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Centralized logging made simple using MongoDB

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Travis CI status Latest PyPI version Number of PyPI downloads
Info:MongoDB python logging handler. Python centralized logging made easy.
Author:Andrei Savu
Maintainer:Jorge Puente Sarrín


Before using this handler for logging you will need to create a capped collection on the MongoDB server.

You can do this using the following commands in the MongoDB shell:

> use mongolog
> db.createCollection('log', {capped:true, size:100000})

… and you are ready. Running stats() function on log collection should show something like this:

> db.log.stats()
        "ns" : "mongolog.log",
        "count" : 0,
        "size" : 0,
        "storageSize" : 102400,
        "numExtents" : 1,
        "nindexes" : 1,
        "lastExtentSize" : 102400,
        "paddingFactor" : 1,
        "systemFlags" : 1,
        "userFlags" : 0,
        "totalIndexSize" : 8176,
        "indexSizes" : {
                "_id_" : 8176
        "capped" : true,
        "max" : 2147483647,
        "ok" : 1


>>> import logging
>>> from mongolog.handlers import MongoHandler
>>> log = logging.getLogger('demo')
>>> log.setLevel(logging.DEBUG)
>>> log.addHandler('mongolog', collection='log'))
>>> log.debug('Some message')

Check the samples folder for more details.

Why centralized logging?

  • Easy troubleshouting:
    • Having the answers to why? quickly and accurately.
    • For troubleshouting while the system is down.
    • Removed risk of loss of log information.
  • Resource tracking.
  • Security.

What is MongoDB?

“MongoDB is a high-performance, open source, schema-free document-oriented database.”

It can eficiently store arbitrary JSON objects. You can read more at MongoDB website.

Why MongoDB is great for logging?

  • MongoDB inserts can be done asynchronously.
  • Old log data automatically LRU’s out thanks to capped collections.
  • It’s fast enough for the problem.
  • Document-oriented / JSON is a great format for log information.

Read more about this subject on the MongoDB blog.

Have fun!

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