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AWS X-Ray
Developer Guide

Tracing Incoming Requests with the X-Ray SDK for Python Middleware

If you use Django or Flask, use the Django middleware or Flask middleware to instrument incoming HTTP requests. When you add the middleware to your application and configure a segment name, the X-Ray SDK for Python creates a segment for each sampled request. This segment includes timing, method, and disposition of the HTTP request. Additional instrumentation creates subsegments on this segment.

Note

For AWS Lambda functions, Lambda creates a segment for each sampled request. See AWS Lambda and AWS X-Ray for more information.

See Worker for a example Python function instrumented in Lambda.

For scripts or Python applications on other frameworks, you can create segments manually.

Each segment has a name that identifies your application in the service map. The segment can be named statically, or you can configure the SDK to name it dynamically based on the host header in the incoming request. Dynamic naming lets you group traces based on the domain name in the request, and apply a default name if the name doesn't match an expected pattern (for example, if the host header is forged).

Forwarded Requests

If a load balancer or other intermediary forwards a request to your application, X-Ray takes the client IP from the X-Forwarded-For header in the request instead of from the source IP in the IP packet. The client IP that is recorded for a forwarded request can be forged, so it should not be trusted.

When a request is forwarded, the SDK sets an additional field in the segment to indicate this. If the segment contains the field x_forwarded_for set to true, the client IP was taken from the X-Forwarded-For header in the HTTP request.

The middleware creates a segment for each incoming request with an http block that contains the following information:

  • HTTP method – GET, POST, PUT, DELETE, etc.

  • Client address – The IP address of the client that sent the request.

  • Response code – The HTTP response code for the completed request.

  • Timing – The start time (when the request was received) and end time (when the response was sent).

  • User agent — The user-agent from the request.

  • Content length — The content-length from the response.

Adding the Middleware to Your Application (Django)

Add the middleware to the MIDDLEWARE list in your settings.py file. The X-Ray middleware should be the first line in your settings.py file to ensure that requests that fail in other middleware are recorded.

Example settings.py - X-Ray SDK for Python middleware

MIDDLEWARE = [ 'aws_xray_sdk.ext.django.middleware.XRayMiddleware', 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware' ]

Configure a segment name in your settings.py file.

Example settings.py – segment name

XRAY_RECORDER = {, 'AWS_XRAY_TRACING_NAME': 'My application', 'PLUGINS': ('EC2Plugin'), }

This tells the X-Ray recorder to trace requests served by your Django application with the default sampling rate. You can configure the recorder your Django settings file to apply custom sampling rules or change other settings.

Adding the Middleware to Your Application (Flask)

To instrument your Flask application, first configure a segment name on the xray_recorder. Then, use the XRayMiddleware function to patch your Flask application in code.

Example app.py

from aws_xray_sdk.core import xray_recorder from aws_xray_sdk.ext.flask.middleware import XRayMiddleware app = Flask(__name__) xray_recorder.configure(service='My application') XRayMiddleware(app, xray_recorder)

This tells the X-Ray recorder to trace requests served by your Flask application with the default sampling rate. You can configure the recorder in code to apply custom sampling rules or change other settings.

Instrumenting Python Code Manually

If you don't use Django or Flask, you can create segments manually. You can create a segment for each incoming request, or create segments around patched HTTP or AWS SDK clients to provide context for the recorder to add subsegments.

Example main.py – manual instrumentation

from aws_xray_sdk.core import xray_recorder # Start a segment segment = xray_recorder.begin_segment('segment_name') # Start a subsegment subsegment = xray_recorder.begin_subsegment('subsegment_name') # Add metadata and annotations segment.put_metadata('key', dict, 'namespace') subsegment.put_annotation('key', 'value') # Close the subsegment and segment xray_recorder.end_subsegment() xray_recorder.end_segment()

Configuring a Segment Naming Strategy

AWS X-Ray uses a service name to identify your application and distinguish it from the other applications, databases, external APIs, and AWS resources that your application uses. When the X-Ray SDK generates segments for incoming requests, it records your application's service name in the segment's name field.

The X-Ray SDK can name segments after the hostname in the HTTP request header. However, this header can be forged, which could result in unexpected nodes in your service map. To prevent the SDK from naming segments incorrectly due to requests with forged host headers, you must specify a default name for incoming requests.

If your application serves requests for multiple domains, you can configure the SDK to use a dynamic naming strategy to reflect this in segment names. A dynamic naming strategy allows the SDK to use the hostname for requests that match an expected pattern, and apply the default name to requests that don't.

For example, you might have a single application serving requests to three subdomains– www.example.com, api.example.com, and static.example.com. You can use a dynamic naming strategy with the pattern *.example.com to identify segments for each subdomain with a different name, resulting in three service nodes on the service map. If your application receives requests with a hostname that doesn't match the pattern, you will see a fourth node on the service map with a fallback name that you specify.

To use the same name for all request segments, specify the name of your application when you configure the recorder, as shown in the previous sections.

A dynamic naming strategy defines a pattern that hostnames should match, and a default name to use if the hostname in the HTTP request doesn't match the pattern. To name segments dynamically in Django, add the DYNAMIC_NAMING setting to your settings.py file.

Example settings.py – dynamic naming

XRAY_RECORDER = { 'AUTO_INSTRUMENT': True, 'AWS_XRAY_TRACING_NAME': 'My application', 'DYNAMIC_NAMING': '*.example.com', 'PLUGINS': ('ElasticBeanstalkPlugin', 'EC2Plugin'), }

You can use '*' in the pattern to match any string, or '?' to match any single character. For Flask, configure the recorder in code.

Example main.py – segment name

from aws_xray_sdk.core import xray_recorder xray_recorder.configure(service='My application') xray_recorder.configure(dynamic_naming='*.example.com')

Note

You can override the default service name that you define in code with the AWS_XRAY_TRACING_NAME environment variable.