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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.
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 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.
Observability turns a black‑box application into a system by gathering logs, metrics, and traces, using alerts to spot anomalies, then linking trace IDs to logs; OpenTelemetry standardizes this with instrumented client agents, a Collector (receivers, processors, exporters), and backend storage, while Java agents, span propagation, exemplars, eBPF, and bundles like SigNoz or OpenObserve let teams choose between a custom OTel stack or a solution.
Prometheus 3.0‑beta introduces a completely redesigned UI, Remote Write 2.0 with native support for metadata and histograms, built‑in OpenTelemetry metrics handling, UTF‑8 label support, native histograms, and several feature‑flag removals, while encouraging community testing before production use.
The new OpenTelemetry Java instrumentation adds client and server request‑size metrics to gRPC by injecting a tracing interceptor via Byte‑Buddy bytecode enhancement, extracting payload sizes from protobuf messages, recording them with custom attributes and histograms, and applying analogous handler‑based logic for Go.
This article explains how to create OpenTelemetry instrumentation for the PowerJob distributed scheduler by implementing a Java agent with ByteBuddy, covering background, prerequisite knowledge, entry point discovery, version selection, implementation details, common pitfalls, Muzzle validation, and unit testing.
The article explains how Helm simplifies deploying complex Kubernetes applications with a single YAML chart but cannot manage runtime operations, while Kubernetes Operators—built on custom resource definitions and webhook logic—automate tasks such as scaling, upgrades, and side‑car injection, offering higher‑level lifecycle management.
This guide explains how to use Alibaba Cloud Service Mesh (ASM) to create isolated, on‑demand environments for cloud‑native microservices across multiple ACK clusters, leveraging traffic‑lane (permissive mode) and OpenTelemetry automatic instrumentation to achieve efficient development, testing, and progressive gray‑release workflows while reducing resource consumption.
This article details Huya's transition from fragmented, non‑standard monitoring solutions to a unified OpenTelemetry‑based platform, covering project background, pain points, design decisions, SDK architecture, data pipeline, storage, alerting, root‑cause analysis, and future plans, highlighting the benefits of standardization and zero‑cost service integration.
The article explains how a custom java.net.spi.InetAddressResolverProvider SPI that works in a regular Spring Boot 3.x JAR fails when the OpenTelemetry Java agent is added because the agent’s JarLoader cannot read the SPI configuration inside the BOOT‑INF layout, and resolves the issue by disabling the agent’s own resolver resource so the custom provider is used.
The article walks through building a custom OpenTelemetry Java‑agent extension for Pulsar client metrics—migrating from SkyWalking, setting up a Gradle project, using ByteBuddy to instrument methods with advice, registering gauge metrics, packaging the jar, handling common class‑loader pitfalls, and configuring deployment via the OpenTelemetry operator.
By introducing the unified tRPC scaffolding tool trpcx and embedding OpenTelemetry‑generated observability configurations, the Tencent Docs backend team streamlined service creation, standardized directory structures, migrated metrics and logs to ClickHouse for cost‑effective performance, and established best‑practice workflows that dramatically improve development speed and fault‑diagnosis efficiency.
Trace2.0 is an OpenTelemetry‑based application monitoring system that processes petabyte‑scale trace data using multi‑channel client protocols, gRPC, load‑balancing optimizations, ZSTD compression, Kafka pipelines, ClickHouse storage, and a JDK 21 upgrade with virtual threads, achieving significant performance and cost improvements.
At the 21st GOPS Global Operations Conference, New Oriental's senior operations manager Qi Chen detailed the demand, technical, and focus pressures that drove a phased, full‑process observability standardization, leveraging OpenTelemetry, Telegraf, Loki and CMDB tagging to achieve cost reduction and higher stability.
The article explains how Tencent Cloud APM implements full‑link tracing using OpenTelemetry standards, addresses challenges such as protocol compatibility, massive trace storage, and bytecode overhead with solutions like conversion gateways, tail sampling and thread profiling, and showcases best‑practice scenarios for topology analysis, front‑end/back‑end integration, and log‑trace correlation within the broader TCOP observability suite.
The article explains the importance of CI/CD observability, outlines common pipeline problems, introduces Grafana's GraCIe plugin built on OpenTelemetry, and discusses how enhanced visibility can improve reliability, decision‑making, and future standardization across CI/CD platforms.
The missing trace data in two Go services was caused by the GoFrame tracing middleware recording the gzip‑compressed /metrics response body as a UTF‑8 string, which the OpenTelemetry exporter rejected as invalid UTF‑8; disabling Prometheus compression or decompressing the body before logging resolves the issue.
Thread profiling uses threshold‑triggered tasks on business threads to capture stack snapshots, which a dedicated profiler thread sends via high‑performance gRPC to a server that queues them in Kafka, enriches and stores them in ClickHouse, correlates with OpenTelemetry traces, and provides metrics that let developers quickly pinpoint latency bottlenecks and improve system stability.
This article details Bilibili's evolution of its log system from an Elastic Stack‑based solution to a ClickHouse‑backed architecture with OpenTelemetry, describing the challenges of cost, stability, and scalability, the new components such as Log‑Agent, Log‑Ingester, and a custom visualization platform, and the performance gains and future directions.