GitHub - puentesarrin/mongodb-log: MongoDB Python logging handler, Centralized logging made simple using MongoDB. (original) (raw)

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 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 atMongoDB 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!