One of the self evident truths about system administration is that you need to know what is going on with your systems. Monitoring - knowing that your systems are working as expected and, more importantly, knowing when they aren't - is the thing most people consider first when they realize that fact. Equally important however, is trending - knowing what your systems were doing in the past. Trending allows you to determine if the current state of your system is normal, or if something has changed that could signify a problem. Trending also allows you to predict when your current systems will become unable to handle what is expected of them. When the amount of traffic to your website is about to outgrow your systems, you can see this and add more capacity, either by adding servers or replacing them with something more powerful, before the capacity problems start to occur.

At OmniTI, we use a number of systems for trending, including Cacti and our very own Reconnoiter. Each system comes with a large number of monitors built in, allowing you to trend anything from network traffic, to system load to disk space. Sometimes however, you need metrics for which there is nothing currently available. This is where these systems' extensibility comes into play.

The following example shows a situation where we needed information that our current monitoring/trending systems were not able to provide, and we needed to extend them with a custom trending solution:

One of our clients had a website that had become very popular, and was suffering performance issues as a result. We suspected that at least part of the system was I/O bound, and so we wanted to gather metrics on the I/O performance of the system over time. The systems in question were running Solaris 10 with the data on ZFS. The normal iostat command, for which a number of monitors exist, does not give true values for reads and writes performed by ZFS. Iostat can only see read/write requests from filesystems. True I/O statistics can be obtained on the command line by running the zpool iostat command. This works in a similar way, producing output similar to the following:

# zpool iostat rpool 10 5
               capacity     operations    bandwidth
pool         used  avail   read  write   read  write
----------  -----  -----  -----  -----  -----  -----
rpool       16.6G  57.7G      1      0  43.5K  2.06K
rpool       16.6G  57.7G      0      0      0      0
rpool       16.6G  57.7G      0      0      0      0
rpool       16.6G  57.7G      0      0      0      0
rpool       16.6G  57.7G      0      0      0      0

The statement above that our monitoring systems were not able to provide the information that we needed isn't quite true. Elsewhere, we had a monitor that obtained zpool I/O statistics using a long running zpool iostat process, taking the values out and entering them into a database, with a custom script that fetched the values from the database and entered them into cacti. The system in question was a database server, so this method, while clunky, worked well enough for its purpose. For monitoring the web servers however, using the same method just wasn't practical and we needed something better. We needed something that didn't require running a long running process and running a database server on the machine just for trending information.

The obvious choice here was to use SNMP. Cacti (as well as pretty much every monitoring/trending package) has built-in support for obtaining data over SNMP, and net-snmp (the snmp agent in use on the server) has various ways of extending functionality to get custom metrics.

Having chosen SNMP, the next decision was how to get the data we needed and present it over SNMP. The seemingly obvious choice would be to run zpool iostat and parse the output as was done previously, presenting those values over SNMP. However, that either requires the long running zpool iostat process, or running it once for a few seconds at a time to get a snapshot of the I/O over that period, which will lead to inaccurate results (it won't tell us anything about the performance of the system during the time between checks). One of the things that Cacti (or rather rrdtool, which cacti makes use of) is very good at is taking raw data and generating meaningful statistics from it. If we could somehow get raw I/O values rather than already aggregated values such as 'n KB over the past m seconds read' and pass those to cacti, then cacti could do the work and we would get accurate values.

Enter open source. The source code to OpenSolaris is available, including the source code to the zpool command, which it possible to see how the zpool iostat command itself worked. Once you trace the various calls made by that function, it turns out that underneath, the zpool iostat command uses libzfs to fetch the exact raw values we are looking for. It was then a relatively simple matter to take that code and print out the raw values:

#include <stdio.h>
#include <sys/fs/zfs.h>
#include <libzfs.h>

 * Sample code to demonstrate printing of raw zpool io stats.
 * Compile with: cc -lzfs -lnvpair zpoolio.c -o zpoolio

int print_stats(zpool_handle_t *zhp, void *data) {
    uint_t c;
    boolean_t missing;

    nvlist_t *nv, *config;
    vdev_stat_t *vs;

    if (zpool_refresh_stats(zhp, &missing) != 0)
        return (1);

    config = zpool_get_config(zhp, NULL);

    if (nvlist_lookup_nvlist(config, 
        ZPOOL_CONFIG_VDEV_TREE, &nv) != 0) {
        return 2;

    if (nvlist_lookup_uint64_array(nv, 
        ZPOOL_CONFIG_STATS, (uint64_t **)&vs, &c) != 0) {
        return 3;

        "pool:%s read_ops:%llu write_ops:%llu " \
            "read_bps:%llu write_bps:%llu\n",
    return 0;

int main() {
    libzfs_handle_t *g_zfs;
    g_zfs = libzfs_init();
    return(zpool_iter(g_zfs, print_stats, NULL));

Once this was done, the next step was to get the values exported over SNMP so that cacti could view them. Net-SNMP has a pass directive that allows you to delegate an OID to an external program, and have that program print out the results it needs. These values are then exported over SNMP, available for any of the above monitoring tools to make use of.

In Cacti, it was then just a matter of creating an appropriate SNMP Data Query, adding some Graph Templates, and wait for the pretty pictures to come flowing in.

This example shows how you might approach developing code to obtain custom metrics, and shows the benefits of having the source code available so that you can learn from tools that do most, but not all of what you are trying to achieve. Sometimes, what you need just isn't available and you just have to build a solution from the available pieces.