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.mdsafety · 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
endpoint and/healthSELF_TRACING_ENABLED=true - Prefer Elasticsearch over MySQL for production workloads with high trace volume