Logging saves output such as errors, warnings and event information to persistent storage for debugging purposes.

Why is logging important?

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 levels

Logging is often grouped into several categories:

  1. Information
  2. Debug
  3. Warning
  4. Error

Logging errors that occur while a web framework is running is crucial to understanding how your application is performing.

Logging aggregators

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 aggregation tools is they allow you to set up custom alerts and alarms so you can get notified when error rates breach a certain threshold.

Open source log aggregators

  • Sentry started as a Django-only exception handling service but now has separate logging clients to cover almost all major languages and frameworks. It still works really well for Python-powered web applications and is often used in conjunction with other monitoring tools. Raven is open source Python client for Sentry.

  • 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 programmatically 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 messaging format so it can be used with any language.

Hosted logging services

  • 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.

  • Splunk offers third party cloud and self hosted solutions for event aggregation. It excels at searching and data mining any text based data.

  • Papertrail is similar to both Loggly and Splunk and provides integration with S3 for long term storage.

  • Raygun logs errors and provides immediate notification when issues arise.

  • Scalyr provides log aggregation, dashboards, alerts and search in a user interface on top of standard logs.

  • There is a hosted version of Sentry in case you do not have the time to set up the open source project yourself.

Logging resources

Logging learning checklist

  1. Read how to integrate logging into your web application framework.

  2. Ensure errors and anomalous results are logged. While these logs can be stored in monitoring solutions, it's best to have your own log storage location to debug issues as they arise to complement other monitoring systems.

  3. Integrate logging for system events you may need to use for debugging purposes later. For example, you may want to know the return values on functions when they are above a certain threshold.

What's next after setting up logging for your app?

What tools exist for monitoring a deployed web app?

I want to learn more about app users via web analytics.

What can I do to mitigate security vulnerability in my web app?

Matt Makai 2012-2022