summaryrefslogtreecommitdiffstats
path: root/collectors/python.d.plugin/smartd_log/smartd_log.conf
blob: 3fab3f1c01a3ddbcc420238a4cbcf8aa73d2ebf9 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
# netdata python.d.plugin configuration for smartd log
#
# 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: 1

# 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

# retries sets the number of retries to be made in case of failures.
# If unset, the default for python.d.plugin is used.
# Attempts to restore the service are made once every update_every
# and only if the module has collected values in the past.
# retries: 60

# 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
#     retries: 60             # the JOB's number of restoration attempts
#     autodetection_retry: 0  # the JOB's re-check interval in seconds
#
# Additionally to the above, smartd_log also supports the following:
#
#    log_path: '/path/to/smartdlogs'    # path to smartd log files. Default is /var/log/smartd
#    raw_values: yes                    # enable/disable raw values charts. Enabled by default.
#    smart_attributes: '1 2 3 4 44'     # smart attributes charts. Default are ['1', '4', '5', '7', '9', '12', '193', '194', '197', '198', '200'].
#    exclude_disks: 'PATTERN1 PATTERN2' # space separated patterns. If the pattern is in the drive name, the module will not collect data for it.
#
# ----------------------------------------------------------------------
# Additional information
#  Plugin reads smartd log files (-A option).
#  You need to add (man smartd) to /etc/default/smartmontools '-i 600 -A /var/log/smartd/' to pass additional options to smartd on startup
#  Then restart smartd service and check /path/log/smartdlogs
#  ls /var/log/smartd/
#  CDC_WD10EZEX_00BN5A0-WD_WCC3F7FLVZS9.ata.csv  WDC_WD10EZEX_00BN5A0-WD_WCC3F7FLVZS9.ata.csv  ZDC_WD10EZEX_00BN5A0-WD_WCC3F7FLVZS9.ata.csv
#
# Smartd APPEND logs at every run. Its NOT RECOMMENDED to set '-i' option below 60 sec.
# STRONGLY RECOMMENDED to create smartd conf file for logrotate
#
# RAW vs NORMALIZED values
# "Normalized value", commonly referred to as just "value". This is a most universal measurement, on the scale from 0 (bad) to some maximum (good) value.
# Maximum values are typically 100, 200 or 253. Rule of thumb is: high values are good, low values are bad.
#
# "Raw value" - the value of the attribute as it is tracked by the device, before any normalization takes place.
# Some raw numbers provide valuable insight when properly interpreted. These cases will be discussed later on.
# Raw values are typically listed in hexadecimal numbers. The raw value has different structure for different vendors and is often not meaningful as a decimal number.
#
# ----------------------------------------------------------------------