Logging is a mechanism for monitoring web applications written with a web framework. Runtime exceptions that prevent code from running are important to log to investigate and fix the source of the problems. Informational and debugging logging also helps to understand how the application is performing even if code is working as intended.
Logging is often grouped into several categories:
Logging errors that occur while a web framework is running is crucial to understanding how your application is performing. Raven is a Python client for the Sentry exception logging and aggregation application. Raven provides the way to send exceptions to Sentry, which should be deployed on a separate server from your production infrastructure. Raven can also be used by Python scripts to send other log data to Sentry for aggregation. Sentry provides a clean web application interface for viewing the exceptions. Sentry can also be configured with a mail plugin to send emails when exceptions occur.
When you are running your application on several servers, it is helpful to have a monitoring tool called a "logging aggregator". You can configure your application to forward your system and application logs to one location that provides tools for viewing, searching, and monitoring logging events across your cluster.
Another advantage of log aggregatortion tools is they allow you to set up custom alerts and alarms so you can get notified when error rates breach a certain threshold.
loggly Loggly is a third party cloud based application that aggregates logs. They have instructions for every major language, including python. It includes email alerting on custom searches.
papertrail Paper trail is similar to both loggly and splunk and provides integration with S3 for long term storage.
splunk Splunk offers third party cloud and self hosted solutions for event aggregation. It excells at searching and data mining any text based data.
Raygun logs errors and provides immediate notification when issues arise.
Graylog2 provides a central server for log aggregation as well as a GUI for browsing and searching through log events. There are libraries for most major languages, including python. Saves data in Elasticache.
Logstash Similar to Graylog2, logstash offers features to programatically configure log data workflows.
Scribe A project written by Facebook to aggregate logs. It's designed to run on multiple servers and scale with the rest of your cluster. Uses the Thrift messagaing format so it can be used with any language.
This intro to logging presents the Python logging module and how to use it.
Logging as Storytelling is a multi-part series working the analogy that logs should read like a story so you can better understand what's taking place in your web application. Part 2 describes actions and part 3 talks about types.
Taking the pain out of Python logging shows a logging set up with uWSGI.
Django's 1.3 release brought unified logging into project configurations. This post shows how to set up logging in a project's settings.py file. Caktus Group also has a nice tutorial on central logging with graypy and Graylog2.
