遷移至 OpenTelemetry Python

pip install aws-xray-sdk
        

pip install opentelemetry-api opentelemetry-sdk opentelemetry-exporter-otlp opentelemetry-propagator-aws-xray
        

在 X-Ray 中，全域xray_recorder會初始化並用來產生區段和子區段。

在 OpenTelemetry 中，您需要初始化全域 TracerProvider。使用此 TracerProvider，您可以取得 Tracer，用於在應用程式中任何位置產生範圍。建議您設定下列元件：

from opentelemetry import (
    trace,
    propagate
)
from opentelemetry.sdk.trace import TracerProvider

from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.propagators.aws import AwsXRayPropagator

# Sends generated traces in the OTLP format to an OTel Collector running on port 4318
otlp_exporter = OTLPSpanExporter(endpoint="http://localhost:4318/v1/traces")
# Processes traces in batches as opposed to immediately one after the other
span_processor = BatchSpanProcessor(otlp_exporter)
# More configurations can be done here. We will visit them later.

# Sets the global default tracer provider
provider = TracerProvider(active_span_processor=span_processor)
trace.set_tracer_provider(provider)

# Configures the global propagator to use the X-Ray Propagator
propagate.set_global_textmap(AwsXRayPropagator())

# Creates a tracer from the global tracer provider
tracer = trace.get_tracer("my.tracer.name")
# Use this tracer to create Spans
          

X-Ray Python SDK 支援應用程式架構，例如 Django、Flask 和 Bottle，以追蹤在其上執行的 Python 應用程式傳入請求。方法是將 XRayMiddleware新增至每個架構的應用程式。

OpenTelemetry 透過特定的檢測程式庫提供 Django 和 Flask 的檢測。OpenTelemetry 中沒有可用的 Bottle 檢測，仍然可以使用 OpenTelemetry WSGI 檢測來追蹤應用程式。

針對下列程式碼範例，您需要下列相依性：

pip install opentelemetry-instrumentation-flask
        

您必須先初始化 OpenTelemetry SDK 並註冊全域 TracerProvider，才能為您的應用程式架構新增檢測。如果沒有它，追蹤操作將是 no-ops。設定全域 之後TracerProvider，您就可以針對應用程式架構使用 檢測器。下列範例示範 Flask 應用程式。

from flask import Flask
from opentelemetry import trace
from opentelemetry.instrumentation.flask import FlaskInstrumentor
from opentelemetry.sdk.extension.aws.resource import AwsEc2ResourceDetector
from opentelemetry.sdk.resources import get_aggregated_resources
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor, ConsoleSpanExporter

provider = TracerProvider(resource=get_aggregated_resources(
    [
        AwsEc2ResourceDetector(),
    ]))

processor = BatchSpanProcessor(ConsoleSpanExporter())
provider.add_span_processor(processor)
trace.set_tracer_provider(provider)

# Creates a tracer from the global tracer provider
tracer = trace.get_tracer("my.tracer.name")

app = Flask(__name__)

# Instrument the Flask app
FlaskInstrumentor().instrument_app(app)


@app.route('/')
def hello_world():
    return 'Hello World!'


if __name__ == '__main__':
    app.run()
        

X-Ray Python SDK 透過修補程式botocore庫來追蹤 AWS SDK 用戶端請求。如需詳細資訊，請參閱使用適用於 Python 的 X-Ray AWS SDK 追蹤 SDK 呼叫。在您的應用程式中， patch_all()方法用於使用 或 程式庫，選擇性地檢測所有boto3程式庫botocore或修補程式patch((['botocore']))。任何選擇的方法都會檢測應用程式中的所有 Boto3 用戶端，並針對使用這些用戶端進行的任何呼叫產生子區段。

針對下列程式碼範例，您將需要下列相依性：

pip install opentelemetry-instrumentation-botocore
        

以程式設計方式使用 OpenTelemetry Botocore 檢測來檢測應用程式中的所有 Boto3 用戶端。下列範例示範 botocore 檢測。

import boto3
import opentelemetry.trace as trace
from botocore.exceptions import ClientError
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.resources import get_aggregated_resources
from opentelemetry.sdk.trace.export import (
    BatchSpanProcessor,
    ConsoleSpanExporter,
)
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor

provider = TracerProvider()
processor = BatchSpanProcessor(ConsoleSpanExporter())
provider.add_span_processor(processor)
trace.set_tracer_provider(provider)

# Creates a tracer from the global tracer provider
tracer = trace.get_tracer("my.tracer.name")

# Instrument BotoCore
BotocoreInstrumentor().instrument()

# Initialize S3 client
s3 = boto3.client("s3", region_name="us-east-1")

# Your bucket name
bucket_name = "my-example-bucket"

# Get bucket location (as an example of describing it)
try:
    response = s3.get_bucket_location(Bucket=bucket_name)
    region = response.get("LocationConstraint") or "us-east-1"
    print(f"Bucket '{bucket_name}' is in region: {region}")

    # Optionally, get bucket's creation date via list_buckets
    buckets = s3.list_buckets()
    for bucket in buckets["Buckets"]:
        if bucket["Name"] == bucket_name:
            print(f"Bucket created on: {bucket['CreationDate']}")
            break
except ClientError as e:
    print(f"Failed to describe bucket: {e}")
        

X-Ray Python SDK 透過修補請求程式庫，透過請求追蹤傳出的 HTTP 呼叫。如需詳細資訊，請參閱使用適用於 Python 的 X-Ray 開發套件追蹤對下游 HTTP Web 服務的呼叫。在您的應用程式中，您可以使用 patch_all()方法來檢測所有程式庫，或使用 選擇性地修補請求程式庫patch((['requests']))。任何選項都會檢測requests程式庫，為透過 進行的任何呼叫產生子區段requests。

針對下列程式碼範例，您將需要下列相依性：

pip install opentelemetry-instrumentation-requests
        

以程式設計方式使用 OpenTelemetry Requests Instrumentation 來檢測請求程式庫，為應用程式中提出的 HTTP 請求產生追蹤。如需詳細資訊，請參閱 OpenTelemetry 請求檢測 。下列範例示範程式requests庫檢測。

from opentelemetry.instrumentation.requests import RequestsInstrumentor

# Instrument Requests
RequestsInstrumentor().instrument()

...

    example_session = requests.Session()
    example_session.get(url="https://example.com")
        

或者，您也可以檢測基礎urllib3程式庫來追蹤 HTTP 請求：

# pip install opentelemetry-instrumentation-urllib3
from opentelemetry.instrumentation.urllib3 import URLLib3Instrumentor

# Instrument urllib3
URLLib3Instrumentor().instrument()

...

    example_session = requests.Session()
    example_session.get(url="https://example.com")