, full‑query debugging, and efficient capacity management.

AvailabilityMicroservicestracing
0 likes · 19 min read
How Baidu Achieved 5‑9+ Availability: Inside Its Tracing and Observability Innovations
Amap Tech
Amap Tech
May 28, 2021 · Operations

System Observability Practices in Gaode Ride-Hailing: From Unified Logging to Fault Defense

Gaode Ride‑Hailing created a comprehensive 360° observability platform—standardized logging, distributed tracing, multi‑domain metrics, visual dashboards, and an incident workflow—that transforms raw data into actionable insights, accelerates root‑cause analysis, and enables automated fault defense for its large‑scale cloud‑native microservice system.

Distributed Systemsfault tolerancelogging
0 likes · 22 min read
System Observability Practices in Gaode Ride-Hailing: From Unified Logging to Fault Defense
Alibaba Cloud Native
Alibaba Cloud Native
Mar 31, 2021 · Operations

What Is OpenTelemetry? A Deep Dive into Its Architecture, History, and Go Demo

OpenTelemetry, a CNCF observability project, standardizes telemetry data models, collection, processing, and export, offering vendor‑agnostic APIs, SDKs, and a configurable collector; the article explains its problem domain, solution components, history, future outlook, and provides a practical Go demo with code and configuration examples.

CNCFCollectorGo
0 likes · 11 min read
What Is OpenTelemetry? A Deep Dive into Its Architecture, History, and Go Demo
Selected Java Interview Questions
Selected Java Interview Questions
Jan 16, 2021 · Backend Development

Performance Optimization of Business Engine Interfaces: Tracing, Local Analysis, and Practical Techniques

The article outlines a systematic approach to optimizing microservice interface performance by using call‑chain tracing with Kibana, local profiling with DotTrace, and concrete optimization tactics such as batching I/O, improving database queries, caching results, parallelizing calls, and asynchronous processing.

dottraceoptimizationtracing
0 likes · 5 min read
Performance Optimization of Business Engine Interfaces: Tracing, Local Analysis, and Practical Techniques
Code Ape Tech Column
Code Ape Tech Column
Nov 27, 2020 · Operations

From Monolith to Microservices: Real‑World Lessons and Practical Strategies

This article walks through the evolution of an online supermarket from a simple monolithic website to a fully split microservice architecture, highlighting the pitfalls of ad‑hoc growth, the need for service abstraction, monitoring, tracing, fault tolerance, testing, and the trade‑offs of frameworks versus service mesh.

MicroservicesService Mesharchitecture
0 likes · 24 min read
From Monolith to Microservices: Real‑World Lessons and Practical Strategies
Programmer DD
Programmer DD
Nov 21, 2020 · Operations

When to Use Monitoring, Tracing, or Logging? A Practical Guide

This article explains the distinct purposes and characteristics of monitoring, tracing, and logging in system design, compares their typical toolchains such as Prometheus, Jaeger, and ELK, and clarifies when each component is necessary for effective observability.

ELKjaegerobservability
0 likes · 7 min read
When to Use Monitoring, Tracing, or Logging? A Practical Guide
Sohu Tech Products
Sohu Tech Products
Aug 26, 2020 · Operations

Production Environment Optimization: Deep Dive into GC, Tracing, and Connection‑Pool Issues

This article walks through a real‑world production incident involving intermittent interface timeouts, demonstrates how tracing with SkyWalking and log analysis revealed a downstream service problem, explores GC log diagnostics, uncovers misconfigured c3p0 connection‑pool settings, and shares practical lessons for Java backend performance tuning.

Connection Poolgcjava
0 likes · 21 min read
Production Environment Optimization: Deep Dive into GC, Tracing, and Connection‑Pool Issues
Java Architect Essentials
Java Architect Essentials
Aug 26, 2020 · Backend Development

A Comprehensive Guide to Evolving a Monolithic Online Store into a Robust Microservice Architecture

This article walks through the transformation of a simple online supermarket from a monolithic design to a fully fledged microservice system, explaining the motivations, architectural changes, component selection, common pitfalls, and best‑practice solutions such as service decomposition, database sharding, monitoring, tracing, service mesh, resilience patterns, and testing strategies.

MicroservicesResiliencearchitecture
0 likes · 22 min read
A Comprehensive Guide to Evolving a Monolithic Online Store into a Robust Microservice Architecture
Efficient Ops
Efficient Ops
Jun 28, 2020 · Operations

How Observability Redefines Modern Monitoring: Metrics, Logs, Tracing, Events

Modern monitoring has evolved into comprehensive observability, encompassing metrics, logging, tracing, and events, and requires specialized storage solutions for each data type; this article explores the origins, key concepts, and design considerations for building effective observability systems in today's complex internet engineering landscape.

Eventsobservabilitytracing
0 likes · 9 min read
How Observability Redefines Modern Monitoring: Metrics, Logs, Tracing, Events
iQIYI Technical Product Team
iQIYI Technical Product Team
May 29, 2020 · Big Data

iQiyi's Full-Link Automated Monitoring Platform: Design and Implementation

iQiyi’s full‑link automated monitoring platform unifies tracing, metric and log collection with deep offline and real‑time analysis, delivering a DAG‑based call graph, near‑real‑time ingestion of tens of millions of logs, multi‑dimensional alerts and rapid root‑cause diagnosis that cut error‑lookup time by over 50 % and now serves as a core component of the company’s microservice reference architecture.

Big DataMetricsarchitecture
0 likes · 12 min read
iQiyi's Full-Link Automated Monitoring Platform: Design and Implementation
Yanxuan Tech Team
Yanxuan Tech Team
May 25, 2020 · Operations

How NetEase Cloud Music Built a Scalable Full‑Link Tracing System for Real‑Time Service Diagnosis

This article details the design, implementation, and evolution of NetEase Cloud Music's full‑link tracing platform, covering its motivations, architecture, low‑overhead data collection, multi‑dimensional analysis, service grooming, automated diagnosis, and future plans for AI‑driven anomaly detection and big‑data processing.

Distributed Systemsobservabilityservice monitoring
0 likes · 19 min read
How NetEase Cloud Music Built a Scalable Full‑Link Tracing System for Real‑Time Service Diagnosis
Efficient Ops
Efficient Ops
May 17, 2020 · Operations

How EMonitor Outperforms CAT: Deep Dive into Modern Monitoring Architecture

EMonitor, Meituan’s unified monitoring platform, extends CAT’s concepts with real‑time 10‑second aggregation, richer metric types, advanced dashboards, and seamless integration across IaaS, PaaS, and application layers, illustrating the evolution from log‑based monitoring to a comprehensive, proactive observability system.

CATEMonitorOperations
0 likes · 15 min read
How EMonitor Outperforms CAT: Deep Dive into Modern Monitoring Architecture
Didi Tech
Didi Tech
Jan 5, 2020 · Backend Development

Investigation and Optimization of High‑Frequency Go Service Timeout in Containers

The study traced severe Redis latency spikes in an 8‑core container to the Go runtime mistakenly reading the host’s CPU count, which created hundreds of threads and scheduler contention; limiting GOMAXPROCS to the container’s quota eliminated the jitter, while further gains were suggested by reducing HMGET calls, tuning GC, and upgrading Go.

CPUContainerGOMAXPROCS
0 likes · 14 min read
Investigation and Optimization of High‑Frequency Go Service Timeout in Containers
Java Captain
Java Captain
Sep 19, 2019 · Backend Development

A Comprehensive Overview of Microservice Architecture and Its Evolution

This article presents a detailed, step‑by‑step illustration of microservice architecture, covering its motivations, component breakdown, migration from monoliths, common pitfalls, monitoring, tracing, logging, gateway, service discovery, resilience patterns, testing strategies, frameworks, and the emerging service‑mesh approach.

Service Meshfault tolerancemonitoring
0 likes · 23 min read
A Comprehensive Overview of Microservice Architecture and Its Evolution
dbaplus Community
dbaplus Community
Sep 16, 2019 · Operations

How to Build Effective Monitoring for Microservices: Logs, Tracing, and Metrics Explained

This article explains the three main monitoring approaches—log collection, distributed tracing, and metric gathering—in microservice architectures, outlines the layered monitoring model, lists key system, application, and user metrics, and reviews popular open‑source time‑series monitoring tools such as Prometheus, OpenTSDB, and InfluxDB.

MetricsMicroservicesPrometheus
0 likes · 10 min read
How to Build Effective Monitoring for Microservices: Logs, Tracing, and Metrics Explained
AntTech
AntTech
Sep 2, 2019 · Cloud Native

Exploring Observability in Cloud‑Native Architecture: Practices from Ant Financial

This article reviews Ant Financial's cloud‑native observability journey, covering its origins, the three pillars of tracing, metrics and logging, community projects like OpenTelemetry, practical implementations, sampling strategies, and future directions for unified microservice, mesh, and serverless monitoring.

MetricsOpenTelemetrycloud-native
0 likes · 15 min read
Exploring Observability in Cloud‑Native Architecture: Practices from Ant Financial
Alibaba Cloud Native
Alibaba Cloud Native
Jul 12, 2019 · Cloud Native

How to Deploy Production-Ready Knative Services on Alibaba Cloud Container Service

This guide walks you through deploying a Knative Service on Alibaba Cloud Container Service, configuring logging and monitoring with Log Service, setting up alerting, and enabling distributed tracing, providing step‑by‑step commands, YAML examples, and console screenshots for a production‑grade serverless setup.

Alibaba CloudContainer ServiceKnative
0 likes · 9 min read
How to Deploy Production-Ready Knative Services on Alibaba Cloud Container Service
dbaplus Community
dbaplus Community
May 22, 2019 · Operations

Designing a Scalable Monitoring System: From Data Collection to Alerting

This article explains how to build a comprehensive monitoring system for distributed applications by classifying monitoring functions, describing data quadrants, outlining core modules such as collection, processing, feature extraction, and visualization, and reviewing typical implementations for metrics, logs, tracing, alerting, and the key open‑source components involved.

Distributed SystemsMetricsmonitoring
0 likes · 18 min read
Designing a Scalable Monitoring System: From Data Collection to Alerting
Bitu Technology
Bitu Technology
Oct 25, 2018 · Backend Development

Applying Node.js async_hooks API in Tubi’s Backend Services

This article explains why Tubi adopted Node.js’s async_hooks API, describes the challenges of context propagation in asynchronous calls, demonstrates a monkey‑patching solution for HTTP servers, and shares production‑grade practices for tracing, retries, and memory management in their micro‑framework.

BackendRPCasync_hooks
0 likes · 8 min read
Applying Node.js async_hooks API in Tubi’s Backend Services
Architects' Tech Alliance
Architects' Tech Alliance
Oct 8, 2018 · Backend Development

Publishing, Registering, Discovering, Monitoring, Tracing and Governing RPC Services in Microservice Architecture

This article explains how to describe, publish, register, discover, invoke, monitor, trace, and govern RPC services in a microservice architecture, covering RESTful API, XML configuration, IDL files, registry principles, Zookeeper deployment, connection methods, server processing models, monitoring metrics, tracing concepts, and common governance techniques such as load balancing and fault tolerance.

RPCService Registrationmonitoring
0 likes · 31 min read
Publishing, Registering, Discovering, Monitoring, Tracing and Governing RPC Services in Microservice Architecture
JD Tech
JD Tech
Sep 26, 2018 · Operations

Root Cause Analysis and Mitigation of Sysmon High CPU and Memory Usage

This article investigates why the Sysinternals Sysmon monitoring tool occasionally consumes an entire CPU core and rapidly increases memory usage, analyzes thread creation, handle explosion, and registry settings, reproduces the issue on any machine, and proposes practical solutions to stop the recursive behavior.

Windowsmemoryperformance
0 likes · 16 min read
Root Cause Analysis and Mitigation of Sysmon High CPU and Memory Usage
JD Retail Technology
JD Retail Technology
Feb 5, 2018 · Backend Development

Design and Implementation of Footprint Platform, Mock Server Platform, and Pre‑release Gray Release Solution for Virtual Products

This article presents the challenges of virtual product development and describes three engineering solutions—a Footprint tracking system, a Mock Server platform, and a pre‑release gray‑release strategy—detailing their backgrounds, architectures, implementations, and operational benefits for improving debugging, testing, and deployment efficiency.

BackendMessage QueueMock Server
0 likes · 8 min read
Design and Implementation of Footprint Platform, Mock Server Platform, and Pre‑release Gray Release Solution for Virtual Products
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.

BackendMetricsNode.js
0 likes · 2 min read
Unlocking Pandora.js: Manageable, Measurable, Traceable Node.js Applications
DevOps
DevOps
Jan 7, 2018 · Fundamentals

Enabling Git Debug Output in PowerShell

When Git commands produce hard‑to‑diagnose errors, you can activate detailed tracing in PowerShell by setting the environment variables GIT_TRACE and GIT_CURL_VERBOSE to 1, which makes Git output extensive operation details to help locate the problem.

GitPowerShellVersion Control
0 likes · 2 min read
Enabling Git Debug Output in PowerShell
Node Underground
Node Underground
Dec 7, 2017 · Backend Development

Build a Node.js Performance Tracing Tool with Async Hooks and Performance API

This article explains how to combine Node.js's experimental Async Hooks and Performance Timing APIs to create a simple tracing and performance monitoring tool, eliminating manual timing and offering a foundation that can be extended into a custom solution, while also noting an open‑source Pandora.js utility.

BackendNode.jsPerformance API
0 likes · 3 min read
Build a Node.js Performance Tracing Tool with Async Hooks and Performance API
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.

APMPinpointPlugin Development
0 likes · 22 min read
Pinpoint Overview and Plugin Development Guide