前言
某天一位業務研發老哥跑來諮詢
- 研發老哥:我的服務出現了504,但是不太清楚是哪個環節報錯,每次請求需要訪問4個微服務、2個數據庫、1個redis、1個消息隊列。。。
- 苦逼運維:停停停,不要再説了,目前不支持鏈路追蹤,只能手動幫你一個服務一個服務的排查了
- 先請老哥大概描述了一下業務邏輯以及訪問方式,10分鐘過去了。再逐級排查每個服務以及對應訪問的資源層,終於在半小時之後完成了故障定位。。。
這效率也太低了,於是,關於鏈路建設項目提上了議程,目標只有一個,快速定位問題,提高穩定性。而鏈路建設,OpenTelemetry是目前行業熱點,那本運維就來研究研究
環境準備
| 組件 | 版本 |
|---|---|
| 操作系統 | Ubuntu 22.04.4 LTS |
| opentelemetry-sdk | 1.35.0 |
安裝
首先先簡單説一下OpenTelemetry的數據採集流程,然後先跑起來再去討論細節
- OpenTelemetry就是在代碼中埋入採集點進行數據採集,opentelemetry-sdk
- 再通過固定的協議將數據上傳至某個地方進行數據展示,jaeger UI
安裝OpenTelemetry-sdk
pip3 install opentelemetry-sdk opentelemetry-exporter-otlp opentelemetry-api
安裝數據展示jaeger UI
docker pull docker.m.daocloud.io/jaegertracing/all-in-one:latest
docker run -d --name jaeger \
-e COLLECTOR_OTLP_ENABLED=true \
-p 16686:16686 \
-p 4317:4317 \
-p 4318:4318 \
docker.m.daocloud.io/jaegertracing/all-in-one:latest
docker啓動之後訪問:http://127.0.0.1:16686

第一個例子
web服務
首先先準備一個web服務,這裏我們用tornado來實現,安裝tornado:pip3 install tornado
import tornado.httpserver as httpserver
import tornado.web
from tornado.ioloop import IOLoop
class TestFlow(tornado.web.RequestHandler):
def get(self):
self.finish('hello world')
def applications():
urls = []
urls.append([r'/', TestFlow])
return tornado.web.Application(urls)
def main():
app = applications()
server = httpserver.HTTPServer(app)
server.bind(10000, '0.0.0.0')
server.start(1)
IOLoop.current().start()
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt as e:
IOLoop.current().stop()
finally:
IOLoop.current().close()
檢查是否能夠正常訪問:

添加埋點
import tornado.httpserver as httpserver
import tornado.web
from tornado.ioloop import IOLoop
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.resources import SERVICE_NAME, Resource
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
trace.set_tracer_provider(
TracerProvider(resource=Resource.create({SERVICE_NAME: "s1"}))
)
tracer = trace.get_tracer(__name__)
span_processor = BatchSpanProcessor(OTLPSpanExporter(endpoint="http://localhost:4318/v1/traces"))
trace.get_tracer_provider().add_span_processor(span_processor)
class TestFlow(tornado.web.RequestHandler):
def get(self):
views()
self.finish('hello world')
def views():
span = tracer.start_span("s1-span")
span.end()
def applications():
urls = []
urls.append([r'/', TestFlow])
return tornado.web.Application(urls)
def main():
app = applications()
server = httpserver.HTTPServer(app)
server.bind(10000, '0.0.0.0')
server.start(1)
IOLoop.current().start()
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt as e:
IOLoop.current().stop()
finally:
IOLoop.current().close()
再次訪問 curl http://localhost:10000 ,打開jaeger UI查看


已經有數據了,剛才的埋點已經上報至jaeger UI了
埋點數據屬性
豐富一下埋點數據的屬性
def views():
span = tracer.start_span("s1-span")
span.set_attribute("name", "wilson")
span.set_attribute("addr", "cd")
span.end()

增加數據庫訪問追蹤
def views():
span = tracer.start_span("s1-span")
span.set_attribute("name", "wilson")
span.set_attribute("addr", "cd")
ctx = trace.set_span_in_context(span)
get_db(ctx)
span.end()
def get_db(parent_ctx):
span = tracer.start_span("s1-span-db", context=parent_ctx)
span.end()

增加跨服務追蹤
增加第二個web服務:s2.py
import tornado.httpserver as httpserver
import tornado.web
from tornado.ioloop import IOLoop
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.resources import SERVICE_NAME, Resource
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.trace.propagation.tracecontext import TraceContextTextMapPropagator
trace.set_tracer_provider(
TracerProvider(resource=Resource.create({SERVICE_NAME: "s2"}))
)
tracer = trace.get_tracer(__name__)
span_processor = BatchSpanProcessor(OTLPSpanExporter(endpoint="http://localhost:4318/v1/traces"))
trace.get_tracer_provider().add_span_processor(span_processor)
class TestFlow(tornado.web.RequestHandler):
def get(self):
ctx = TraceContextTextMapPropagator().extract(self.request.headers)
span = tracer.start_span("s2-span", context=ctx)
span.end()
self.finish('hello world')
def applications():
urls = []
urls.append([r'/', TestFlow])
return tornado.web.Application(urls)
def main():
app = applications()
server = httpserver.HTTPServer(app)
server.bind(20000, '0.0.0.0')
server.start(1)
IOLoop.current().start()
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt as e:
IOLoop.current().stop()
finally:
IOLoop.current().close()
修改s1.py
from opentelemetry.trace.propagation.tracecontext import TraceContextTextMapPropagator
import requests
def views():
span = tracer.start_span("s1-span")
span.set_attribute("name", "wilson")
span.set_attribute("addr", "cd")
ctx = trace.set_span_in_context(span)
get_db(ctx)
headers = {}
TraceContextTextMapPropagator().inject(headers, context=ctx)
requests.get("http://localhost:20000", headers=headers)
span.end()

改造進k8s
jaeger
編排文件:
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: jaeger
name: jaeger
namespace: default
spec:
replicas: 1
selector:
matchLabels:
app: jaeger
template:
metadata:
labels:
app: jaeger
spec:
containers:
- image: docker.m.daocloud.io/jaegertracing/all-in-one:latest
imagePullPolicy: Always
name: jaeger
dnsPolicy: ClusterFirst
restartPolicy: Always
---
apiVersion: v1
kind: Service
metadata:
labels:
app: jaeger-service
name: jaeger-service
namespace: default
spec:
ports:
- name: port-4317
port: 4317
protocol: TCP
targetPort: 4317
- name: port-4318
port: 4318
protocol: TCP
targetPort: 4318
- name: port-16686
port: 16686
protocol: TCP
targetPort: 16686
selector:
app: jaeger
type: NodePort
s2
1)製作鏡像
由於在k8s集羣中通過svc訪問jaeger,需要改造一下s2.py
s2.py
...
import os
JAEGER_ADDR=os.environ.get('JAEGER_ADDR')
...
span_processor = BatchSpanProcessor(OTLPSpanExporter(endpoint=JAEGER_ADDR))
...
Dockerfile
FROM python:3.8
WORKDIR /opt
RUN pip3 install tornado opentelemetry-api opentelemetry-sdk opentelemetry-exporter-otlp -i https://pypi.tuna.tsinghua.edu.cn/simple
ADD s2.py /opt
CMD python3 s2.py
2)編排文件
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: s2
name: s2
namespace: default
spec:
replicas: 1
selector:
matchLabels:
app: s2
template:
metadata:
labels:
app: s2
spec:
containers:
- env:
- name: JAEGER_ADDR
value: http://jaeger-service:4318/v1/traces
image: s2:v1
imagePullPolicy: Always
name: s2
dnsPolicy: ClusterFirst
restartPolicy: Always
---
apiVersion: v1
kind: Service
metadata:
labels:
app: s2-service
name: s2-service
namespace: default
spec:
ports:
- name: s2-port
port: 20000
protocol: TCP
targetPort: 20000
selector:
app: s2
type: NodePort
s1
1)製作鏡像
由於在k8s集羣中通過svc訪問s2與jaeger,需要改造一下s1.py
s1.py
...
import os
S2_ADDR=os.environ.get('S2_ADDR')
JAEGER_ADDR=os.environ.get('JAEGER_ADDR')
...
span_processor = BatchSpanProcessor(OTLPSpanExporter(endpoint=JAEGER_ADDR))
...
def views():
span = tracer.start_span("s1-span")
span.set_attribute("name", "wilson")
span.set_attribute("addr", "cd")
ctx = trace.set_span_in_context(span)
get_db(ctx)
headers = {}
TraceContextTextMapPropagator().inject(headers, context=ctx)
requests.get(S2_ADDR, headers=headers)
span.end()
...
Dockerfile:
FROM python:3.8
WORKDIR /opt
RUN pip3 install tornado opentelemetry-api opentelemetry-sdk opentelemetry-exporter-otlp -i https://pypi.tuna.tsinghua.edu.cn/simple
ADD s1.py /opt
CMD python3 s1.py
2)編排文件
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: s1
name: s1
namespace: default
spec:
replicas: 1
selector:
matchLabels:
app: s1
template:
metadata:
labels:
app: s1
spec:
containers:
- env:
- name: S2_ADDR
value: http://s2-service:20000
- name: JAEGER_ADDR
value: http://jaeger-service:4318/v1/traces
image: s1:v1
imagePullPolicy: Always
name: s1
dnsPolicy: ClusterFirst
restartPolicy: Always
---
apiVersion: v1
kind: Service
metadata:
labels:
app: s1-service
name: s1-service
namespace: default
spec:
ports:
- name: s1-port
port: 10000
protocol: TCP
targetPort: 10000
selector:
app: s1
type: NodePort
查看結果
▶ kubectl get pod -owide
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
jaeger-6669cd7c4-4pl5j 1/1 Running 0 7m31s 10.244.0.236 minikube <none> <none>
s1-5c569c5b4b-lctzq 1/1 Running 0 73s 10.244.0.237 minikube <none> <none>
s2-5bb648dcdf-mlnbj 1/1 Running 0 61s 10.244.0.238 minikube <none> <none>
▶ kubectl get svc
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
jaeger-service NodePort 10.106.13.217 <none> 4317:31891/TCP,4318:31997/TCP,16686:31002/TCP 5m49s
s1-service NodePort 10.102.25.195 <none> 10000:32376/TCP 4m23s
s2-service NodePort 10.103.114.198 <none> 20000:30032/TCP 3m40s
進行數據測試:
-
訪問s1服務
▶ curl http://192.168.49.2:32376 hello world% -
查看jaeger日誌,訪問:
http://192.168.49.2:31002/
![watermarked-first_10]()
總結
在第一個例子中,我們主要採集了業務服務的trace記錄,即一個完整的請求需要經過的路徑,包括讀取數據庫、跨服務請求等等
在整個跟蹤過程中trace_id與span_id發揮了決定性的作用,前者為請求鏈路的唯一標識,串聯了整個訪問步驟;而後者則是鏈路上每一次不同的具體操作的標識

- 採集:通過嵌入代碼埋點,採集重點監控的流程,比如數據庫讀寫速度、下游服務速度等
- 處理:opentelemetry-sdk對數據進行處理:過濾、緩存、合併
- 導出:將處理過的數據,通過固定的協議(otlp協議、grpc協議、http協議等)發送到後端系統,比如jaeger

聯繫我
- 聯繫我,做深入的交流

至此,本文結束
在下才疏學淺,有撒湯漏水的,請各位不吝賜教...
