opentracing-python-instrumentation
A collection of instrumentation tools to enable tracing with OpenTracing API.
Module
Make sure you are running recent enough versions of pip
and setuptools
, e.g. before installing your project requirements execute this:
pip install --upgrade "setuptools>=29" "pip>=9"
The module name is opentracing_instrumentation
.
What's inside
Supported client frameworks
The following libraries are instrumented for tracing in this module:
urllib2
requests
SQLAlchemy
MySQLdb
psycopg2
- Tornado HTTP client
redis
Server instrumentation
For inbound requests a helper function before_request
is provided for creating middleware for frameworks like Flask and uWSGI.
Manual instrumentation
Finally, a @traced_function
decorator is provided for manual instrumentation.
In-process Context Propagation
request_context
implements thread-local based context propagation facility.
Usage
This library provides two types of instrumentation, explicit instrumentation for server endpoints, and implicit instrumentation for client call sites.
Server endpoints are instrumented by creating a middleware class that:
- initializes the specific tracer implementation
- wraps incoming request handlers into a method that reads the incoming tracing info from the request and creates a new tracing Span
Client call sites are instrumented implicitly by executing a set of
available client_hooks
that monkey-patch some API points in several
common libraries like SQLAlchemy
, urllib2
, Tornado Async HTTP Client.
The initialization of those hooks is usually also done from the middleware
class's __init__
method.
There is a client-server example using this library with Flask instrumentation from opentracing-contrib: https://github.com/opentracing-contrib/python-flask/tree/master/example.
Here's an example of a middleware for Clay framework:
from opentracing_instrumentation.request_context import RequestContextManager
from opentracing_instrumentation.http_server import before_request
from opentracing_instrumentation.http_server import WSGIRequestWrapper
from opentracing_instrumentation.client_hooks import install_all_patches
class TracerMiddleware(object):
def __init__(self, app, wsgi_app):
self.wsgi_app = wsgi_app
self.service_name = app.name
CONFIG.app_name = self.service_name
CONFIG.caller_name_headers.append('X-Uber-Source')
CONFIG.callee_endpoint_headers.append('X-Uber-Endpoint')
install_all_patches()
self.wsgi_app = create_wsgi_middleware(wsgi_app)
self.init_tracer()
def __call__(self, environ, start_response):
return self.wsgi_app(environ, start_response)
def init_tracer(self):
# code specific to your tracer implementation
pass
def create_wsgi_middleware(other_wsgi, tracer=None):
"""
Create a wrapper middleware for another WSGI response handler.
If tracer is not passed in, 'opentracing.tracer' is used.
"""
def wsgi_tracing_middleware(environ, start_response):
# TODO find out if the route can be retrieved from somewhere
request = WSGIRequestWrapper.from_wsgi_environ(environ)
span = before_request(request=request, tracer=tracer)
# Wrapper around the real start_response object to log
# additional information to opentracing Span
def start_response_wrapper(status, response_headers, exc_info=None):
if exc_info is not None:
span.add_tag('error', str(exc_info))
span.finish()
return start_response(status, response_headers)
with RequestContextManager(span=span):
return other_wsgi(environ, start_response_wrapper)
return wsgi_tracing_middleware
And here's an example for middleware in Tornado-based app:
class TracerMiddleware(object):
def __init__(self):
# perform initialization similar to above, including installing
# the client_hooks
@gen.coroutine
def __call__(self, request, handler, next_mw):
request_wrapper = http_server.TornadoRequestWrapper(request=request)
span = http_server.before_request(request=request_wrapper)
@gen.coroutine
def next_middleware_with_span():
yield next_mw()
yield run_coroutine_with_span(span=span,
func=next_middleware_with_span)
span.finish()
def run_coroutine_with_span(span, func, *args, **kwargs):
"""Wrap the execution of a Tornado coroutine func in a tracing span.
This makes the span available through the get_current_span() function.
:param span: The tracing span to expose.
:param func: Co-routine to execute in the scope of tracing span.
:param args: Positional args to func, if any.
:param kwargs: Keyword args to func, if any.
"""
def mgr():
return RequestContextManager(span)
with tornado.stack_context.StackContext(mgr):
return func(*args, **kwargs)
Development
virtualenv env
source env/bin/activate
make bootstrap
make test