Skills zipkin

install
source · Clone the upstream repo
git clone https://github.com/TerminalSkills/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/TerminalSkills/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/zipkin" ~/.claude/skills/terminalskills-skills-zipkin && rm -rf "$T"
manifest: skills/zipkin/SKILL.md
safety · automated scan (low risk)
This is a pattern-based risk scan, not a security review. Our crawler flagged:
  • makes HTTP requests (curl)
Always read a skill's source content before installing. Patterns alone don't mean the skill is malicious — but they warrant attention.
source content

Zipkin

Overview

Set up Zipkin for distributed tracing to visualize request flows across services. Covers deployment, instrumentation with Spring Boot and OpenTelemetry, storage configuration, and dependency analysis.

Instructions

Task A: Deploy Zipkin

# docker-compose.yml — Zipkin with Elasticsearch storage
services:
  zipkin:
    image: openzipkin/zipkin:3
    environment:
      - STORAGE_TYPE=elasticsearch
      - ES_HOSTS=http://elasticsearch:9200
      - ES_INDEX=zipkin
      - ES_INDEX_REPLICAS=1
      - ES_INDEX_SHARDS=3
      - SELF_TRACING_ENABLED=true
      - JAVA_OPTS=-Xms512m -Xmx512m
    ports:
      - "9411:9411"
    depends_on:
      - elasticsearch

  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0
    environment:
      - discovery.type=single-node
      - xpack.security.enabled=false
      - "ES_JAVA_OPTS=-Xms1g -Xmx1g"
    volumes:
      - es_data:/usr/share/elasticsearch/data

volumes:
  es_data:
# Quick start with in-memory storage (development only)
docker run -d -p 9411:9411 openzipkin/zipkin:3

Task B: Instrument Spring Boot Application

<!-- pom.xml — Zipkin dependencies for Spring Boot 3 -->
<dependency>
    <groupId>io.micrometer</groupId>
    <artifactId>micrometer-tracing-bridge-brave</artifactId>
</dependency>
<dependency>
    <groupId>io.zipkin.reporter2</groupId>
    <artifactId>zipkin-reporter-brave</artifactId>
</dependency>
# application.yml — Spring Boot tracing configuration
spring:
  application:
    name: order-service
management:
  tracing:
    sampling:
      probability: 1.0
  zipkin:
    tracing:
      endpoint: http://zipkin:9411/api/v2/spans
logging:
  pattern:
    level: "%5p [${spring.application.name:},%X{traceId:-},%X{spanId:-}]"
// OrderController.java — Spring Boot controller with automatic tracing
@RestController
@RequestMapping("/api/orders")
public class OrderController {

    private final RestClient restClient;
    private final ObservationRegistry registry;

    @PostMapping
    public ResponseEntity<Order> createOrder(@RequestBody OrderRequest req) {
        // Spans are created automatically for @RestController methods
        Order order = orderService.create(req);

        // RestClient propagates trace context automatically
        PaymentResult payment = restClient.post()
            .uri("http://payment-service/api/charge")
            .body(new ChargeRequest(order.getId(), order.getTotal()))
            .retrieve()
            .body(PaymentResult.class);

        return ResponseEntity.status(201).body(order);
    }
}

Task C: Instrument with OpenTelemetry (Generic)

# tracing.py — Python service sending traces to Zipkin via OTLP
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.zipkin.json import ZipkinExporter
from opentelemetry.sdk.resources import Resource

resource = Resource.create({"service.name": "inventory-service"})
provider = TracerProvider(resource=resource)

zipkin_exporter = ZipkinExporter(endpoint="http://zipkin:9411/api/v2/spans")
provider.add_span_processor(BatchSpanProcessor(zipkin_exporter))
trace.set_tracer_provider(provider)

tracer = trace.get_tracer("inventory-service")
// tracing.js — Node.js service sending traces to Zipkin
const { NodeSDK } = require('@opentelemetry/sdk-node')
const { ZipkinExporter } = require('@opentelemetry/exporter-zipkin')
const { getNodeAutoInstrumentations } = require('@opentelemetry/auto-instrumentations-node')

const sdk = new NodeSDK({
  traceExporter: new ZipkinExporter({ url: 'http://zipkin:9411/api/v2/spans' }),
  instrumentations: [getNodeAutoInstrumentations()],
  serviceName: 'notification-service',
})
sdk.start()

Task D: Query Traces via API

# Find traces by service name and time range
curl -s "http://localhost:9411/api/v2/traces?serviceName=order-service&limit=10&lookback=3600000" | \
  jq '.[] | {traceId: .[0].traceId, spans: length, root: .[0].name, duration: (.[0].duration / 1000)}'
# Get service dependency graph
curl -s "http://localhost:9411/api/v2/dependencies?endTs=$(date +%s000)&lookback=86400000" | \
  jq '.[] | "\(.parent) -> \(.child) (\(.callCount) calls)"'
# Find traces with specific tag
curl -s "http://localhost:9411/api/v2/traces?annotationQuery=http.status_code%3D500&serviceName=order-service" | \
  jq '.[0][] | {name: .name, service: .localEndpoint.serviceName, duration: .duration}'

Task E: Zipkin with MySQL Storage

# docker-compose.yml — Zipkin with MySQL for durable storage
services:
  zipkin:
    image: openzipkin/zipkin:3
    environment:
      - STORAGE_TYPE=mysql
      - MYSQL_HOST=mysql
      - MYSQL_TCP_PORT=3306
      - MYSQL_USER=zipkin
      - MYSQL_PASS=zipkin_password
    ports:
      - "9411:9411"
    depends_on:
      - mysql

  mysql:
    image: openzipkin/zipkin-mysql:3
    volumes:
      - mysql_data:/var/lib/mysql

volumes:
  mysql_data:

Best Practices

  • Use sampling rates below 100% in production for high-traffic services to control storage costs
  • Include trace IDs in application logs for log-trace correlation
  • Use B3 propagation headers for cross-service context propagation in Spring Boot
  • Set appropriate storage TTL — 7 days for detailed traces, dependency data is lightweight
  • Monitor Zipkin's own health with
    /health
    endpoint and
    SELF_TRACING_ENABLED=true
  • Prefer Elasticsearch over MySQL for production workloads with high trace volume