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This article details Vivo's end‑to‑end Pulsar observability solution, covering the challenges of Prometheus‑based monitoring, the architecture of the alerting pipeline, adaptor development, metric optimizations for subscription backlog and bundle load, and fixes for kop lag reporting issues.
This article provides an in‑depth analysis of BPF maps—explaining their design principles, core features, various map types with code examples, and the macro expansion process that turns high‑level BCC helpers into native kernel map definitions for cloud‑native observability.
This article details WeChat's migration of large‑scale big data and AI workloads to a cloud‑native Kubernetes platform, discussing performance bottlenecks, API server and ETCD overload protection, scheduler enhancements, observability solutions, resource utilization gains, and future serverless directions.
This guide walks you through deploying kube-state-metrics, configuring Prometheus scrape jobs, verifying metric collection, and adding Grafana dashboards to achieve a visible, manageable, and reliable Kubernetes monitoring solution for large‑scale clusters.
This article explains why observability is essential for Spring AI applications, outlines common cost‑control and performance challenges, and provides a step‑by‑step guide—including Maven setup, client configuration, service implementation, metric exposure, Zipkin tracing, and architecture insights—to create a fully observable, enterprise‑grade AI translation service.
This article introduces SigNoz, a self‑hosted open‑source observability platform that unifies metrics, logs, and traces, outlines its core capabilities, shows how to install it with Docker, and compares its resource efficiency to commercial solutions like DataDog and Elastic.
Spring Boot 3.5 introduces a suite of enhancements—including task decorator support, the Vibur connection pool, SSL health metrics, flexible configuration loading, automatic Trace‑ID headers, richer Actuator capabilities, functional programming hooks, and many more—each explained with code examples and practical usage tips for modern Java backend development.
Spring Boot 3.5 introduces a suite of powerful enhancements—including task decorator support, a new Vibur connection pool, SSL monitoring, flexible environment variable loading, Actuator-triggered Quartz jobs, automatic Trace ID headers, structured log customization, functional routing insights, expanded SSL client support, OpenTelemetry upgrades, Spring Batch tweaks, OAuth 2.0 JWT profiling, and functional bean registration—providing developers with richer capabilities for modern Java backend applications.
This comprehensive guide explains Loki's lightweight log aggregation architecture, compares it with ELK, details AllInOne, Helm, Kubernetes, and bare‑metal deployment methods, shows Promtail and Logstash integration, and provides practical troubleshooting tips for common issues.
This guide compiles the most important Linux performance analysis utilities—such as vmstat, iostat, dstat, iotop, pidstat, top, htop, mpstat, netstat, ps, strace, uptime, lsof, and perf—explaining their usage, output fields, and how they fit into a comprehensive system observability workflow.
Changan Automobile’s full‑link observability platform passed both ITU DevOps international and domestic standards assessments, showcasing its advanced monitoring capabilities, improved system stability, and strategic role in the company’s digital transformation, while the interview reveals implementation challenges, benefits, and future AI‑driven enhancements.
Baidu’s SRE digital‑immune system, evolved into an AI‑powered intelligent immunity platform, quantifies and mitigates risk across thousands of services by integrating data‑driven monitoring, rule‑based detection, and large‑model GraphRAG knowledge mining, cutting degradation cases by ~40% and shifting operations from reactive troubleshooting to proactive, data‑centric quality assurance.
OpenTelemetry unifies tracing and metrics by merging OpenTracing and OpenCensus, offering vendor‑neutral APIs, SDKs, and a collector that standardize telemetry data collection, context propagation, and export to various back‑ends, with detailed components such as Tracer, Meter, and shared Context layers.
This article examines the causes of Log4j2 asynchronous logging blockage in high‑throughput Java services, explains the underlying Disruptor mechanics, and proposes a dual‑track logging architecture with compile‑time bytecode enhancement and IDE plugins for line‑level log activation.
This article explains the challenges of observability in distributed microservice and LLM architectures, introduces CloudWeGo and APMPlus, and provides step‑by‑step integration guides for Kitex, Hertz, and Eino frameworks, including code samples, data reporting methods, and advanced monitoring features such as RED metrics, LLM‑specific indicators, service topology, and future roadmap.
This article shares practical experience from Volcengine's managed Prometheus service and its deep integration with large‑model and autonomous‑driving platforms, explaining what high cardinality is, its impact on monitoring systems, root causes, and a range of design, collection, and analysis techniques to mitigate it.
Chronon is an open‑source ML feature platform that lets engineers declaratively define, compute, and serve both batch and real‑time features with built‑in observability, data‑quality checks, and a low‑latency retrieval API, ensuring online‑offline consistency while simplifying pipeline management and enabling future automation.
This article explains the core value of front‑end error monitoring, outlines key error categories, presents practical code examples for capturing explicit, implicit, resource, promise and framework errors, and proposes a multi‑layer defense strategy to improve observability, response time and team collaboration.
This article explains Application Performance Monitoring (APM), its key benefits such as business continuity, performance optimization, and cost reduction, outlines essential APM modules, and details Yunzhou Observation’s OpenTelemetry‑based design, data ingestion, processing, visualization, and future roadmap for observability.
Monitoring Kubernetes is essential to detect resource contention, component failures, and network issues; it involves tracking core component metrics such as API server latency, etcd write times, scheduler delays, as well as node‑level CPU, memory, disk, and network statistics, pod health, and custom application metrics exposed via Prometheus exporters for comprehensive observability.