Primitive SNMP scanner, logger, grapher - the UNIX way

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Foreword

On my troubleshooter job, there are times when I need to collect a bunch of hand-picked SNMP OID's for a short while, to get my hands on some instant in time when things went "uh oh". A day or two worth of data, with maybe a 1-second periodicity, to squash a pesky bug, and then to move on.

There are a numer of advanced SNMP collection / storage / graphing software packages, which take days or weeks to learn and to configure, have a web front-end etc.
For the purpose at hand, they are typically bloated and unwieldy.
Don't get me started about time-series databases - a Ph.D. research topic in its own right.

At the other end of the spectrum, there is a simple clickety applet or two, for Win32, that can record a single OID, straight into a simple graph, but do not store the data on disk or anything.
These are overly simple for my needs.

It is not my point to record the whole MIB tree.
Nor is it my goal to record a large number of hosts, for indeterminate durations in time. No big data!
I just need a dozen OID's from a single host, for maybe a day or two. Make it a week if you will, but even two hours are often enough.

I don't need a round-robin database. I don't even need precisely clock-synchronized polling: imprecise polling period is okay, as long as I can get a semi-precise timestamp on every sample.
And, a complete log file is more useful than automatic round-robin post-aggregation / rotation. Also, the log should be in some simple format: human readable and machine-processible. Disk space costs peanuts. Thus, the choice is clear: the CSV format is obvious to anyone.

Dependencies

The "scanner" (collector) scripts are written in Perl 5, and require the "SNMP" module = Perl bindings for libsnmp, as provided by the net-snmp.org project. In Debian, the package is called "libsnmp-perl". (Note: do not confuse this with Perl/CPAN Net::SNMP = a different project.)

If your SNMP target hosts contain a proprietary SNMP MIB tree, you should get a corresponding MIB file. (For generic switches, routers and many other sorts of hardware, libsnmp comes with a set of generic / standard / RFC-based MIB files.)

Another requirement is "GNUplot" - the graphing tool. My "scanner-logger-grapher" package contains a few example GNUplot scripts or config files (those with .gnu extension) that take the time series data in .csv format and transform them into simple time-series graphs in PDF format.

There are some UNIX shell scripts (.sh) as wrappers around GNUplot and around the periodic scanner (to run it as a daemon). These are not strictly necessary.

The scripts were originally written in Linux, but might be easy to run in Windows too, if you can get Perl with libsnmp and GNUplot under Windows.

To browse MIB files, I tend to use the GUI-based snmpb or the text editor VIM with syntax highlighting on - it's got a profile for ASN.1 symbolic notation (i.e. MIB textual source code).

Scanners

The package contains two "scanner" scripts, written in Perl:
The first one called scan_once.pl takes a single sample (of all the OID's configured) and prints them, one OID per row, in textual representation (taken from the MIB).
The second script called scan_periodic.pl is a "periodic" scanner, taking a sample of all the OID's roughly once per second, and storing the output in a CSV file, one row per sample, including a full timestamp in the first column.

The scripts share two config files:
cfg_oids.pl contains a hostname or IP address of the target and SNMP community,
cfg_target_host.pl cotains a list of SNMP variables, one per row.
The config files are in Perl syntax: the common parameters (first file) initializes a "hash" (key=>value map) and the second one initializes an array (of references to anonymous arrays...) -- just stick to the syntax of brackets, commas and quotes and you'll be fine.

Graphing

The time-series output from the periodic "scanner", stored in a CSV file, can be piped directly into GNUplot. That, provided that you can write a GNUplot script (more like a config file).

While the output of GNUplot may seem simple and un-sexy, it can provide more detail and flexibility than your typical web-based SNMP über-collector monster.
You can customize the tick spacing, legend font size, legend descriptive strings, ranges (min/max), all of that per axis, you can have two scales vertically (one on the left and another one on the right) sharing the time base, you can have several "variables" (OID's, CSV columns) share a common vertical scale etc.
Each time series "variable" can have its line a different color, thickness and line style.
GNUplot is actually much more capable than this, it can plot several other types of charts - but as we are interested in time series, our chart should probably have time on the horizontal axis.

The PDF output format is nice for several reasons: it is a vector format, can be zoomed in pretty much indefinitely, retaining maximum detail from the input data - which can turn into a downside, if there are many thousand samples in the time series - the display in reader will be slow. PDF is also universally accepted, readers are available for most OS platforms.
If the size of your input data makes PDF impractical, try some bitmap/raster format for your output, such as the .PNG.

The fastest way to find out how to modify the example GNUplot scripts = what keywords to use and what the syntax is, is using Google to search for other people's examples. That combined with GNUplot's reference manual (and full-text keyword search in that).

Some example output

The following two graphs show the development in time of GPS "satellites in view and good" and GPS constellation quality indicators called "PDOP and TDOP", as reported by a Meinberg GPS, with a nearly optimal antenna placement.

The graphs were generated using the enclosed scripts.
Specifically for the DOP values it may be necessary to modify the yrange in the GNUplot script, depending on if you want to see the actual insane maxima (especially with suboptimal antenna placement), or you are more interested in the "sane region".
Similarly, you can limit the window in time that gets displayed in the plot, using the xrange keyword and a special format for date and time in the range definition.