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MongoDB python logging handler. Python centralized logging made easy.
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mongolog
samples
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README.md
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test.py

README.md

MongoLog : Centralized Logging made simple using MongoDB

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 mongo shell:

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

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

    > db.log.stats()
    { "ns" : "mongolog.log", "count" : 0, "size" : 0, "storageSize" :
    100096, "numExtents" : 1, "nindexes" : 0, "lastExtentSize" : 100096,
    "paddingFactor" : 1, "flags" : 0, "totalIndexSize" : 0, "indexSizes" : {
    }, "capped" : 1, "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?

"Mongo is a high-performance, open source, schema-free document-oriented database."

It can eficiently store arbitrary JSON objects. You can read more at http://www.mongodb.org/

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: http://blog.mongodb.org

Have fun!

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