Python 语言快速开始

快速开始

本文将描述您如何在 Python 中开始使用 OpenTelemetry即OTel。您将学习如何对一个简单的Python应用程序进行观测，并向控制台上报trace、log、metrics数据

请确保您已经安装

Demo示例

下文将展示以一个简单的 Flask 应用程序接入OTel Python 探针的过程。当然，OTel Python 探针也支持Django、FastAPI等框架。有关支持框架的库的完整列表，详见：OTel Python探针插件支持列表

首先，我们创建一个新的目录，并设置新的python环境

mkdir otel-getting-started
cd otel-getting-started
python3 -m venv venv
source ./venv/bin/activate

使用pip安装Flask:

pip install flask

创建并启动一个HTTP服务器

新建一个名为 app.py 的文件，具体代码如下:

from random import randint
from flask import Flask, request
import logging

app = Flask(__name__)
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

@app.route("/rolldice")
def roll_dice():
    player = request.args.get('player', default=None, type=str)
    result = str(roll())
    if player:
        logger.warning("%s is rolling the dice: %s", player, result)
    else:
        logger.warning("Anonymous player is rolling the dice: %s", result)
    return result

def roll():
    return randint(1, 6)

使用以下命令运行应用程序，并在您的网页浏览器中打开 http://localhost:8080/rolldice 以确保它正常工作。

flask run -p 8080

接入OTel Python探针

使用无侵入方式接入OTel Python探针，您不需要更改任何代码既可拥有完整的可观测数据，详见：无侵入注入原理 .

首先需要安装 opentelemetry-distro 、 opentelemetry-bootstrap 、 opentelemetry-instrument 三个package，具体的

Step 1. 安装opentelemetry-distro

pip install opentelemetry-distro

Step 2. 使用 `opentelemetry-bootstrap` 命令安装观测应用所需的埋点插件

opentelemetry-bootstrap -a install

在本示例中这将会安装观测Flask的插件。

Run 使用OTel Python探针来启动应用

export OTEL_PYTHON_LOGGING_AUTO_INSTRUMENTATION_ENABLED=true
opentelemetry-instrument \
    --traces_exporter console \
    --metrics_exporter console \
    --logs_exporter console \
    --service_name dice-server \
    flask run -p 8080

在您的网页浏览器中打开 http://localhost:8080/rolldice，并多次刷新页面。过一段时间后，您应该会在控制台中看到打印出的 spans，如下所示：

{
    "name": "/rolldice",
    "context": {
        "trace_id": "0xdb1fc322141e64eb84f5bd8a8b1c6d1f",
        "span_id": "0x5c2b0f851030d17d",
        "trace_state": "[]"
    },
    "kind": "SpanKind.SERVER",
    "parent_id": null,
    "start_time": "2023-10-10T08:14:32.630332Z",
    "end_time": "2023-10-10T08:14:32.631523Z",
    "status": {
        "status_code": "UNSET"
    },
    "attributes": {
        "http.method": 




    
"GET",
        "http.server_name": "127.0.0.1",
        "http.scheme": "http",
        "net.host.port": 8080,
        "http.host": "localhost:8080",
        "http.target": "/rolldice?rolls=12",
        "net.peer.ip": "127.0.0.1",
        "http.user_agent": "curl/8.1.2",
        "net.peer.port": 58419,
        "http.flavor": "1.1",
        "http.route": "/rolldice",
        "http.status_code": 200
    },
    "events": [],
    "links": [],
    "resource": {
        "attributes": {
            "telemetry.sdk.language": "python",
            "telemetry.sdk.name": "opentelemetry",
            "telemetry.sdk.version": "1.17.0",
            "service.name": "dice-server",
            "telemetry.auto.version": "0.38b0"
        },
        "schema_url": ""
    }
}
{
    "body": "Anonymous player is rolling the dice: 3",
    "severity_number": "<SeverityNumber.WARN: 13>",
    "severity_text": "WARNING",
    "attributes": {
        "otelSpanID": "5c2b0f851030d17d",
        "otelTraceID": "db1fc322141e64eb84f5bd8a8b1c6d1f",
        "otelServiceName": "dice-server"
    },
    "timestamp": "2023-10-10T08:14:32.631195Z",
    "trace_id": "0xdb1fc322141e64eb84f5bd8a8b1c6d1f",
    "span_id": "0x5c2b0f851030d17d",
    "trace_flags": 1,
    "resource": "BoundedAttributes({'telemetry.sdk.language': 'python', 'telemetry.sdk.name': 'opentelemetry', 'telemetry.sdk.version': '1.17.0', 'service.name': 'dice-server', 'telemetry.auto.version': '0.38b0'}, maxlen=None)"
}

生成的 span 是对 /rolldice 路由的请求生命周期。在请求期间发出的调用链中包含相同的Trace ID 和 span ID，并通过Span Exporter导出到控制台。

发送几条请求到该端点，然后稍等片刻或终止应用程序，你将会在控制台输出中看到一些指标，例如以下内容：

{
  "resource_metrics": [
    {
      "resource": {
        "attributes": {
          "service.name": "unknown_service",
          "telemetry.auto.version": "0.34b0",
          "telemetry.sdk.language": "python",
          "telemetry.sdk.name": "opentelemetry",
          "telemetry.sdk.version": "1.13.0"
        },
        "schema_url": ""
      },
      "schema_url": "",
      "scope_metrics": [
        {
          "metrics": [
            {
              "data": {
                "aggregation_temporality": 2,
                "data_points": [
                  {
                    "attributes": {
                      "http.flavor": "1.1",
                      "http.host": "localhost:5000",
                      "http.method": "GET",
                      "http.scheme": "http",
                      "http.server_name": "127.0.0.1"
                    },
                    "start_time_unix_nano": 1666077040061693305,
                    "time_unix_nano": 1666077098181107419,
                    "value": 0
                  }
                




    
],
                "is_monotonic": false
              },
              "description": "measures the number of concurrent HTTP requests that are currently in-flight",
              "name": "http.server.active_requests",
              "unit": "requests"
            },
            {
              "data": {
                "aggregation_temporality": 2,
                "data_points": [
                  {
                    "attributes": {
                      "http.flavor": "1.1",
                      "http.host": "localhost:5000",
                      "http.method": "GET",
                      "http.scheme": "http",
                      "http.server_name": "127.0.0.1",
                      "http.status_code": 200,
                      "net.host.port": 5000
                    },
                    "bucket_counts": [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
                    "count": 1,
                    "explicit_bounds": [
                      0, 5, 10, 25, 50, 75, 100, 250, 500, 1000
                    ],
                    "max": 1,
                    "min": 1,
                    "start_time_unix_nano": 1666077040063027610,
                    "sum": 1,
                    "time_unix_nano": 1666077098181107419
                  }
                ]
              },
              "description": "measures the duration of the inbound HTTP request",
              "name": "http.server.duration",
              "unit": "ms"
            }
          ],
          "schema_url": "",
          "scope": {
            "name": "opentelemetry.instrumentation.flask",
            "schema_url": "",
            "version": "0.34b0"
          }
        }
      ]
    }
  ]
}

手动埋点与自动埋点联动

自动埋点主要用于采集一些常用组件的观测数据，如HTTP请求的信息，但是没法自动观测应用业务的数据。如果需要采集业务的观测数据，需要手动埋点，以上是进行手动埋点和自动埋点联动的例子：

手动埋点采集日志

首先更改上文中的app.py代码，获取当前trace实例，tracer，并使用tracer来新建一条新的trace。

from random import randint
from flask import Flask

from opentelemetry import trace

# Acquire a tracer
tracer = trace.get_tracer("diceroller.tracer")

app = Flask(__name__)

@app.route("/rolldice")
def roll_dice():
    return str(roll())

def roll():
    # This creates a new span that's the child of the current one
    with tracer.start_as_current_span("roll") as rollspan:
        




    
res = randint(1, 6)
        rollspan.set_attribute("roll.value", res)
        return res

重新使用OTel Python探针启动应用：

export OTEL_PYTHON_LOGGING_AUTO_INSTRUMENTATION_ENABLED=true
opentelemetry-instrument \
    --traces_exporter console \
    --metrics_exporter console \
    --logs_exporter console \
    --service_name dice-server \
    flask run -p 8080

这时在向Flask Web服务器发送请求时，您将看到两个Span，如下所示：

{
    "name": "roll",
    "context": {
        "trace_id": "0x6f781c83394ed2f33120370a11fced47",
        "span_id": "0x623321c35b8fa837",
        "trace_state": "[]"
    },
    "kind": "SpanKind.INTERNAL",
    "parent_id": "0x09abe52faf1d80d5",
    "start_time": "2023-10-10T08:18:28.679261Z",
    "end_time": "2023-10-10T08:18:28.679560Z",
    "status": {
        "status_code": "UNSET"
    },
    "attributes": {
        "roll.value": "6"
    },
    "events": [],
    "links": [],
    "resource": {
        "attributes": {
            "telemetry.sdk.language": "python",
            "telemetry.sdk.name": "opentelemetry",
            "telemetry.sdk.version": "1.17.0",
            "service.name": "dice-server",
            "telemetry.auto.version": "0.38b0"
        },
        "schema_url": ""
    }
}
{
    "name": "/rolldice",
    "context": {
        "trace_id": "0x6f781c83394ed2f33120370a11fced47",
        "span_id": "0x09abe52faf1d80d5",
        "trace_state": "[]"
    },
    "kind": "SpanKind.SERVER",
    "parent_id": null,
    "start_time": "2023-10-10T08:18:28.678348Z",
    "end_time": "2023-10-10T08:18:28.679677Z",
    "status": {
        "status_code": "UNSET"
    },
    "attributes": {
        "http.method": "GET",
        "http.server_name": "127.0.0.1",
        "http.scheme": "http",
        "net.host.port": 8080,
        "http.host": "localhost:8080",
        "http.target": "/rolldice?rolls=12",
        "net.peer.ip": "127.0.0.1",
        "http.user_agent": "curl/8.1.2",
        "net.peer.port": 58485,
        "http.flavor": "1.1",
        "http.route": "/rolldice",
        "http.status_code": 200
    },
    "events": [],
    "links": [],
    "resource": {
        "attributes": {
            "telemetry.sdk.language": "python",
            "telemetry.sdk.name": "opentelemetry",
            "telemetry.sdk.version": "1.17.0",
            "service.name": "dice-server",
            "telemetry.auto.version": "0.38b0"
        },
        "schema_url": ""
    }




    
}

roll Span的的parent_id与/rolldice的span_id相同，这表明了其父子关系。

手动采集指标

修改 app.py 文件，在代码中初始化一个meter，并使用meter创建一个Counter类型的指标，用于统计每个可能请求数量。

# These are the necessary import declarations
from opentelemetry import trace
from opentelemetry import metrics

from random import randint
from flask import Flask, request
import logging

# Acquire a tracer
tracer = trace.get_tracer("diceroller.tracer")
# Acquire a meter.
meter = metrics.get_meter("diceroller.meter")

# Now create a counter instrument to make measurements with
roll_counter = meter.create_counter(
    "dice.rolls",
    description="The number of rolls by roll value",
)

app = Flask(__name__)
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

@app.route("/rolldice")
def roll_dice():
    # This creates a new span that's the child of the current one
    with tracer.start_as_current_span("roll") as roll_span:
        player = request.args.get('player', default = None, type = str)
        result = str(roll())
        roll_span.set_attribute("roll.value", result)
        # This adds 1 to the counter for the given roll value
        roll_counter.add(1, {"roll.value": result})
        if player:
            logger.warn("{} is rolling the dice: {}", player, result)
        else:
            logger.warn("Anonymous player is rolling the dice: %s", result)
        return result

def roll():
    return randint(1, 6)

重新启动应用：

export OTEL_PYTHON_LOGGING_AUTO_INSTRUMENTATION_ENABLED=true
opentelemetry-instrument \
    --traces_exporter console \
    --metrics_exporter console \
    --logs_exporter console \
    --service_name dice-server \
    flask run -p 8080

当你向服务器发送请求时，你将在控制台看到请求roll的计数指标被输出，并且每次请求roll都有单独的计数：

{
  "resource_metrics": [
    {
      "resource": {
        "attributes": {
          "telemetry.sdk.language": "python",
          "telemetry.sdk.name": "opentelemetry",
          "telemetry.sdk.version": "1.17.0",
          "service.name": "dice-server",
          "telemetry.auto.version": "0.38b0"
        },




    
        "schema_url": ""
      },
      "scope_metrics": [
        {
          "scope": {
            "name": "opentelemetry.instrumentation.flask",
            "version": "0.38b0",
            "schema_url": ""
          },
          "metrics": [
            {
              "name": "http.server.active_requests",
              "description": "measures the number of concurrent HTTP requests that are currently in-flight",
              "unit": "requests",
              "data": {
                "data_points": [
                  {
                    "attributes": {
                      "http.method": "GET",
                      "http.host": "localhost:8080",
                      "http.scheme": "http",
                      "http.flavor": "1.1",
                      "http.server_name": "127.0.0.1"
                    },
                    "start_time_unix_nano": 1696926005694857000,
                    "time_unix_nano": 1696926063549782000,
                    "value": 0
                  }
                ],
                "aggregation_temporality": 2,
                "is_monotonic": false
              }
            },
            {
              "name": "http.server.duration",
              "description": "measures the duration of the inbound HTTP request",
              "unit": "ms",
              "data": {
                "data_points": [
                  {
                    "attributes": {
                      "http.method": "GET",
                      "http.host": "localhost:8080",
                      "http.scheme": "http",
                      "http.flavor": "1.1",
                      "http.server_name": "127.0.0.1",
                      "net.host.port": 8080,
                      "http.status_code": 200
                    },
                    "start_time_unix_nano": 1696926005695798000,
                    "time_unix_nano": 1696926063549782000,
                    "count": 7,
                    "sum": 6,
                    "bucket_counts": [
                      1, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
                    ],
                    "explicit_bounds": [
                      0.0, 5.0, 10.0, 25.0, 50.0, 75.0, 100.0, 250.0, 500.0,
                      750.0, 1000.0, 2500.0, 5000.0, 7500.0, 10000.0
                    ],
                    "min": 0,
                    "max": 1
                  }
                ],
                "aggregation_temporality": 2
              }
            }
          ],
          "schema_url": ""
        },
        {
          "scope": {
            "name": "diceroller.meter",
            "version": "",
            "schema_url": ""
          },
          "metrics": [
            {
              "name": "dice.rolls",
              "description": "The number of rolls by roll value",
              "unit": "",
              "data": {
                




    
"data_points": [
                  {
                    "attributes": {
                      "roll.value": "5"
                    },
                    "start_time_unix_nano": 1696926005695491000,
                    "time_unix_nano": 1696926063549782000,
                    "value": 3
                  },
                  {
                    "attributes": {
                      "roll.value": "6"
                    },
                    "start_time_unix_nano": 1696926005695491000,
                    "time_unix_nano": 1696926063549782000,
                    "value": 1
                  },
                  {
                    "attributes": {
                      "roll.value": "1"
                    },
                    "start_time_unix_nano": 1696926005695491000,
                    "time_unix_nano": 1696926063549782000,
                    "value": 1
                  },
                  {
                    "attributes": {
                      "roll.value": "3"
                    },
                    "start_time_unix_nano": 1696926005695491000,
                    "time_unix_nano": 1696926063549782000,
                    "value": 1
                  },
                  {
                    "attributes": {
                      "roll.value": "4"
                    },
                    "start_time_unix_nano": 1696926005695491000,
                    "time_unix_nano": 1696926063549782000,
                    "value": 1
                  }
                ],
                "aggregation_temporality": 2,
                "is_monotonic": true
              }
            }
          ],
          "schema_url": ""
        }
      ],
      "schema_url": ""
    }
  ]
}

将观测数据发往 OTel Collector

OTel Collector 是大多数生产部署中一个关键的组件。以下是一些使用OTel Collector的优势：

● 一个由多个服务共享的单一可观测数据收集器，以减少切换Exporter的开销

在发往服务端之前可以集中处理trace，避免重复处理操作

● 可以聚合多个服务、多个主机上的Trace

除非您只有一个服务或正在进行测试，否则在生产部署中，推荐您使用收集器

配置并启动一个本地的OTel Collector

首先，将以下OTel Collector配置代码保存到 /tmp/ 目录中的文件中：

receivers:
  otlp:
    protocols:
      grpc:
        endpoint: 0.0.0.0:4317
      http




    
:
        endpoint: 0.0.0.0:4318
exporters:
  # NOTE: Prior to v0.86.0 use `logging` instead of `debug`.
  debug:
    verbosity: detailed
processors:
  batch:
service:
  pipelines:
    traces:
      receivers: [otlp]
      exporters: [debug]
      processors: [batch]
    metrics:
      receivers: [otlp]
      exporters: [debug]
      processors: [batch]
    logs:
      receivers: [otlp]
      exporters: [debug]
      processors: [batch]

以上配置将使用otlp 协议来接收用户的输入，即OTel Python探针与OTel Collector之间使用otlp 协议进行通信。并将数据最终打印在OTel Collector控制台。您也可以将数据上报至于Prometheus 或者Jaeger中，详细的配置信息见： OTel Collector配置

然后运行 Docker 命令，根据此配置获取并运行OTel Collector：

docker run -p 4317:4317 \
    -v /tmp/otel-collector-config.yaml:/etc/otel-collector-config.yaml \
    otel/opentelemetry-collector:latest \
    --config=/etc/otel-collector-config.yaml

您现在将在本地运行一个OTel Collector实例，该实例监听4317端口。

修改OTel Python 探针的启动命令，使用OTLP上报Trace和Metrics

下一步是修改命令，使其通过 OTLP 将Trace和Metrics发送到OTel Collector中，而不是打印到控制台。

首先安装OTLP exporter :

pip install opentelemetry-exporter-otlp

opentelemetry-instrument 将会检测到您刚刚安装的包，并在下次运行时默认为 OTLP 导出。

像之前一样运行应用程序，但不要打印到控制台：

export OTEL_PYTHON_LOGGING_AUTO_INSTRUMENTATION_ENABLED=true
opentelemetry-instrument --logs_exporter otlp flask run -p 8080

默认情况下，opentelemetry-instrument 通过 OTLP/gRPC 导出追踪和指标，并将它们发送到 localhost:4317，即发送到上文启动的OTel Collector中，

此时再访问 /rolldice 地址时，你会在OTel Collector 进程中看到输出，而不是在 Flask 进程中：

2022-06-09T20:43:39.915Z        DEBUG   debugexporter/debug_exporter.go:51  ResourceSpans #0
Resource labels:
     -> telemetry.sdk.language: STRING(python)
     -> telemetry.sdk.name: STRING(opentelemetry)
     -> telemetry.sdk.version: STRING(1.12.0rc1)
     -> telemetry.auto.version: STRING(0.31b0)
     -> service.name: STRING(unknown_service)
InstrumentationLibrarySpans #0
InstrumentationLibrary app
Span #0
    Trace ID       : 7d4047189ac3d5f96d590f974bbec20a
    Parent ID      : 0b21630539446c31
    ID             : 4d18cee9463a79ba
    Name           : roll
    Kind           : SPAN_KIND_INTERNAL
    Start time     : 2022-06-09 20:43:37.390134089 +0000 UTC
    End time       : 2022-06-09 20:43:37.390327687 +0000 UTC
    Status code    : STATUS_CODE_UNSET
    Status message :
Attributes:
     -> roll.value: INT(5)
InstrumentationLibrarySpans #1
InstrumentationLibrary opentelemetry.instrumentation.flask 0.31b0
Span #0
    Trace ID       : 7d4047189ac3d5f96d590f974bbec20a
    Parent ID      :
    ID             : 0b21630539446c31
    Name           : /rolldice
    Kind           : SPAN_KIND_SERVER
    Start time     : 2022-06-09 20:43:37.388733595 +0000 UTC
    End time       : 2022-06-09 20:43:37.390723792 +0000 UTC
    Status code    : STATUS_CODE_UNSET
    Status message :
Attributes:
     -> http.method: STRING(GET)
     -> http.server_name: STRING(127.0.0.1)
     -> http.scheme: STRING(http)
     -> net.host.port: INT(5000)
     -> http.host: STRING(localhost:5000)
     -> http.target: STRING(/rolldice)
     -> net.peer.ip: STRING(127.0.0.1)
     -> http.user_agent: STRING(curl/7.82.0)
     -> net.peer.port: INT(53878)
     -> http.flavor: STRING(1.1)
     -> http.route: STRING(/rolldice)
     -> http.status_code: INT(200)

2022-06-09T20:43:40.025Z        INFO    debugexporter/debug_exporter.go:56  MetricsExporter {"#metrics": 1}
2022-06-09T20:43:40.025Z        DEBUG   debugexporter/debug_exporter.go:66  ResourceMetrics #0
Resource labels:
     -> telemetry.sdk.language: STRING(python)
     -> telemetry.sdk.name: STRING(opentelemetry)
     -> telemetry.sdk.version: STRING(1.12.0rc1)
     -> telemetry.auto.version: STRING(0.31b0)
     -> service.name: STRING(unknown_service)
InstrumentationLibraryMetrics #0
InstrumentationLibrary app
Metric #0
Descriptor:
     -> Name: roll_counter
     -> Description: The number of rolls by roll value
     -> Unit:
     -> DataType: Sum
     -> IsMonotonic: true
     -> AggregationTemporality: AGGREGATION_TEMPORALITY_CUMULATIVE
NumberDataPoints #0
Data point attributes:
     -> roll.value: INT(5)
StartTimestamp: 2022-06-09 20:43:37.390226915 +0000 UTC
Timestamp: 2022-06-09 20:43:39.848587966 +0000 UTC
Value: 1

如果OTel Collector配置为上报至jaeger，将会出现如下记录：