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Diffstat (limited to 'collectors/python.d.plugin/zscores/zscores.conf')
| -rw-r--r-- | collectors/python.d.plugin/zscores/zscores.conf | 108 |
1 files changed, 108 insertions, 0 deletions
diff --git a/collectors/python.d.plugin/zscores/zscores.conf b/collectors/python.d.plugin/zscores/zscores.conf new file mode 100644 index 000000000..fab18c787 --- /dev/null +++ b/collectors/python.d.plugin/zscores/zscores.conf @@ -0,0 +1,108 @@ +# netdata python.d.plugin configuration for example +# +# This file is in YaML format. Generally the format is: +# +# name: value +# +# There are 2 sections: +# - global variables +# - one or more JOBS +# +# JOBS allow you to collect values from multiple sources. +# Each source will have its own set of charts. +# +# JOB parameters have to be indented (using spaces only, example below). + +# ---------------------------------------------------------------------- +# Global Variables +# These variables set the defaults for all JOBs, however each JOB +# may define its own, overriding the defaults. + +# update_every sets the default data collection frequency. +# If unset, the python.d.plugin default is used. +update_every: 5 + +# priority controls the order of charts at the netdata dashboard. +# Lower numbers move the charts towards the top of the page. +# If unset, the default for python.d.plugin is used. +# priority: 60000 + +# penalty indicates whether to apply penalty to update_every in case of failures. +# Penalty will increase every 5 failed updates in a row. Maximum penalty is 10 minutes. +# penalty: yes + +# autodetection_retry sets the job re-check interval in seconds. +# The job is not deleted if check fails. +# Attempts to start the job are made once every autodetection_retry. +# This feature is disabled by default. +# autodetection_retry: 0 + +# ---------------------------------------------------------------------- +# JOBS (data collection sources) +# +# The default JOBS share the same *name*. JOBS with the same name +# are mutually exclusive. Only one of them will be allowed running at +# any time. This allows autodetection to try several alternatives and +# pick the one that works. +# +# Any number of jobs is supported. +# +# All python.d.plugin JOBS (for all its modules) support a set of +# predefined parameters. These are: +# +# job_name: +# name: myname # the JOB's name as it will appear at the +# # dashboard (by default is the job_name) +# # JOBs sharing a name are mutually exclusive +# update_every: 1 # the JOB's data collection frequency +# priority: 60000 # the JOB's order on the dashboard +# penalty: yes # the JOB's penalty +# autodetection_retry: 0 # the JOB's re-check interval in seconds +# +# Additionally to the above, example also supports the following: +# +# - none +# +# ---------------------------------------------------------------------- +# AUTO-DETECTION JOBS +# only one of them will run (they have the same name) + +local: + name: 'local' + + # what host to pull data from + host: '127.0.0.1:19999' + + # what charts to pull data for - A regex like 'system\..*|' or 'system\..*|apps.cpu|apps.mem' etc. + charts_regex: 'system\..*' + + # Charts to exclude, useful if you would like to exclude some specific charts. + # Note: should be a ',' separated string like 'chart.name,chart.name'. + charts_to_exclude: 'system.uptime' + + # length of time to base calculations off for mean and stddev + train_secs: 14400 # use last 4 hours to work out the mean and stddev for the zscore + + # offset preceeding latest data to ignore when calculating mean and stddev + offset_secs: 300 # ignore last 5 minutes of data when calculating the mean and stddev + + # recalculate the mean and stddev every n steps of the collector + train_every_n: 900 # recalculate mean and stddev every 15 minutes + + # smooth the z score by averaging it over last n values + z_smooth_n: 15 # take a rolling average of the last 15 zscore values to reduce sensitivity to temporary 'spikes' + + # cap absolute value of zscore (before smoothing) for better stability + z_clip: 10 # cap each zscore at 10 so as to avoid really large individual zscores swamping any rolling average + + # set z_abs: 'true' to make all zscores be absolute values only. + z_abs: 'true' + + # burn in period in which to initially calculate mean and stddev on every step + burn_in: 2 # on startup of the collector continually update the mean and stddev in case any gaps or inital calculations fail to return + + # mode can be to get a zscore 'per_dim' or 'per_chart' + mode: 'per_chart' # 'per_chart' means individual dimension level smoothed zscores will be aggregated to one zscore per chart per time step + + # per_chart_agg is how you aggregate from dimension to chart when mode='per_chart' + per_chart_agg: 'mean' # 'absmax' will take the max absolute value accross all dimensions but will maintain the sign. 'mean' will just average. |