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librato-python-web

librato-python-web is the Python agent for Librato's Django, Flask, CherryPy and Gunicorn turnkey integrations. It gathers essential health and performance metrics related to your web application and ships them to Librato, where you can view them in curated or custom metrics dashboards.

System requirements

  • Python 2.7.x (>=2.7.3) or Python 3.x
  • Django 1.8.6 or later, or Flask 0.10.1 or later, CherryPy 4.0.0 or later, Gunicorn 19.4.5 or later
  • Linux or OSX

Verified combinations

  • Python 2.7.3 or Python 3.5.1
  • Django 1.8.6 or Flask 0.10.1 or CherryPy 4.0.0 or Gunicorn 19.4.5
  • Ubuntu 14.04.3 LTS or OSX Yosemite 10.10.5

Overview

See the following KB articles for a general overview of how to create a turnkey Librato integration and configure the Python agent.

We highly recommend running your instrumented application under a virtual environment. E.g.

pip install virtualenv
virtualenv my_project_folder
source my_project_folder/bin/activate

Installing and configuring the agent

Install the Python agent using pip as shown below.

pip install librato-python-web

Use the provided librato-launch tool to configure the Python agent. Do this for every web application that you want to monitor. For example, the following command configures the Python agent to monitor a cherrypy application called 'cherrypy-prod-1'.

librato-config --app-id cherrypy-prod-1 --integration=cherrypy --user [email protected] --api-token XXXXXXXXXXXX

This will create a JSON configuration file in the current directory, named agent-conf.json, which looks as follows.

{
   "integration": "cherrypy",
   "metrics_hostname": "metrics-api.librato.com",
   "hostname": "localhost",
   "stop": false,
   "app_id": "cherrypy-prod-1",
   "no_aggregate_counters": false,
   "pidfile": "/var/run/solarwinds-python-statsd.pid",
   "flush_interval": 10000,
   "daemonize": false,
   "user": "[email protected]",
   "expire": 0,
   "api_token": “XXXXXXXXXXXX”,
   "debug": false,
   "pct": 95,
   "port": 8142,
   "restart": false
}

--config-path can be optionally used to specify an alternate file location. Default is './agent-conf.json'.

--integration optionally specifies the web framework to monitor (default is 'django').

--app-id (required) specifies a unique identifier for the application. The instrumentation prefixes the application id to the source for every measurement related to the app. This allows you to filter or aggregate metrics down to the application in turnkey or custom dashboards.

Run librato-config --help to see a full list of options.

Running your application

In order to instrument your application, prefix your runtime command with librato-launch. E.g.

librato-launch python manage.py runserver

Running with librato-launch installs a custom module loader, which instruments classes as they get imported by the application. The loader targets framework modules (e.g. django.*) to report web request latency, throughput and error metrics. It also instruments libraries such as mysql, postgres, elasticsearch, urllib2 and requests in order to decompose web request latency into 'data', 'external', 'wsgi' and 'app' buckets.

librato-launch consumes the configuration file (./agent-conf.json, by default). Use --config-path to override this default location.

librato-launch spawns a StatsD process to report metrics to Librato, which listens over UDP port 8142 by default. You can customize this port using the --port option to librato-config, or by manually editing the 'port' option in the configuration file.

The following environment variables, if defined, will override any configuration file settings.

  • LIBRATO_INTEGRATION - identifies the web framework for your app (django, flask or cherrypy)
  • LIBRATO_USER - the username associated with your Librato account
  • LIBRATO_TOKEN - a valid api token which has write access to Librato
  • LIBRATO_APP_ID - uniquely identifies your web application and can be used to filter your curated dashboards
  • LIBRATO_INSTRUMENTATION_PORT - UDP port that the bundled statsd instance will listen on
  • LIBRATO_INSTRUMENTATION_LIBS - a white-space separated list of libraries to instrument
  • LIBRATO_INSTRUMENTATION_LOG_LEVEL - a value from 10 to 50, which controls instrumentor logging verbosity (10 = debug)

Gunicorn monitoring

To monitor Gunicorn, add the --statsd-host option as shown below.

librato-launch gunicorn --statsd-host=127.0.0.1:8142 ... my_module:my_app

Instrumenting using code

You can't or don't want to auto-instrument your app, you can skip librato-launch and trigger instrumentation using the following code.

from librato_python_web.instrumentor import bootstrap

bootstrap.init(config-file-path)   # config-file-path can be omitted and defaults to './agent-conf.json'

Since modules are instrumented as they are loaded, it is important to call bootstrap.init() before the web framework (e.g. Django) and dependencies such as mysql or postgres are imported.

Since librato-launch is no longer in the picture, you'll need to run the StatsD server in order to report measurements to Librato. This can be done using the following command.

librato-statsd-server

or

librato-statsd-server --config-path <config-file-location>

Run librato-statsd-server --help for a complete list of options.

Configuring instrumented libraries

One of the web frameworks (django, flask or cherrypy) gets instrumented depending on the 'integration' configuration file option. By default, The following additional libraries are instrumented, if imported by the application.

Library Tested version(s) Comments
gunicorn 19.4.5
sqlite3
MySQL-python 1.2.5
psycopg2 2.6.1 Postgres
elasticsearch 2.2.0
pykafka 2.2.1
urllib2 Python 2.x only
requests 2.9.1
logging

The 'libraries' option can be used to exclude libraries (e.g. to zero in on a version compatibility issue). For example, appending the following line to the configuration file causes postgres, elasticsearch and urllib2 to be ignored.

    "libraries": ["gunicorn", "sqlite3", "MySQL-python", "requests", "logging"]

Debugging

You can turn on verbose logging using the 'instrumentor.log_level' configuration file option. 10 means debug, 20 means info, 30 means warning and so on. The default logging level is 30 (warning). Append the following line to the configuration file to turn on verbose debugging.

    "instrumentor.log_level": 10

This should be done during troubleshooting only to avoid a performance degradation.

Copyright

Copyright (c) 2015 Librato Inc. See LICENSE for details.

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