README.rst

MongoLog: Centralized logging made simple using MongoDB

Info:	MongoDB python logging handler. Python centralized logging made easy.
Author:	Andrei Savu
Maintainer:	Jorge Puente Sarrín

Setup

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
}

Usage

>>> import logging
>>> from mongolog.handlers import MongoHandler
>>>
>>> log = logging.getLogger('demo')
>>> log.setLevel(logging.DEBUG)
>>> log.addHandler(MongoHandler.to(db='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!