# Dstat: pluggable real-time monitoring

Dag Wieers
`<dag@wieers.com>`
$Id$

This Dstat paper was originally written for LinuxConf Europe that was held together with the Linux Kernel summit at the University in Cambridge, UK in August 2007.

## Introduction

Many tools exist to monitor hardware resources and software behaviour, but few tools exist that allow you to easily monitor any conceivable counter.

Dstat was designed with the idea that it should be simple to plug in a piece of code that extracts one or more counters, and make it visible in a way that visually pleases the eye and helps you extract information in real-time.

By being able to select those counters that you want (and likely those counters that matter to you in the job you’re doing) you make it easier to correlate raw numbers and see a pattern that may otherwise not be visible.

## A case for Dstat

A few years ago I was involved in a project that was testing a storage cluster with a SAN back-end using GPFS and Samba for a broadcasting company. The performance tests that were scheduled together with the customer took a few weeks to measure the different behaviour under different stresses.

During these tests there was a need to see how each of the components behaved and to find problematic behaviour during testing. Also, because it involved 5 GPFS nodes, we needed to make sure that the load was spread evenly during the test. If everything went well repeatedly, the results were validated and the next batch of tests could be prepared and run.

We started off using different tools at first, but the more counters we were trying to capture the harder it was to post-process the information we had collected. What’s more, we often saw only after performing the tests that the data was not representative because the numbers didn’t add up. Sometimes it was caused by the massive setup of clients that were autonomously stressing the cluster. On other occasions we noticed that the network was the culprit. All in all, we lost time because we could only validate the results by relating numbers after the tests were complete and not during the tests.

Complicating the matter was the fact that 5 different nodes were involved and using the normal command line tools like vmstat, iostat or ifstat (which only showed us a small part of what was happening) was problematic as each needed a different terminal. Besides, not all information was interesting.

Eventually Dstat was born, to make a dull task more enjoyable.

After the project was finished I was able to correlate system resources with network throughput, TCP information, Samba sessions, GPFS throughput, accumulated block device throughput, HBA throughput, all within a single interval on one screen for the complete cluster.

## Dstat characteristics

There are many ideas incorporated into Dstat by design, and this section serves to list all of them. Not all of them may appeal to the task you’re doing, but the combination may make it an appealing proposition nevertheless.

### History of counters

An important characteristic in line-based tools like vmstat, iostat or ifstat is the fact that you can compare historical collected data with new data. This allows you to have a good feeling of how something is evolving.

Compare this to tools like top or nmon, where data is often being refreshed and you loose historical information (but in return can provide you with a lot more information at the same time).

### Adding unit indication

It was very important that when numbers were compared, they were in the same unit, and not eg. a different power exponent. The human mind sometimes works in mysterious ways and more so when working with numbers for hours and hours. Adding the unit is something very convenient and may reduce the human error factor.

Additionally, indicating the unit also makes sure that the columns have a fixed width. Often when using vmstat or other tools, the columns tend to shift depending on the width of the counter. This makes it very inconvenient to find counters in the shifted output.

### Colour highlighting units

After I added colours to help improve indicating units, I noticed that the colours also helped to show patterns. This of course is very limited, nevertheless it instantly shows when numbers are flat or changes are taking place.

Important | The colours are arbitrarily chosen. Do not make the mistake to assume that green means good and red means bad. There is no real meaning to the colour itself, however a change of colour does mean that a value has gone over some pre-defined limit.

### Intermediate updates

During tests, when you choose to see average values over a given time, it can be useful to see how the averages evolve. Dstat, by default, displays intermediate updates. This means that if you select to see 10 second averages, after each second you see the accumulated average over the timespan. This means that after 4 seconds with intermediate updates, you see an average taken over the 4 second timeframe.

Note | This means that the closer you get to the given timeframe (eg. 10 seconds) the more likely that it nears its final average over that period.

### Adding custom counters

Dstat was specifically designed to enable anyone to add their own counters in a matter of minutes. The plugin-based system takes care of displaying, colouring and adding units to the counters. As a plugin-writer, you only have to focus on extracting the counters from the kernel (procfs or sysfs), logfiles or daemons.

### Selecting plugins and counters

Being able to add custom counters is important, but selecting those counters that you really need is even more important if you want to correlate counters and see patterns. Less is more.

Note | In fact, Dstat currently does not allow you to select just counters, it only allows you to select plugins. However, since you can modify or fork a plugin, you still have the ability to select just those counters you prefer.

### Exporting to CSV

Having information on screen is one thing, you most likely need some hard evidence later to make your case. (Why else do all the work?)

Dstat allows to write out all counters in the greatest detail possible to CSV. By default it also adds the command-line used for generating the output, as well as a date and time stamp. Since Dstat in the first place is meant for human-readable real-time statistics, it will by default also display the counters to screen (unless you /dev/null it).

Tip | Dstat appends to the output file so that you can add tests-results of different tests to a single file. However, make sure that you tag each test properly (eg. by using distinct filenames for each different test).

### Time-plugin included

It may seem a small thing, but having exact time (and date) information for your counters allows for a completely different usage as well. By adding simple date and time information, Dstat can be used as a background process in a screen to monitor the behaviour of your system during the night.

This proves to be very valuable for example, to find offending processes during nightly tasks or to pinpoint their behaviour to certain events that you cannot monitor during working hours.

It is also important when you have multiple Dstats running (eg. for nodes in a cluster) to correlate counters between the outputs.

### Terminal capabilities

Dstat also takes into account the width and height of your terminal window and modifies output to fit into your terminal. This, of course, has no effect on what ends up in the CSV output.

Another (debatable) useful feature is that Dstat will modify the terminal title to indicate on what system it was run and what options were used. Especially when monitoring nodes in a cluster, this can be useful, but even in Gnome finding your Dstat window is handy.

Warning | Some people however are annoyed by the fact that their distribution does not reset the terminal title and Dstat therefor messes it up. There is no way for Dstat to fix this.

## Plugins and counters

When we talk about plugins, we make a distinction between those plugins that are included within the Dstat tool itself, and those that ship with it externally. In essence there is no real difference, as the internal plugins could easily have been created as an external plugin. The basic difference is that the internal plugins have no dependencies except on procfs.

Having the basic plugins as part of Dstat, makes sure that Dstat can be moved as a self-contained file to other systems.

### Internal plugins

The plugins that have been selected to be part of the Dstat tool itself, and therefor have no dependencies other than procfs, are:

- aio: asynchronous I/O counters

- cpu, cpu24: CPU counters (`-c` and `-C`)

- disk, disk24, disk24old: disk counters (`-d` and `-D`)

- epoch: seconds since Epoch (`-T`)

- fs: file system counters

- int, int24: interrupts per IRQ (`-i` and `-I`)

- io: I/O requests completed (`-r`)

- ipc: IPC counters

- load: load counters (`-l`)

- lock: locking counters

- mem: memory usage (`-m`)

- net: network usage (`-n` and `-N`)

- page, page24: paging counters (`-g`)

- proc: process counters (`-p`)

- raw: raw socket counters

- swap, swapold: swap usage (`-s` and `-S`)

- socket: socket counters

- sys: system (kernel) countersA (`-y`)

- tcp: TCP socket counters

- time: date and time (`-t`)

- udp: UDP socket counters

- unix: unix socket counters

- vm: virtual memory counters

For backward compatibility with older kernels there is a cascading system that selects the most appropriate internal plugin for your kernel. (eg. the `dstat_disk` plugin falls back to `dstat_disk24` and `dstat_disk24old`) At this moment there is no such system for external plugins.

### External plugins

This basic functionality is easily extended by writing your own plugins (subclasses of the python Dstat class) which are then inserted at runtime into Dstat. A set of external modules exist for:

- battery: battery usage

- battery-remain: remaining battery time

- cpufreq: CPU frequency

- dbus: DBUS connections

- disk-tps: disk transactions counters

- disk-util: disk utilization percentage

- dstat: dstat cputime consumption and latency

- dstat-cpu: dstat advanced cpu usage

- dstat-ctxt: dstat context switches

- dstat-mem: dstat advanced memory usage

- fan: Fan speed

- freespace: free space on filesystems

- gpfs: GPFS IO counters

- gpfs-ops: GPFS operations counters

- helloworld: Hello world dispenser

- innodb-buffer: innodb buffer counters

- innodb-io: innodb I/O counters

- innodb-ops: innodb operations counters

- lustre: lustre throughput counters

- memcache-hits: Memcache hit counters

- mysql5-cmds: MySQL communication counters

- mysql5-conn: MySQL connection counters

- mysql5-io: MySQL I/O counters

- mysql5-keys: MySQL keys counters

- mysql-io: MySQL I/O counters

- mysql-ops: MySQL operations counters

- net-packets: number of packets received and transmitted

- nfs3: NFS3 client counters

- nfs3-ops: NFS3 client operations counters

- nfsd3: NFS3 server counters

- nfsd3-ops: NFS3 server operations counters

- ntp: NTP time counters

- postfix: postfix queue counters

- power: Power usage counters

- proc-count: total number of processes

- qmail: qmail queue sizes

- rpc: RPC client counters

- rpcd: RPC server counters

- sendmail: sendmail queue counters

- snooze: Dstat time delay counters

- squid: squid usage statistics

- thermal: Thermal counters

- top-bio: most expensive block I/O process

- top-bio-adv: most expensive block I/O process (advanced)

- top-cpu: most expensive cpu process

- top-cpu-adv: most expensive CPU process (advanced)

- top-cputime: process using the most CPU time

- top-cputime-avg: process having the highest average CPU time

- top-int: most frequent interrupt

- top-io: most expensive I/O process

- top-io-adv: most expensive I/O process (advanced)

- top-latency: process with the highest total latency

- top-latency-avg: process with the highest average latency

- top-mem: most expensive memory process

- top-oom: process first shot by OOM killer

- utmp: utmp counters

- vm-memctl: VMware guest memory counters

- vmk-hba: VMware kernel HBA counters

- vmk-int: VMware kernel interrupt counters

- vmk-nic: VMware kernel NIC counters

- vz-cpu: OpenVZ CPU counters

- vz-io: I/O usage per OpenVZ guest

- vz-ubc: OpenVZ user beancounters

- wifi: WIFI quality information

### Most-wanted plugins

Hoping someone interested reads this document, I added a few plugins that would be “very nice” to have but are currently lacking:

- slab: needs a VM expert to make sense out of the vast amount of data

- xorg: need information on how to get X resources, would be nice to see evolution of X resources over time

- samba: lacking information to get counters from Samba without forking smbstatus every second

- snmp: could be useful to relate counters from different systems in a single Dstat

- topx: display the most expensive X application(s)

- systemtap: connecting Dstat to systemtap counters

Creative souls with other ideas are welcome as well !

## Using Dstat

Central to the Dstat command line interface is the selection of plugins. The selection and order of options influence the Dstat output directly.

### Enabling plugins

The internal plugins have short and/or long options within Dstat, eg. `-c` or `--cpu` will enable the cpu counters.

The external plugins are enable by a long option including their name, eg. `--top-cpu`

The following examples will enable the time, cpu and disk plugins, and are equal.

    dstat -tcd
    dstat --time --cpu --disk

### Total or individual counters

Some of the plugins can show both total values or individual values and therefor have an extra option to influence this decision.

    dstat -d -D sda,sdb
    dstat -n -N eth0,eth1
    dstat -c -C total,0,1

You can show both the individual values and total values as follows:

    [dag@horsea ~]$ dstat -d -D total,hda,hdc
    -dsk/total----dsk/hda-----dsk/hdc--
     read  writ: read  writ: read  writ
    1384k 1502k: 114k 1332k:  81k  359B
       0    44k:   0    44k:   0     0
       0     0 :   0     0 :   0     0

The special `-f` or `--full` option allows to select individual counters by default, and can be overruled by `-C`, `-D`, `-I`, `-N` or `-S`.

### Influencing output

Dstat has a few more options to influence its output. With the `--nocolor` one can disable colours. The `--noheaders` option disables repeating headers. The `--noupdate` option disables intermediate updates. The `--output` option is used for writing out to a CSV file.

### Plugin search path

Dstat looks in the following places for plugins. This allows a user without root privileges to use some extra plugins.

- ~/.dstat/

- <binarypath>/plugins/

- /usr/share/dstat/

- /usr/local/share/dstat/

The option `--list` shows the available plugins and their location in the order that the plugin search path is used.

Note | Plugins are named `dstat_<name>.py`.

## Use-cases

Below are some use-cases to demonstrate the usage of Dstat.

Warning | The following examples do not look as nice as they do on screen because this document is not printed in colour (and I did not prepare it in colour :-)).

### Simple system check

Let’s say you quickly want to see if the system is doing alright. In the past this probably was a `vmstat 1`, as of now you would do:

    dstat -taf

Sample output

    [dag@rhun dag]$ dstat -taf
    -----time----- -------cpu0-usage------ --dsk/sda-----dsk/sr0-- --net/eth1- ---paging-- ---system--
      date/time   |usr sys idl wai hiq siq| read  writ: read  writ| recv  send|  in   out | int   csw
    02-08 02:42:48| 10   2  85   2   0   0|  22k   23k: 1.8B    0 |   0     0 |2588B 2952B| 558   580
    02-08 02:42:49|  4   3  93   0   0   0|   0     0 :   0     0 |   0     0 |   0     0 |1116   962
    02-08 02:42:50|  5   2  90   0   2   1|   0    28k:   0     0 |   0     0 |   0     0 |1380  1136
    02-08 02:42:51| 11   6  82   0   1   0|   0     0 :   0     0 |   0     0 |   0     0 |1277  1340
    02-08 02:42:52|  3   3  93   0   1   0|   0    84k:   0     0 |   0     0 |   0     0 |1311  1034

Note | The `-t` here is completely optional and generally wastes space. But often you are not monitoring for 10 seconds but rather measure in minutes or hours. Having a general idea on what timescale counters have been averaged is nevertheless interesting.

### What is this system doing now ?

I often run both the `dstat_top_cpu` and `dstat_top_mem` programs on a system, just to see what a system is doing. Having a quick look at what application is using the most CPU over a few minutes and to see what the general usage of memory is of the top application gives away a lot about a system.

Sample output

    [dag@horsea dag]$ dstat -c --top-cpu -dng --top-mem
    ----total-cpu-usage---- -most-expensive- -dsk/total- -net/total- ---paging-- -most-expensive-
    usr sys idl wai hiq siq|  cpu process   | read  writ| recv  send|  in   out | memory process
      9   2  80   9   0   0|kswapd         0| 123k  164k|   0     0 |9196B   18k|rsync        74M
      2   3  95   0   0   0|sendmail       1|   0   168k|2584B   39k|   0     0 |rsync        74M
     18   3  79   0   0   0|httpd         17|   0    88k|5759B  118k|   0     0 |rsync        74M
      3   2  94   1   0   0|sendmail       1|4096B    0 |2291B 4190B|   0     0 |rsync        74M
      2   3  95   0   0   0|httpd          1|   0     0 |2871B 3201B|   0     0 |rsync        74M
     10   7  83   0   0   0|httpd         13|   0     0 |2216B   10k|   0     0 |rsync        74M
      2   2  96   0   0   0|                |   0    52k| 724B 2674B|   0     0 |rsync        74M

### What process is using all my CPU, memory or I/O at 4:20 AM ?

Imagine the monitoring team notices strange peaks, a system engineer got a worthless message, the system was swapping extensively, a process got killed.

Something indicates the system is doing something unexpected but what is causing it and why ? As of now you can do:

    screen dstat -tcy --top-cpu 120
    screen dstat -tmgs --top-mem 120
    screen dstat -tdi --top-io 120

to see what process is using the most CPU, the most memory and the most I/O resources.

And hopefully one day we can do:

    dstat -tn --top-net 120
    dstat -tn --top-x 120

Leave it running during the night and in the morning you can see the light.

### How much ticks per second on my kernel ?

In some cases it can be useful to see how many ticks (timer interrupts) your kernel is producing. With older kernels this is a fixed number (usually 100, 250 or 1000) but on newer kernels the number can be dynamic.

Also on VMware virtual machines, the number of ticks can cause clock issues, so in that case if you want to see what is happening, you can simply do:

    dstat -ti -I0 --snooze --debug

Dstat nowadays can also detect lost ticks (when the number of ticks do not match the time progress. This is useful to correlate VM issues with other problems.

### What device is slowing down my system ?

A nice feature of Dstat is that it can show how many interrupts each of your devices is generating. The cpu stats already show this in percentage as hard interrupt and soft interrupt, and the sys stats shows the total number of interrupts, but the int stats go into detail. And you can specify exactly what IRQs you want to watch.

Many devices generate interrupts, especially when used at maximum capacity. Sometimes too many interrupts can slow down a system. If you want to correlate bad performance with hardware interrupts, you can run a command like:

    dstat -tyif
    dstat -tyi -I 12,58,iwlagn -f 5

Much like `watch -n1 -d cat /proc/interrupts` on steroids.

    dstat -t -y -i -f

which then results in:

Sample output

    [dag@rhun ~]$ dstat -t -y -i -f 5
    -----time----- ---system-- -------------------interrupts------------------
      date/time   | int   csw |  1     9     12    14    15    58   177   185
    13-08 21:52:53| 740   923 |   1     0    18     5     1    17     4   131
    13-08 21:52:58|1491  2085 |   0     4   351     1     2    37     0    97
    13-08 21:53:03|1464  1981 |   0     0   332     1     3    31     0    96
    13-08 21:53:08|1343  1977 |   0     0   215     1     2    32     0    93
    13-08 21:53:13|1145  1918 |   0     0    12     0     3    33     0    95

When having the following hardware:

    [dag@rhun ~]$ cat /proc/interrupts
               CPU0
      0:  143766685    IO-APIC-edge  timer
      1:     374043    IO-APIC-edge  i8042
      9:     102564   IO-APIC-level  acpi
     12:    4481057    IO-APIC-edge  i8042
     14:    1192508    IO-APIC-edge  libata
     15:     358891    IO-APIC-edge  libata
     58:    4391819   IO-APIC-level  ipw2200
    177:     993740   IO-APIC-level  Intel ICH6
    185:   33542364   IO-APIC-level  yenta, uhci_hcd:usb1, eth0, i915@pci:0000:00:02.0
    NMI:          0
    LOC:  143766578
    ERR:          0
    MIS:          0

Or select specific interrupts:

    dstat -t -y -i -I 12,58,185 -f 5

Another possibility is to use the `--top-int` plugin, showing you the most frequent plugin on your system:

    [dag@rhun ~]# dstat -t --top-int
    ----system---- ---most-frequent----
         time     |     interrupt
    11-06 08:34:53|ahci              5
    11-06 08:34:54|i8042            69
    11-06 08:34:55|i8042            45
    11-06 08:34:56|ehci/usb2        12
    11-06 08:34:57|

### How does my WIFI signal evolve when I move my laptop or AP through the house ?

Something I was looking into when trying to find the optimal location for the WIFI access point. However I must say that another tool I wrote Dwscan is currently more sophisticated.

    dstat -t --wifi

### Is my SWRAID performing as it claims ?

You can monitor I/O throughput for any block device. By default dstat limits itself to real block devices to prevent having the same I/O to be counted more than once, but if you want to monitor a SWRAID device, or a multipath device, you can simply do that by doing:

    dstat -td -D md0,md1,sda,sdb,hda

## Writing your own Dstat plugin

Dstat is completely written in python and this makes it extremely convenient to write your own plugins. The many plugins that come with Dstat are an excellent source of information if you want to write your own.

### Introducing the hello world plugin

The following plugin does nothing more than write "Hello world!" to its output.

The dstat_helloworld plugin in its full glory.

    class dstat_helloworld(dstat):
        ``"
        Example "Hello world!" output plugin for aspiring Dstat developers.
        ``"
        def __init__(self):
            self.name = 'plugin title'          <1>
            self.nick = ('counter',)            <2>
            self.vars = ('text',)               <3>
            self.type = 's'                     <4>
            self.width = 12                     <5>
            self.scale = 0                      <6>

        def extract(self):
            self.val['text'] = 'Hello world!'   <7>

In this example, there are several components:

1. `self.name` contains the plugin’s visible title.

2. `self.nick` is a list of the counter names

3. `self.vars` is a list of the variable names for each counter

4. `self.type` defines the counter type: string, percentage, integer, float

5. `self.width` defines the column width

6. `self.scale` influences the coloring and unit type

7. `self.val` contains the counter values that are being displayed

### Parsing counters

The following example shows how information is collected and counters are processed. It also includes a `check()` method to properly bail out when the system fails to meet some plugin criteria.

The dstat_postfix plugin

    class dstat_postfix(dstat):
        def __init__(self):
            self.name = 'postfix'
            self.nick = ('inco', 'actv', 'dfrd', 'bnce', 'defr')
            self.vars = ('incoming', 'active', 'deferred', 'bounce', 'defer')
            self.type = 'd'                                                    <1>
            self.width = 4
            self.scale = 100

        def check(self):                                                       <2>
            if not os.access('/var/spool/postfix/active', os.R_OK):
                raise Exception, 'Cannot access postfix queues'

        def extract(self):
            for item in self.vars:                                             <3>
                self.val[item] = len(glob.glob('/var/spool/postfix/'+item+'/*/*')

This example shows the following items:

1. type, width and scale specify decimal, column width a,d coloring based on multiplication of 100

2. The `check()` method tests conditions and bails out of they are not met

3. To make processing easier we have opted to use as value names (`self.vars`) the name of the postfix queues and store counts in `self.val`

### Opening files

Dstat provides its own `dopen()` function to plugins. Using `dopen()` instead of `open()` plugins do not need to reopen files to update their counters. But this is only useful when plugins open a few files. For eg. opening /proc/pid files the number of open files would only be increasing as the number of processes increases.

### Piping to an application

Dstat provides its own `dpopen()` function to plugins. This function allows the plugin to open stdin, stdout and stderr pipes for 2-way communication with processes. To see this in action, take a look at the `dstat_gpfs` plugins or the `dstat_mysql` plugins.

Piping to an application is more expensive than getting kernel counters from /proc, but it beats having to run a program and capturing the output.

## Known issues

There are some known issues that are important to understand when using Dstat.

### Writing Dstat and plugins in C

It makes sense to reimplement Dstat or some of its plugins in C and still allow the writing of Python (or even Perl) plugins. Tests have shown that for example processing /proc/pid in C makes the plugin 3 times faster. And this did not take into account the processing of the results and displaying the output.

So rewriting in C makes a lot of sense, but it is also much more complicated.

### Python 1.5

There used to be a Python 1.5 version of Dstat, but with RHEL2 going out of support in 2009 I decided to no longer spend the extra effort to sync and test the Dstat15 version.

Leaving Python 1.5 behind means that plugins do not longer have to be compatible with Python 1.5 either. It is no coincedence that after this event a major overhaul was made to the plugin interface.

### Counter rollovers

Unfortunately Dstat is susceptible for counters that “rollover”. This means that a counter gets bigger than its maximum value the data-structure is capable of storing. As a result the counter is reset.

For some architectures and some counters, Linux implements 32bit values, this means that such counter can go up to 2^32 (= 4294967296B = 4G) values.

For example the network counters are calculated in absolute bytes. Every 4GB that is being transferred over the network will cause a counter reset. For example on a bonded 2x10Gbps interfaces that is using its theoretical transfer limit, this would happen every 1.6 seconds.

Since /proc is updated every second, this would be impossible for Dstat to catch. Currently if Dstat encounters a negative difference for an interval it assumes a single rollover has happened and compensates for it. If that assumption is wrong, the user is working with wrong counters nonetheless.

If you suspect that the behaviour of your system is susceptible of counter rollovers, make sure you take this into account when using Dstat (or any other tool that uses these counters for that matter).

Tip | Shipped with the Dstat documentation there is a document (counter-rollovers.txt) that goes deeper into counter rollovers. If this affects you, read that document and contact me for possible implementation changes to improve handling them.

## Dstat performance

As mentioned several times now, Dstat is written in python. There are various reasons that Python was chosen and the most important reason is that we target system engineers and users, so we need to simplify writing plugins, processing counters and lowers the bar for people to contribute changes.

The downside of choosing a scripting language is that it is slower than if it would be written in C, obviously. Dstat is not optimised for performance.

Note | This may seem ironic: a performance monitoring tool that is not optimised for performance, but rather for flexibility. However the ease of writing plugins and prototyping gets precedence over performance at this time. On the other hand we have pretty good tools to measure the overhead of a single plugin and profiling infrastructure to counter any excuses for sloppy plugin development.

### Plugin performance

If we look at the basic plugins, there are no real performance issues with Dstat. Loading Dstat takes longer to start than eg. vmstat, but once running, Dstat’s performance for the same functionality is up to par with vmstat, ifstat and other similar tools.

However there are some plugins that are much more resource intensive than others and the selection of plugins determines Dstat’s performance in a major way.

### Performance monitoring Dstat

Dstat comes with some plugins (starting with `dstat_`) to check the overhead of itself, this together with the selection of plugins makes it very convenient to measure the overhead of individual plugins. The following options exist (as plugins):

--dstat

  Provides cputime and latency information for Dstat. This plugin can help you determine how accurate and how much overhead Dstat has with its current plugins enabled.

--dstat-cpu

  Provides cpu utilization (user-space and kernel-space) statistics for Dstat. This plugin can help determine where there is some room for improvement for individual plugins (or Dstat itself).

--dstat-ctxt

  Provides context switch information for Dstat. Both voluntary as well ass involuntary context switches are shown, providing you with some idea of how the system is providing timeslices and how Dstat is returning the cpu to the system.

--dstat-mem

  Provides memory information about the Dstat process. This plugin enables plugin developers to determine whether Dstat is increasing its memory usage and therefor is leaking memory over time. This plugin proved very useful in optimizing memory usage of the top-plugins, which typically scan all processes.

--snooze

  This plugin shows in milliseconds how much time is deviating from the previous run. Which is influenced by the time it takes for earlier stats to be calculated. So the output of this plugin is very dependant on the location on the command-line.

--debug

  This option is not a plugin, but internal to Dstat. It will cause Dstat to show the actual time in milliseconds from start to end at the end of each line. This should be more or less close to the output of the `dstat_dstat` and `dstat_dstat_cpu` plugins.

  It also influences the internal `dstat_time` plugin to show milliseconds instead of seconds, which may help showing the accuracy of Dstat itself.

--profile

  Ths option is also not a plugin, but internal to Dstat. It provides you with detailed profiling information at the end of each run. The default settings can be changed inside Dstat (or a copy) to tweak the output you are looking for. It creates a termporary profiling file in the current directory when running, but will clean it up after exit.

### Measuring plugins

Here is a small example of how one can measure the impact of a plugin.

The cost of running the timer plugin

    [dag@rhun dag]$ dstat -t --debug
    Module dstat_time
    -----time-----
      date/time
    19-08 20:34:21  5.90ms
    19-08 20:34:22  0.17ms
    19-08 20:34:23  0.18ms
    19-08 20:34:24  0.18ms

Compare this with other plugins to see what the cost is of an individual plugin.

The cost of running the `dstat_cpu` plugin

    [dag@rhun dstat]$ dstat -c --debug
    Module dstat_cpu requires ['/proc/stat']
    ----total-cpu-usage----
    usr sys idl wai hiq siq
     15   3  77   4   0   1 11.07ms
      5   3  92   0   0   0  0.66ms
      5   4  91   0   0   0  0.65ms
      5   3  92   0   0   0  0.66ms

As you can see, getting the CPU counters and calculating the CPU usage takes up 0.5 milliseconds on this particular system. But if we look at the usage of the `dstat_top_cpu` plugin:

The cost of running the `dstat_top_cpu` plugin

    [dag@rhun dstat]$ dstat --top-cpu --debug
    Module dstat_top_cpu
    -most-expensive-
      cpu process
    Xorg           2 43.82ms
    Xorg           1 33.23ms
    firefox-bin    2 33.54ms
    Xorg           1 33.24ms

we see that processing the /proc/pid files causes the top-cpu plugin to use an additional 33ms.

Warning | These values show the time it takes to process the plugins and does not indicate the amount of CPU usage Dstat consumes. This obviously means that the process time of plugins depends on how much the system is being stressed as well as on what the plugin exactly is doing.

Plugins that communicate with other processes or those that process lots of information (eg. communicating with the mysql client, or processing the mail queue) may not actually use any local resources, but the latency causes Dstat to slow down processing other counters.

## Future development

The Dstat release contains a TODO file highlighting all the items and ideas that have been played with. Here is a list of the most important ones:

- Output

  - Changes in how Dstat colours digits within a value (the 6 in 6134B)

- Exporting information

  - Connecting Dstat with rrdtool

  - Exporting to syslog or remote syslog (a way to transport counters ?)

- Plugins

  - Be smart when plugins are loaded more than once (some plugins could benefit)

  - Add more plugins

- Redesign Dstat

  - Create an object-model and namespace for plugins and counters so that other tools can be based on Dstat

## Links

- Dstat homepage

- Dstat subversion

- Dstat mailinglist