# The form of each line in this file should be as follows:
#
#   output_template (frequency) = method input_pattern
#
# This will capture any received metrics that match 'input_pattern'
# for calculating an aggregate metric. The calculation will occur
# every 'frequency' seconds and the 'method' can specify 'sum' or
# 'avg'. The name of the aggregate metric will be derived from
# 'output_template' filling in any captured fields from 'input_pattern'.
#
# For example, if you're metric naming scheme is:
#
#   <env>.applications.<app>.<server>.<metric>
#
# You could configure some aggregations like so:
#
#   <env>.applications.<app>.all.requests (60) = sum <env>.applications.<app>.*.requests
#   <env>.applications.<app>.all.latency (60) = avg <env>.applications.<app>.*.latency
#
# As an example, if the following metrics are received:
#
#   prod.applications.apache.www01.requests
#   prod.applications.apache.www01.requests
#
# They would all go into the same aggregation buffer and after 60 seconds the
# aggregate metric 'prod.applications.apache.all.requests' would be calculated
# by summing their values.
#
# Note that any time this file is modified, it will be re-read automatically.

# Aggregate all per-bucket memcached stats into a generit hit/miss stat
stats.<app>.cache.all.hit (10) = sum stats.<app>.cache.*.hit
stats.<app>.cache.all.miss (10) = sum stats.<app>.cache.*.miss

# Aggregate all per-domain active stats to overall active stats
stats.gauges.<app>.users.active.all.<bucket> (10) = sum stats.gauges.<app>.users.active.*.<bucket>