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apache/skywalking

📈 Trending★ 24,799JavaAudience · ops devopsComplexity · 4/5ActiveLicenseSetup · hard

TLDR

Open-source monitoring system that tracks requests across multiple services, showing you where slowdowns and errors happen in production applications.

Mindmap

mindmap
  root((repo))
    What it does
      Traces requests
      Collects metrics
      Aggregates logs
    Data sources
      Java agents
      Python agents
      Node.js agents
      eBPF monitoring
    Use cases
      Diagnose slowdowns
      Find error sources
      Monitor microservices
    Tech stack
      Java
      OpenTelemetry
      Prometheus
      Kubernetes

Things people build with this

USE CASE 1

Monitor microservices in production and trace a slow request across multiple services to find the bottleneck.

USE CASE 2

Set up alerts when error rates spike or response times exceed thresholds in your Kubernetes cluster.

USE CASE 3

Diagnose why a specific user's transaction failed by viewing the full trace of requests and logs across your system.

USE CASE 4

Track performance metrics and trends over time to identify when deployments introduce regressions.

Tech stack

JavaOpenTelemetryPrometheusZipkineBPFKubernetes

Getting it running

Difficulty · hard Time to first run · 1day+

Requires Kubernetes cluster, eBPF kernel support, and coordination of multiple observability backends (Prometheus, Zipkin) plus Java instrumentation.

Apache License 2.0, use freely for any purpose, including commercial, as long as you include the license notice and document any changes.

In plain English

Apache SkyWalking is an open-source monitoring system designed to help engineering teams understand how their software applications are performing in production. Think of it like a health dashboard for complex, multi-service software systems, it watches everything happening inside your apps and surfaces problems before users notice them. It works by collecting three types of data: traces (following a single request as it travels through multiple services), metrics (numbers like response time, error rate, and throughput), and logs (text records of what happened and when). SkyWalking stitches these together so you can see, for example, that a slow page load was caused by a database query in a specific microservice. It supports agents, small add-ons, for Java, Python, Node.js, Go, PHP, Rust, and several other languages, so it plugs into most existing tech stacks. It also uses eBPF, a modern Linux technology, to monitor Kubernetes (containerized application) deployments at a low level without requiring code changes. The system can handle over 100 billion data points from a single cluster and integrates with popular monitoring ecosystems like OpenTelemetry, Prometheus, and Zipkin. Teams use SkyWalking when they run distributed systems, multiple services talking to each other, and need to diagnose slowdowns, errors, or unexpected behavior. It is especially common in cloud-native and container-based environments. The primary language is Java and it is an Apache Software Foundation project.

Copy-paste prompts

Prompt 1
How do I install SkyWalking agents for my Java microservices and start collecting traces?
Prompt 2
Show me how to set up SkyWalking to monitor a Kubernetes cluster using eBPF without modifying my application code.
Prompt 3
How do I integrate SkyWalking with Prometheus and Grafana to visualize metrics and set up alerts?
Prompt 4
Walk me through how to use SkyWalking's UI to find which service is causing a slow request in my distributed system.
Prompt 5
How do I configure SkyWalking to collect and correlate traces, metrics, and logs from multiple services?
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.