OpenTelemetry 可观测¶

# Python SDK
pip install opentelemetry-api opentelemetry-sdk
pip install opentelemetry-exporter-otlp  # OTLP 导出器
pip install opentelemetry-instrumentation-fastapi  # FastAPI 自动埋点

from opentelemetry import trace, metrics
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.resources import Resource

# 初始化
resource = Resource.create({"service.name": "bioinfo-api"})
provider = TracerProvider(resource=resource)
provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
trace.set_tracer_provider(provider)

tracer = trace.get_tracer("bioinfo-api")

# 手动创建 Span
with tracer.start_as_current_span("run_analysis") as span:
    span.set_attribute("sample_id", "S001")  # 添加属性
    span.add_event("analysis_started")  # 添加事件
    # 执行分析...
    span.set_status(trace.StatusCode.OK)

# FastAPI 自动埋点
from opentelemetry.instrumentation.fastapi import FastAPIInstrumentor
FastAPIInstrumentor.instrument_app(app)  # 自动追踪所有请求

# otel-collector-config.yaml
receivers:
  otlp:
    protocols:
      grpc: { endpoint: "0.0.0.0:4317" }
      http: { endpoint: "0.0.0.0:4318" }

processors:
  batch: { timeout: 5s }

exporters:
  jaeger: { endpoint: "jaeger:14250" }
  prometheus: { endpoint: "0.0.0.0:8889" }

service:
  pipelines:
    traces:
      receivers: [otlp]
      processors: [batch]
      exporters: [jaeger]
    metrics:
      receivers: [otlp]
      processors: [batch]
      exporters: [prometheus]

# === 三大信号 ===
# Traces:  请求在服务间的流转路径（定位慢在哪）
# Metrics: 数值指标（CPU、QPS、延迟分布）
# Logs:    文本事件记录（调试详情）

# === 常用导出器 ===
# OTLP → 通用格式（推荐）
# Jaeger → 分布式追踪
# Prometheus → 指标监控
# Zipkin → 分布式追踪

# === 自动埋点库 ===
# opentelemetry-instrumentation-fastapi
# opentelemetry-instrumentation-django
# opentelemetry-instrumentation-flask
# opentelemetry-instrumentation-requests
# opentelemetry-instrumentation-sqlalchemy