Usage

First of all, you need to install Kaneda package:

pip install kaneda

Then you need a backend in order to keep data in a persistent storage. The following example it shows how to send metrics with Elasticsearch as a backend:

from kaneda.backend import ElasticsearchBackend
from kaneda import Metrics

backend = ElasticsearchBackend(index_name='myindex', app_name='myapp', host='localhost',
                               port=9200, user='kaneda', password='kaneda')
metrics = Metrics(backend=backend)
metrics.gauge('answer_of_life', 42)

Features

• Builtin metrics functions and custom metric reports.

• Configurable reporting backends classes and asynchronous queue classes.

• Builtin Elasticsearch, MongoDB, InfluxDB and RethinkDB backends.

• Builtin Celery, RQ and ZMQ asynchronous queue classes.

• Django support.

Documentation

Visit the documentation for an in-depth look at Kaneda.