关于 opentelemetry
opentelemetry 是一份使用 Grafana 的 OpenTelemetry 指南,面向需要为应用采集并发送指标、日志、追踪和性能剖析数据的开发人员。内容包括 OTLP 配置、自动插桩、采样及 Alloy 收集器工作流。
主要功能
- 01通过 OTLP 发送遥测数据
- 02配置 Grafana Cloud 认证与环境变量
- 03自动插桩 Java 和 Python 应用
- 04使用 Alloy 缓冲、转发和采样
- 05通过 Operator 为 Kubernetes Pod 注入插桩
适用场景
- 01将应用遥测数据发送至 Grafana 后端
- 02为 Java 或 Python 应用启用自动插桩
- 03在 Alloy 中配置数据转发与尾部采样
- 04在 Kubernetes 中为 Pod 注入插桩
安装
复制下面的命令,在终端中运行。
$
npx skills add https:/ / github.com/ grafana/ skills --skill opentelemetry安装后在 Claude Code 中输入/opentelemetry确认已加载。
附带文件references/collector-config.mdreferences/instrumentation.md
详细介绍
使用 Grafana 的 OpenTelemetry
与供应商无关的埋点管道。应用通过 OTLP 通信 → Alloy(或直接通信)→ Grafana Cloud(Mimir / Loki / Tempo / Pyroscope)。
后端
| 信号 | 后端 |
|---|---|
| 指标 | Grafana Mimir |
| 日志 | Grafana Loki |
| 跟踪 | Grafana Tempo |
| 性能剖析 | Grafana Pyroscope |
先决条件
- Grafana Cloud 堆栈,或可自托管的 Mimir / Loki / Tempo
- Cloud OTLP 端点:
https://otlp-gateway-<region>.grafana.net/otlp - Basic-auth 凭据:数字型实例 ID + 具有
MetricsPublisher+LogsPublisher+TracesPublisher权限的 API 令牌 - 要进行埋点的应用
常见工作流
1. 向 Grafana Cloud OTLP 端点进行身份验证
# 1. Build the auth header
INSTANCE_ID=123456
API_KEY="glc_eyJ..."
export OTEL_EXPORTER_OTLP_ENDPOINT=https://otlp-gateway-prod-us-east-0.grafana.net/otlp
export OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf
export OTEL_EXPORTER_OTLP_HEADERS="Authorization=Basic $(echo -n "${INSTANCE_ID}:${API_KEY}" | base64)"
export OTEL_RESOURCE_ATTRIBUTES="service.name=myapp,service.namespace=myteam,deployment.environment=prod"
# 2. Smoke-test creds with a curl POST against the OTLP traces endpoint (empty body)
curl -s -o /dev/null -w "%{http_code}\n" \
-X POST -H "Content-Type: application/x-protobuf" \
-H "Authorization: Basic $(echo -n "${INSTANCE_ID}:${API_KEY}" | base64)" \
"$OTEL_EXPORTER_OTLP_ENDPOINT/v1/traces" --data-binary '\n'
# Expect 400 (malformed payload) — NOT 401 (auth) or 404 (wrong endpoint).
2. 对 Java 应用进行自动埋点并验证
# 1. Download the Grafana JVM agent (single jar)
curl -sLO https://github.com/grafana/grafana-opentelemetry-java/releases/latest/download/grafana-opentelemetry-java.jar
# 2. Run with the agent + env from step 1
java -javaagent:./grafana-opentelemetry-java.jar -jar myapp.jar
# 3. Generate traffic, then verify in Grafana → Explore → Tempo:
# TraceQL: { resource.service.name = "myapp" }
# Expect spans within ~30s. Also verify metrics:
# PromQL: count by (service_name)({service_name="myapp"})
3. 对 Python 应用进行自动埋点
pip install "opentelemetry-distro[otlp]"
opentelemetry-bootstrap -a install
# Same env vars as step 1, then:
opentelemetry-instrument python app.py
# Verify the same way — Explore → Traces filter service.name=myapp.
4. 添加 Alloy 作为缓冲 / 采样收集器
# Application points at local Alloy (gRPC fastest)
export OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
export OTEL_EXPORTER_OTLP_PROTOCOL=grpc
# Alloy environment for forwarding to Cloud
export GRAFANA_CLOUD_OTLP_ENDPOINT=https://otlp-gateway-prod-us-east-0.grafana.net/otlp
export GRAFANA_CLOUD_INSTANCE_ID=$INSTANCE_ID
export GRAFANA_CLOUD_API_KEY=$API_KEY
alloy run /etc/alloy/config.alloy
# Verify Alloy received and forwarded
curl -s http://localhost:12345/metrics | grep otelcol_exporter_sent_spans
完整 Alloy 配置 + 尾部采样配置块 + OTel Collector YAML + K8s Operator 安装说明:references/collector-config.md。
各语言 SDK 详情(Go 完整代码、Node 手动设置、.NET ASP.NET Core、所有环境变量的特殊之处):references/instrumentation.md。
5. Kubernetes — 通过 Operator 自动注入
apiVersion: opentelemetry.io/v1alpha1
kind: Instrumentation
metadata: { name: my-instrumentation }
spec:
exporter: { endpoint: http://otelcol:4317 }
propagators: [tracecontext, baggage]
java:
image: us-docker.pkg.dev/grafanalabs-global/docker-grafana-opentelemetry-java-prod/grafana-opentelemetry-java:2.3.0-beta.1
nodejs: {}
python: {}
然后为 Pod 添加注解:
metadata:
annotations:
instrumentation.opentelemetry.io/inject-java: "true"
# or: inject-nodejs, inject-python, inject-dotnet
# Verify the operator injected the agent
kubectl describe pod <pod> | grep -A2 'opentelemetry-auto-instrumentation'
# Then run the same Grafana Explore checks.
采样 — 如何选择
# Head sampling (cheap, decided at start; may lose rare errors)
export OTEL_TRACES_SAMPLER=parentbased_traceidratio
export OTEL_TRACES_SAMPLER_ARG=0.1 # 10%
尾部采样(查看完整跟踪后再做决定——保留错误并对其余部分采样)需要 Alloy / OTel-Collector tail_sampling 处理器;完整配置块见 references/collector-config.md。
关键环境变量
| 变量 | 示例 |
|---|---|
OTEL_EXPORTER_OTLP_ENDPOINT | https://otlp-gateway-prod-us-east-0.grafana.net/otlp |
OTEL_EXPORTER_OTLP_PROTOCOL | grpc 或 http/protobuf |
OTEL_EXPORTER_OTLP_HEADERS | Authorization=Basic <base64> |
OTEL_RESOURCE_ATTRIBUTES | service.name=app,service.namespace=team,deployment.environment=prod |
OTEL_SERVICE_NAME | service.name 的简写 |
OTEL_TRACES_SAMPLER / _ARG | parentbased_traceidratio / 0.1 |
故障排查
- OTLP 网关返回 401 → 实例 ID 不是数字,或 API 密钥缺少发布者权限
- 返回 404 → 端点 URL 错误(必须以
/otlp结尾) - 缺少 Span → 检查
OTEL_EXPORTER_OTLP_PROTOCOL是否与传输方式匹配(Cloud OTLP 网关 =http/protobuf,本地 Alloy =grpc) - Node.js 自动埋点在打包后失效 →
@vercel/ncc等打包工具会破坏 require 钩子 - Gunicorn / uWSGI 下的 Python 没有 Span → 在 post-fork 钩子中重新初始化 OTel providers
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