jammy (1) rrdtool.1.gz

Provided by: rrdtool_1.7.2-3ubuntu6_amd64 bug

NAME

       rrdtool - Round Robin Database Tool

SYNOPSIS

       rrdtool - [workdir]| function

DESCRIPTION

   OVERVIEW
       It is pretty easy to gather status information from all sorts of things, ranging from the temperature in
       your office to the number of octets which have passed through the FDDI interface of your router. But it
       is not so trivial to store this data in an efficient and systematic manner. This is where RRDtool comes
       in handy. It lets you log and analyze the data you gather from all kinds of data-sources (DS). The data
       analysis part of RRDtool is based on the ability to quickly generate graphical representations of the
       data values collected over a definable time period.

       In this man page you will find general information on the design and functionality of the Round Robin
       Database Tool (RRDtool). For a more detailed description of how to use the individual functions of
       RRDtool check the corresponding man page.

       For an introduction to the usage of RRDtool make sure you consult the rrdtutorial.

   FUNCTIONS
       While the man pages talk of command line switches you have to set in order to make RRDtool work it is
       important to note that RRDtool can be remotely controlled through a set of pipes. This saves a
       considerable amount of startup time when you plan to make RRDtool do a lot of things quickly. Check the
       section on "REMOTE CONTROL" further down. There is also a number of language bindings for RRDtool which
       allow you to use it directly from Perl, python, Tcl, PHP, etc.

       create  Set up a new Round Robin Database (RRD). Check rrdcreate.

       update  Store new data values into an RRD. Check rrdupdate.

       updatev Operationally equivalent to update except for output. Check rrdupdate.

       graph   Create a graph from data stored in one or several RRDs. Apart from generating graphs, data can
               also be extracted to stdout. Check rrdgraph.

       graphv  Create a graph from data stored in one or several RRDs. Same as graph, but metadata are printed
               before the graph. Check rrdgraph.

       dump    Dump the contents of an RRD in plain ASCII. In connection with restore you can use this to move
               an RRD from one computer architecture to another.  Check rrddump.

       restore Restore an RRD in XML format to a binary RRD. Check rrdrestore

       fetch   Get data for a certain time period from a RRD. The graph function uses fetch to retrieve its data
               from an RRD. Check rrdfetch.

       tune    Alter setup and structure of an RRD. Check rrdtune.

       first   Find the first update time of an RRD. Check rrdfirst.

       last    Find the last update time of an RRD. Check rrdlast.

       lastupdate
               Find the last update time of an RRD. It also returns the value stored for each datum in the most
               recent update. Check rrdlastupdate.

       info    Get information about an RRD. Check rrdinfo.

       resize  Change the size of individual RRAs. This is dangerous! Check rrdresize.

       xport   Export data retrieved from one or several RRDs. Check rrdxport.

       flushcached
               Flush the values for a specific RRD file from memory. Check rrdflushcached.

       list    List the directories and rrd databases remotely. Check rrdlist.

   HOW DOES RRDTOOL WORK?
       Data Acquisition
               When monitoring the state of a system, it is convenient to have the data available at a constant
               time interval. Unfortunately, you may not always be able to fetch data at exactly the time you
               want to. Therefore RRDtool lets you update the log file at any time you want. It will
               automatically interpolate the value of the data-source (DS) at the latest official time-slot
               (interval) and write this interpolated value to the log. The original value you have supplied is
               stored as well and is also taken into account when interpolating the next log entry.

       Consolidation
               You may log data at a 1 minute interval, but you might also be interested to know the development
               of the data over the last year. You could do this by simply storing the data in 1 minute
               intervals for the whole year. While this would take considerable disk space it would also take a
               lot of time to analyze the data when you wanted to create a graph covering the whole year.
               RRDtool offers a solution to this problem through its data consolidation feature. When setting up
               a Round Robin Database (RRD), you can define at which interval this consolidation should occur,
               and what consolidation function (CF) (average, minimum, maximum, last) should be used to build
               the consolidated values (see rrdcreate). You can define any number of different consolidation
               setups within one RRD. They will all be maintained on the fly when new data is loaded into the
               RRD.

       Round Robin Archives
               Data values of the same consolidation setup are stored into Round Robin Archives (RRA). This is a
               very efficient manner to store data for a certain amount of time, while using a known and
               constant amount of storage space.

               It works like this: If you want to store 1'000 values in 5 minute interval, RRDtool will allocate
               space for 1'000 data values and a header area. In the header it will store a pointer telling
               which slots (value) in the storage area was last written to. New values are written to the Round
               Robin Archive in, you guessed it, a round robin manner. This automatically limits the history to
               the last 1'000 values (in our example). Because you can define several RRAs within a single RRD,
               you can setup another one, for storing 750 data values at a 2 hour interval, for example, and
               thus keep a log for the last two months at a lower resolution.

               The use of RRAs guarantees that the RRD does not grow over time and that old data is
               automatically eliminated. By using the consolidation feature, you can still keep data for a very
               long time, while gradually reducing the resolution of the data along the time axis.

               Using different consolidation functions (CF) allows you to store exactly the type of information
               that actually interests you: the maximum one minute traffic on the LAN, the minimum temperature
               of your wine cellar, ... etc.

       Unknown Data
               As mentioned earlier, the RRD stores data at a constant interval. Sometimes it may happen that no
               new data is available when a value has to be written to the RRD. Data acquisition may not be
               possible for one reason or other. With RRDtool you can handle these situations by storing an
               *UNKNOWN* value into the database. The value '*UNKNOWN*' is supported through all the functions
               of the tool. When consolidating a data set, the amount of *UNKNOWN* data values is accounted for
               and when a new consolidated value is ready to be written to its Round Robin Archive (RRA), a
               validity check is performed to make sure that the percentage of unknown values in the data point
               is above a configurable level. If not, an *UNKNOWN* value will be written to the RRA.

       Graphing
               RRDtool allows you to generate reports in numerical and graphical form based on the data stored
               in one or several RRDs. The graphing feature is fully configurable. Size, color and contents of
               the graph can be defined freely. Check rrdgraph for more information on this.

       Aberrant Behavior Detection
               by Jake Brutlag

               RRDtool provides the building blocks for near real-time aberrant behavior detection. These
               components include:

               •   An algorithm for predicting the value of a time series one time step into the future.

               •   A measure of deviation between predicted and observed values.

               •   A mechanism to decide if and when an observed value or sequence of observed values is too
                   deviant from the predicted value(s).

               Here is a brief explanation of these components:

               The Holt-Winters time series forecasting algorithm is an on-line (or incremental) algorithm that
               adaptively predicts future observations in a time series. Its forecast is the sum of three
               components: a baseline (or intercept), a linear trend over time (or slope), and a seasonal
               coefficient (a periodic effect, such as a daily cycle). There is one seasonal coefficient for
               each time point in the period (cycle). After a value is observed, each of these components is
               updated via exponential smoothing. This means that the algorithm "learns" from past values and
               uses them to predict the future. The rate of adaptation is governed by 3 parameters, alpha
               (intercept), beta (slope), and gamma (seasonal). The prediction can also be viewed as a smoothed
               value for the time series.

               The measure of deviation is a seasonal weighted absolute deviation. The term seasonal means
               deviation is measured separately for each time point in the seasonal cycle. As with Holt-Winters
               forecasting, deviation is predicted using the measure computed from past values (but only at that
               point in the seasonal cycle). After the value is observed, the algorithm learns from the observed
               value via exponential smoothing. Confidence bands for the observed time series are generated by
               scaling the sequence of predicted deviation values (we usually think of the sequence as a
               continuous line rather than a set of discrete points).

               Aberrant behavior (a potential failure) is reported whenever the number of times the observed
               value violates the confidence bands meets or exceeds a specified threshold within a specified
               temporal window (e.g. 5 violations during the past 45 minutes with a value observed every 5
               minutes).

               This functionality is embedded in a set of related RRAs. In particular, a FAILURES RRA logs
               potential failures. With these data you could, for example, use a front-end application to
               RRDtool to initiate real-time alerts.

               For a detailed description on how to set this up, see rrdcreate.

   REMOTE CONTROL
       When you start RRDtool with the command line option '-' it waits for input via standard input (STDIN).
       With this feature you can improve performance by attaching RRDtool to another process (MRTG is one
       example) through a set of pipes. Over these pipes RRDtool accepts the same arguments as on the command
       line and some special commands like cd, mkdir, pwd, ls and quit. For detailed help on the server commands
       type:

          rrdtool help cd

       When a command is completed, RRDtool will print the string  '"OK"', followed by timing information of the
       form u:usertime s:systemtime. Both values are the running totals of seconds since RRDtool was started. If
       an error occurs, a line of the form '"ERROR:" Description of error' will be printed instead. RRDtool will
       not abort, unless something really serious happens. If a workdir is specified and the UID is 0, RRDtool
       will do a chroot to that workdir. If the UID is not 0, RRDtool only changes the current directory to
       workdir.

   RRD Server
       If you want to create a RRD-Server, you must choose a TCP/IP Service number and add them to /etc/services
       like this:

        rrdsrv      13900/tcp                       # RRD server

       Attention: the TCP port 13900 isn't officially registered for rrdsrv. You can use any unused port in your
       services file, but the server and the client system must use the same port, of course.

       With this configuration you can add RRDtool as meta-server to /etc/inetd.conf. For example:

        rrdsrv stream tcp nowait root /opt/rrd/bin/rrdtool rrdtool - /var/rrd

       Don't forget to create the database directory /var/rrd and reinitialize your inetd.

       If all was setup correctly, you can access the server with Perl sockets, tools like netcat, or in a quick
       interactive test by using 'telnet localhost rrdsrv'.

       NOTE: that there is no authentication with this feature! Do not setup such a port unless you are sure
       what you are doing.

RRDCACHED, THE CACHING DAEMON

       For very big setups, updating thousands of RRD files often becomes a serious IO problem. If you run into
       such problems, you might want to take a look at rrdcached, a caching daemon for RRDtool which may help
       you lessen the stress on your disks.

SEE ALSO

       rrdcreate, rrdupdate, rrdgraph, rrddump, rrdfetch, rrdtune, rrdlast, rrdxport, rrdflushcached, rrdcached

BUGS

       Bugs? Features!

AUTHOR

       Tobias Oetiker <tobi@oetiker.ch>