NMIS8 is a Network Management System which performs performance management. NMIS8 collects SNMP data from routers, switches, firewalls, servers, and many more types of IT devices. It stores the collected data in a performance database, which is an RRD file using RRDTool.
This article will describe how much data NMIS8 stores and how to modify NMIS8 to store more data.
How much data does NMIS8 Store?
RRDTool is a round robin database, which stores data in a binary file which is effectively circular, you define how many elements of data you want to keep and keep feeding data and it will keep adding elements up to that many of entries, when it is full, the oldest entries are overwritten. To keep summarised data you define a summarisation scheme, so the data is rolled up into the next level. In NMIS8 we define how much data RRDTool keeps by using the NMIS8 modelling system. The files for the NMIS8 models are stored in /path/to/nmis8/models and specifically the default database definitions are kept in /path/to/nmis8/models/Common-database.nmis
By default NMIS8 polls for performance data every 5 minutes and data in the following scheme:
| Data Summary | Days Kept For |
|---|---|
| raw data (5 minute polls) | 8 days |
| 30 minute averaged data | 32 days |
| 120 minute averaged data | 189 days |
| daily averaged data | 1890 days (5 years) |
This summarisation scheme was chosen to get a good balance of data stored and disk space used. The file sizes created using this scheme are as follows:
| RRD Type | File Size |
|---|---|
| Interface (ifInOctets and ifOutOcts) | 581112 bytes |
| Packet data | 1933120 bytes |
| HC Packet data (new) | 2319408 bytes |
| MIB-2 IP data | 1739976 bytes |
| NMIS Health data | 3091984 bytes |
What about statistical summarisation?
NMIS8 does not just keep the AVERAGES, it also keeps the MAXIMUM and MINIMUM for each data point, so in effect you have the range of data seen for a given summarisation, this is very important statistically, and many systems do not maintain this information. When doing analysis of performance data, it is important to use the averages (MEAN) as well as the MAXIMUM and MINIMUM (RANGE).
Can NMIS8 Store More Performance Data?
Yes, NMIS8 can be configured to store as much performance data as you have disk for. This is very easy to do when you first install an NMIS system. To store more data, first you need to determine how much more data you would like to store, then plug those numbers into the RRD Calculator Spreadsheet rrd_calc.xls, attached for your convenience, this will tell you what you need to change in the NMIS8 model file /path/to/nmis8/models/Common-database.nmis
The default Common-database.nmis file contains this:
'db' => {
'hbeat' => '900',
'poll' => '300',
'size' => {
'reachability' => {
'step_year' => '288',
'rows_month' => '2268',
'rows_year' => '1890',
'step_day' => '1',
'step_month' => '24',
'step_week' => '6',
'rows_day' => '2304',
'rows_week' => '1536'
},
'interface' => {
'step_year' => '288',
'rows_month' => '2268',
'rows_year' => '1890',
'step_day' => '1',
'step_month' => '24',
'step_week' => '6',
'rows_day' => '2304',
'rows_week' => '1536'
},
'default' => {
'step_year' => '288',
'rows_month' => '2268',
'rows_year' => '1890',
'step_day' => '1',
'step_month' => '24',
'step_week' => '6',
'rows_day' => '2304',
'rows_week' => '1536'
},
'metrics' => {
'step_year' => '288',
'rows_month' => '2268',
'rows_year' => '1890',
'step_day' => '1',
'step_month' => '24',
'step_week' => '6',
'rows_day' => '2304',
'rows_week' => '1536'
}
}
},
This will need to be changed to suit your new scheme, you might like to only keep more interface data, or to change all of them to keep more data.
How would I configure NMIS8 to keep 32 days of raw data?
To configure NMIS8 to keep 32 days of raw data (5 minute) and 96 days of 30 minutes of interface data you would make the following change to the interface section.
| Keep (days) | Summarise (minutes) | Model Entry | Default Value | New Value |
|---|---|---|---|---|
| 32 days | 5 minutes | rows_day | 2304 | 9216 |
| 96 days | 30 minutes | rows_week | 1536 | 4608 |
The entry for the Common-database.nmis model would look like this after the change:
'interface' => {
'step_year' => '288',
'rows_month' => '2268',
'rows_year' => '1890',
'step_day' => '1',
'step_month' => '24',
'step_week' => '6',
'rows_day' => '9216',
'rows_week' => '4608'
},
This change could be made to all the entries in the Common-database.nmis file if required.
NMIS8 will now create new RRD files with the new scheme defined in the model file. The resulting file sizes from the change above are:
| RRD Type | Old File Size | New File Size | % Increase |
|---|---|---|---|
| Interface (ifInOctets and ifOutOcts) | 581112 bytes | 1391364 bytes | 239% |
| Packet data | 1933120 bytes | 4264508 bytes | 220% |
Can I migrate existing NMIS8 RRD files to the new scheme
Yes, you can take existing NMIS8 RRD files and resize them using RRDTool Resize, the documentation for RRDTool resize is available on the RRDTool website http://oss.oetiker.ch/rrdtool/doc/rrdresize.en.html, in summary it would work like this.
If I wanted to change the amount of data being kept in an existing file, I would first determine the RRA Number for the entry to update, so I would run RRDTool Info on the file the output looks like this:
[root@nmisdev64 wanedge1]# /usr/local/rrdtool/bin/rrdtool info wanedge1-fastethernet0-1.rrd filename = "wanedge1-fastethernet0-1.rrd" rrd_version = "0003" step = 300 last_update = 1355967616 header_size = 5256 ds[ifInOctets].index = 0 ds[ifInOctets].type = "COUNTER" ds[ifInOctets].minimal_heartbeat = 900 ds[ifInOctets].min = 0.0000000000e+00 ds[ifInOctets].max = 1.0240000000e+06 ds[ifInOctets].last_ds = "9695172" ds[ifInOctets].value = 1.2818317168e+02 ds[ifInOctets].unknown_sec = 0 ds[ifOperStatus].index = 1 ds[ifOperStatus].type = "GAUGE" ds[ifOperStatus].minimal_heartbeat = 900 ds[ifOperStatus].min = 0.0000000000e+00 ds[ifOperStatus].max = 1.0000000000e+02 ds[ifOperStatus].last_ds = "100" ds[ifOperStatus].value = 1.6507604000e+03 ds[ifOperStatus].unknown_sec = 0 ds[ifOutOctets].index = 2 ds[ifOutOctets].type = "COUNTER" ds[ifOutOctets].minimal_heartbeat = 900 ds[ifOutOctets].min = 0.0000000000e+00 ds[ifOutOctets].max = 1.0240000000e+06 ds[ifOutOctets].last_ds = "17185853" ds[ifOutOctets].value = 2.2330066758e+02 ds[ifOutOctets].unknown_sec = 0 rra[0].cf = "AVERAGE" rra[0].rows = 2304 rra[0].cur_row = 537 rra[0].pdp_per_row = 1 rra[0].xff = 5.0000000000e-01 rra[0].cdp_prep[0].value = NaN rra[0].cdp_prep[0].unknown_datapoints = 0 rra[0].cdp_prep[1].value = NaN rra[0].cdp_prep[1].unknown_datapoints = 0 rra[0].cdp_prep[2].value = NaN rra[0].cdp_prep[2].unknown_datapoints = 0 rra[1].cf = "AVERAGE" rra[1].rows = 1536 rra[1].cur_row = 1325 rra[1].pdp_per_row = 6 rra[1].xff = 5.0000000000e-01 rra[1].cdp_prep[0].value = 1.5618120721e+01 rra[1].cdp_prep[0].unknown_datapoints = 0 rra[1].cdp_prep[1].value = 2.0000000000e+02 rra[1].cdp_prep[1].unknown_datapoints = 0 rra[1].cdp_prep[2].value = 2.7509214203e+01 rra[1].cdp_prep[2].unknown_datapoints = 0 rra[2].cf = "AVERAGE" rra[2].rows = 2268 rra[2].cur_row = 1977 rra[2].pdp_per_row = 24 rra[2].xff = 5.0000000000e-01 rra[2].cdp_prep[0].value = 1.5614431658e+02 rra[2].cdp_prep[0].unknown_datapoints = 0 rra[2].cdp_prep[1].value = 2.0000000000e+03 rra[2].cdp_prep[1].unknown_datapoints = 0 rra[2].cdp_prep[2].value = 2.7504466927e+02 rra[2].cdp_prep[2].unknown_datapoints = 0 rra[3].cf = "AVERAGE" rra[3].rows = 1890 rra[3].cur_row = 1585 rra[3].pdp_per_row = 288 rra[3].xff = 5.0000000000e-01 rra[3].cdp_prep[0].value = 1.5614431658e+02 rra[3].cdp_prep[0].unknown_datapoints = 0 rra[3].cdp_prep[1].value = 2.0000000000e+03 rra[3].cdp_prep[1].unknown_datapoints = 0 rra[3].cdp_prep[2].value = 2.7504466927e+02 rra[3].cdp_prep[2].unknown_datapoints = 0 rra[4].cf = "MAX" rra[4].rows = 2304 rra[4].cur_row = 611 rra[4].pdp_per_row = 1 rra[4].xff = 5.0000000000e-01 rra[4].cdp_prep[0].value = NaN rra[4].cdp_prep[0].unknown_datapoints = 0 rra[4].cdp_prep[1].value = NaN rra[4].cdp_prep[1].unknown_datapoints = 0 rra[4].cdp_prep[2].value = NaN rra[4].cdp_prep[2].unknown_datapoints = 0 rra[5].cf = "MAX" rra[5].rows = 1536 rra[5].cur_row = 1239 rra[5].pdp_per_row = 6 rra[5].xff = 5.0000000000e-01 rra[5].cdp_prep[0].value = 7.8502714737e+00 rra[5].cdp_prep[0].unknown_datapoints = 0 rra[5].cdp_prep[1].value = 1.0000000000e+02 rra[5].cdp_prep[1].unknown_datapoints = 0 rra[5].cdp_prep[2].value = 1.3968230743e+01 rra[5].cdp_prep[2].unknown_datapoints = 0 rra[6].cf = "MAX" rra[6].rows = 2268 rra[6].cur_row = 251 rra[6].pdp_per_row = 24 rra[6].xff = 5.0000000000e-01 rra[6].cdp_prep[0].value = 7.9934094489e+00 rra[6].cdp_prep[0].unknown_datapoints = 0 rra[6].cdp_prep[1].value = 1.0000000000e+02 rra[6].cdp_prep[1].unknown_datapoints = 0 rra[6].cdp_prep[2].value = 1.4389061029e+01 rra[6].cdp_prep[2].unknown_datapoints = 0 rra[7].cf = "MAX" rra[7].rows = 1890 rra[7].cur_row = 1714 rra[7].pdp_per_row = 288 rra[7].xff = 5.0000000000e-01 rra[7].cdp_prep[0].value = 7.9934094489e+00 rra[7].cdp_prep[0].unknown_datapoints = 0 rra[7].cdp_prep[1].value = 1.0000000000e+02 rra[7].cdp_prep[1].unknown_datapoints = 0 rra[7].cdp_prep[2].value = 1.4389061029e+01 rra[7].cdp_prep[2].unknown_datapoints = 0 rra[8].cf = "MIN" rra[8].rows = 2304 rra[8].cur_row = 955 rra[8].pdp_per_row = 1 rra[8].xff = 5.0000000000e-01 rra[8].cdp_prep[0].value = NaN rra[8].cdp_prep[0].unknown_datapoints = 0 rra[8].cdp_prep[1].value = NaN rra[8].cdp_prep[1].unknown_datapoints = 0 rra[8].cdp_prep[2].value = NaN rra[8].cdp_prep[2].unknown_datapoints = 0 rra[9].cf = "MIN" rra[9].rows = 1536 rra[9].cur_row = 927 rra[9].pdp_per_row = 6 rra[9].xff = 5.0000000000e-01 rra[9].cdp_prep[0].value = 7.7678492474e+00 rra[9].cdp_prep[0].unknown_datapoints = 0 rra[9].cdp_prep[1].value = 1.0000000000e+02 rra[9].cdp_prep[1].unknown_datapoints = 0 rra[9].cdp_prep[2].value = 1.3540983460e+01 rra[9].cdp_prep[2].unknown_datapoints = 0 rra[10].cf = "MIN" rra[10].rows = 2268 rra[10].cur_row = 720 rra[10].pdp_per_row = 24 rra[10].xff = 5.0000000000e-01 rra[10].cdp_prep[0].value = 7.6268952036e+00 rra[10].cdp_prep[0].unknown_datapoints = 0 rra[10].cdp_prep[1].value = 1.0000000000e+02 rra[10].cdp_prep[1].unknown_datapoints = 0 rra[10].cdp_prep[2].value = 1.2730238700e+01 rra[10].cdp_prep[2].unknown_datapoints = 0 rra[11].cf = "MIN" rra[11].rows = 1890 rra[11].cur_row = 1641 rra[11].pdp_per_row = 288 rra[11].xff = 5.0000000000e-01 rra[11].cdp_prep[0].value = 7.6268952036e+00 rra[11].cdp_prep[0].unknown_datapoints = 0 rra[11].cdp_prep[1].value = 1.0000000000e+02 rra[11].cdp_prep[1].unknown_datapoints = 0 rra[11].cdp_prep[2].value = 1.2730238700e+01 rra[11].cdp_prep[2].unknown_datapoints = 0
From all of this data I am interested in the following six lines:
rra[0].rows = 2304 rra[1].rows = 1536 rra[4].rows = 2304 rra[5].rows = 1536 rra[8].rows = 2304 rra[9].rows = 1536
These entries define the storage of the day and week summaries for RRA entries AVERAGE, MIN and MAX.
The RRDTool resize command can only resize one RRA at a time, and works on adding rows, so we need to add 6912 rows to the daily value (9216 - 2304) and add 3072 rows to the weekly value (4608 - 1536). The following are the commands required to resize this RRD.
cp wanedge1-fastethernet0-1.rrd wanedge1-fastethernet0-1.rrd.bak /usr/local/rrdtool/bin/rrdtool resize wanedge1-fastethernet0-1.rrd 0 GROW 6912 mv resize.rrd wanedge1-fastethernet0-1.rrd /usr/local/rrdtool/bin/rrdtool resize wanedge1-fastethernet0-1.rrd 4 GROW 6912 mv resize.rrd wanedge1-fastethernet0-1.rrd /usr/local/rrdtool/bin/rrdtool resize wanedge1-fastethernet0-1.rrd 8 GROW 6912 mv resize.rrd wanedge1-fastethernet0-1.rrd /usr/local/rrdtool/bin/rrdtool resize wanedge1-fastethernet0-1.rrd 1 GROW 3072 mv resize.rrd wanedge1-fastethernet0-1.rrd /usr/local/rrdtool/bin/rrdtool resize wanedge1-fastethernet0-1.rrd 5 GROW 3072 mv resize.rrd wanedge1-fastethernet0-1.rrd /usr/local/rrdtool/bin/rrdtool resize wanedge1-fastethernet0-1.rrd 9 GROW 3072 mv resize.rrd wanedge1-fastethernet0-1.rrd
This takes a second or two to complete. This process can be scripted easily enough, and there is a template for this in the NMIS8 distribution in /path/to/nmis8/admin/rrd_file_update.pl, the script would need to determine the RRA numbers by running rrdtool info first and then execute the above rrdtool resize commands for each RRD file.
Where are NMIS RRD Files Stored?
NMIS stores the RRD files in the folder /path/to/nmis8/database, then in various sub-directories depending on what is required. The script rrd_file_update.pl has the code to traverse a directory structure. NMIS can easily be configured to store RRD files in another location, this is controlled by the NMIS config item database_root which by default is set to '<nmis_data>/database'.
Conclusion
NMIS8 is a powerful network management system which can keep as much data as you have disk space to store, the defaults make sense for most organisations and provide a good balance between statistical granularity and disk space.