Zipkin Tracing

beginner

Distributed tracing system for latency analysis in microservices.

Overview

Zipkin is an open-source distributed tracing system originally developed by Twitter to help troubleshoot latency problems in microservice architectures. It collects timing data needed to troubleshoot latency issues, allowing developers to visualize request flows across multiple services and identify performance bottlenecks. Zipkin follows the OpenTracing standard and provides detailed insights into how requests propagate through distributed systems, making it essential for maintaining observable microservices. This configuration combines Zipkin with Elasticsearch as the storage backend, creating a powerful tracing platform that can handle high-volume trace data with advanced search and analytics capabilities. Elasticsearch provides Zipkin with scalable storage, fast querying, and the ability to perform complex aggregations on trace data, while the zipkin-dependencies service automatically generates service dependency graphs from collected traces. Development teams building microservices, DevOps engineers managing distributed systems, and organizations transitioning from monolithic to service-oriented architectures will find this stack invaluable for understanding system behavior and optimizing performance across service boundaries.

Key Features

B3 propagation support for seamless trace context propagation across HTTP requests
Real-time service dependency graph generation with automatic topology discovery
Latency percentile analysis with P50, P95, and P99 calculations for performance monitoring
Elasticsearch-powered full-text search across trace annotations and tags
Automatic trace retention and cleanup through Elasticsearch index lifecycle management
Support for multiple span types including client, server, producer, and consumer spans
Built-in sampling strategies to control trace collection overhead in high-traffic environments
RESTful API for programmatic trace submission and querying

Common Use Cases

1Debugging performance bottlenecks in microservice architectures during development
2Root cause analysis for intermittent latency spikes in production environments
3Service dependency mapping for legacy system modernization projects
4Performance regression testing in CI/CD pipelines with trace comparison
5Capacity planning by analyzing request patterns and service utilization
6SLA monitoring and alerting based on service-level latency metrics
7API gateway performance optimization through upstream service analysis

Prerequisites

Minimum 2GB RAM for Elasticsearch storage backend (4GB recommended for production)
Port 9411 available for Zipkin web UI and API access
Basic understanding of distributed tracing concepts and span terminology
Application instrumentation with Zipkin-compatible tracing libraries
Docker Engine 19.03+ with Docker Compose v2 support
At least 10GB free disk space for trace data storage and Elasticsearch indices

For development & testing. Review security settings, change default credentials, and test thoroughly before production use. See Terms

docker-compose.yml

1services: 
2  zipkin: 
3    image: openzipkin/zipkin:latest
4    container_name: zipkin
5    environment: 
6      - STORAGE_TYPE=elasticsearch
7      - ES_HOSTS=elasticsearch:9200
8    ports: 
9      - "9411:9411"
10    depends_on: 
11      - elasticsearch
12    networks: 
13      - zipkin-network
14    restart: unless-stopped
15
16  elasticsearch: 
17    image: docker.elastic.co/elasticsearch/elasticsearch:8.11.0
18    container_name: zipkin-elasticsearch
19    environment: 
20      - discovery.type=single-node
21      - xpack.security.enabled=false
22      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
23    volumes: 
24      - elasticsearch-data:/usr/share/elasticsearch/data
25    networks: 
26      - zipkin-network
27    restart: unless-stopped
28
29  zipkin-dependencies: 
30    image: openzipkin/zipkin-dependencies:latest
31    container_name: zipkin-dependencies
32    environment: 
33      - STORAGE_TYPE=elasticsearch
34      - ES_HOSTS=elasticsearch:9200
35    depends_on: 
36      - elasticsearch
37    networks: 
38      - zipkin-network
39    entrypoint: crond -f
40
41volumes: 
42  elasticsearch-data: 
43
44networks: 
45  zipkin-network: 
46    driver: bridge

.env Template

.env

1# Zipkin
2# Send traces to http://localhost:9411/api/v2/spans

Usage Notes

1Zipkin UI at http://localhost:9411
2Send traces via HTTP POST
3Service dependency graph
4Latency percentile analysis
5Supports B3 propagation

Individual Services(3 services)

Copy individual services to mix and match with your existing compose files.

zipkin

zipkin:
  image: openzipkin/zipkin:latest
  container_name: zipkin
  environment:
    - STORAGE_TYPE=elasticsearch
    - ES_HOSTS=elasticsearch:9200
  ports:
    - "9411:9411"
  depends_on:
    - elasticsearch
  networks:
    - zipkin-network
  restart: unless-stopped

elasticsearch

elasticsearch:
  image: docker.elastic.co/elasticsearch/elasticsearch:8.11.0
  container_name: zipkin-elasticsearch
  environment:
    - discovery.type=single-node
    - xpack.security.enabled=false
    - ES_JAVA_OPTS=-Xms512m -Xmx512m
  volumes:
    - elasticsearch-data:/usr/share/elasticsearch/data
  networks:
    - zipkin-network
  restart: unless-stopped

zipkin-dependencies

zipkin-dependencies:
  image: openzipkin/zipkin-dependencies:latest
  container_name: zipkin-dependencies
  environment:
    - STORAGE_TYPE=elasticsearch
    - ES_HOSTS=elasticsearch:9200
  depends_on:
    - elasticsearch
  networks:
    - zipkin-network
  entrypoint: crond -f

Quick Start

terminal

1# 1. Create the compose file
2cat > docker-compose.yml << 'EOF'
3services:
4  zipkin:
5    image: openzipkin/zipkin:latest
6    container_name: zipkin
7    environment:
8      - STORAGE_TYPE=elasticsearch
9      - ES_HOSTS=elasticsearch:9200
10    ports:
11      - "9411:9411"
12    depends_on:
13      - elasticsearch
14    networks:
15      - zipkin-network
16    restart: unless-stopped
17
18  elasticsearch:
19    image: docker.elastic.co/elasticsearch/elasticsearch:8.11.0
20    container_name: zipkin-elasticsearch
21    environment:
22      - discovery.type=single-node
23      - xpack.security.enabled=false
24      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
25    volumes:
26      - elasticsearch-data:/usr/share/elasticsearch/data
27    networks:
28      - zipkin-network
29    restart: unless-stopped
30
31  zipkin-dependencies:
32    image: openzipkin/zipkin-dependencies:latest
33    container_name: zipkin-dependencies
34    environment:
35      - STORAGE_TYPE=elasticsearch
36      - ES_HOSTS=elasticsearch:9200
37    depends_on:
38      - elasticsearch
39    networks:
40      - zipkin-network
41    entrypoint: crond -f
42
43volumes:
44  elasticsearch-data:
45
46networks:
47  zipkin-network:
48    driver: bridge
49EOF
50
51# 2. Create the .env file
52cat > .env << 'EOF'
53# Zipkin
54# Send traces to http://localhost:9411/api/v2/spans
55EOF
56
57# 3. Start the services
58docker compose up -d
59
60# 4. View logs
61docker compose logs -f

One-Liner

Run this command to download and set up the recipe in one step:

terminal

1curl -fsSL https://docker.recipes/api/recipes/zipkin-tracing/run | bash

Troubleshooting

Zipkin UI shows no traces: Verify applications are instrumented and sending traces to http://localhost:9411/api/v2/spans
Elasticsearch connection refused errors: Wait for Elasticsearch to fully start (30-60 seconds) before Zipkin attempts connection
Out of memory errors in Elasticsearch: Increase ES_JAVA_OPTS heap size from 512m to 1g or higher based on trace volume
zipkin-dependencies service not generating dependency graphs: Check that spans have proper service names and that Elasticsearch contains trace data
High CPU usage on zipkin-dependencies: Adjust cron schedule in entrypoint or limit dependency analysis to specific time ranges
Traces not appearing in UI after submission: Check Elasticsearch cluster health and verify STORAGE_TYPE environment variable is set correctly

Community Notes

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Components

zipkinelasticsearch

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