Redis backed metrics library - implements the most of the famous Metrics library.
RetricsGauge(BaseMetrics) - Single value gauge
RetricsCounter(BaseMetrics) - Simple counter with incr and decr methods
RetricsMeter(BaseMetrics) - Time series data, with 1, 5 and 15 minutes avg
RetricsHistogram(BaseMetrics) - Histogram with percentile, mean, median and std deviation methods
RetricsTimer(BaseMetrics) - Timer (wallclock)
The main class to loof after is RetricsFactory - Metrics factory
Basically we register an application and its metrics instances in the following order:
Application -> Metrics -> Instances of metrics
The important thing to monitor is that each metric will have an internal name based on the application + metric name + pid.
By looking at the way the name is composed it's easy to interchange data between processes.
from pymetrics import RetricsFactory
rf = RetricsFactory('application_name')
c = rf.new_counter('requests')
To list all instances for a given metric:
Unregister metrics instances is not mandatory as each new metric will not use the same internal name.
For more examples, check the tests/ directory
Use python -m unittest discover tests/unit to run all tests
Should use riemann optionally
Should integrate with dashify
Should be ported to ruby