Logging for Slackers

Posted in: Big Data, Technical Track

When I’m not working on Big Data infrastructure for clients, I develop a few internal web applications and side projects. It’s very satisfying to write a Django app in an afternoon and throw it on Heroku, but there comes a time when people actually start to use it. They find bugs, they complain about downtime, and suddenly your little side project needs some logging and monitoring infrastructure. To be clear, the right way to do this would be to subscribe to a SaaS logging platform, or to create some solution with ElasticSearch and Kibana, or just use Splunk. Today I was feeling lazy, and I wondered if there wasn’t an easier way.

Enter Slack

Slack is a chat platform my team already uses to communicate – we have channels for different purposes, and people subscribe to keep up to date about Data Science, our internal Hadoop cluster, or a bunch of other topics. I already get notifications on my desktop and my phone, and the history of messages is visible and searchable for everyone in a channel. This sounds like the ideal lazy log repository.

Slack offers a rich REST API where you can search, work with files, and communicate in channels. They also offer an awesome (for the lazy) Incoming WebHooks feature – this allows you to POST a JSON message with a secret token, which is posted to a pre-configured channel as a user you can configure in the web UI. The hardest part of setting up a new WebHook was choosing which emoji would best represent application errors – I chose a very sad smiley face, but the devil is also available.

The Kludge

Django already offers the AdminEmailHandler, which emails log messages to the admins listed in your project. I could have created a mailing list, added it to the admins list, and let people subscribe. They could then create a filter in their email to label the log messages. That sounds like a lot of work, and there wouldn’t be a history of the messages except in individual recipients’ inboxes.

Instead, I whipped up this log handler for Django which will post the message (and a stack trace, if possible) to your Slack endpoint:

from logging import Handler
import requests, json, traceback
class SlackLogHandler(Handler):
   def __init__(self, logging_url="", stack_trace=False):
      self.logging_url = logging_url
      self.stack_trace = stack_trace
   def emit(self, record):
      message = '%s' % (record.getMessage())
      if self.stack_trace:
         if record.exc_info:
            message += '\n'.join(traceback.format_exception(*record.exc_info))
            requests.post(self.logging_url, data=json.dumps({"text":message} ))

There you go: install the requests library, generate an Incoming WebHook URL at api.slack.com, stick the SlackLogHandler in your Django logging configuration, and your errors will be logged to the Slack channel of your choice. Stack traces are optional – I’ve also been using this to post hourly reports of active users, etc. to the channel under a difference username.

For reference, here’s a log configuration for the Django settings.py. Now go write some code, you slacker.

    'handlers': {
        'console': {
        'slack-error': {
    'loggers': {
        'django': {
            'level': 'INFO',
            'handlers': ['console', 'slack-error']

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3 Comments. Leave new

Alex Gorbachev
July 28, 2014 11:46 am

Thanks Alan for subscribing me to this logging channel on Slack – it’s been *very* vocal this morning!


Something I didn’t really touch on above, but I really like how they allow bulk-dismissing messages. It’s actually pretty perfect for log avalanches ;)


Hi, thanks for a great article! I’ve just used in one of my projects. I would change example a little to use formatter that was set for our handler:

> message = ‘%s’ % (self.formatter.format(record))

instead of

> message = ‘%s’ %(record.getMessage())


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