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Centralized logging made simple using MongoDB

Project description

MongoLog: Centralized logging made simple using MongoDB

MongoDB python logging handler. Python centralized logging made easy.


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

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!

.. _MongoDB website:
.. _MongoDB blog:

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