RRDTOOL(1)                          rrdtool                         RRDTOOL(1)

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:systemtimer:runtime.  The  usertime  and  systemtime  values  are the
       running totals of seconds since RRDtool was started.   runtime  is  the
       total  amount  of  seconds  that RRDtool has been running.  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.

ENVIRONMENT VARIABLES
       The  following environment variables may be used to change the behavior
       of most of the utilities.

       RRD_LOCKING
           If this environment variable is set, the RRD file is locked in  the
           given mode:

           -   try fails, when the file is locked by another process.  This is
               the default.

           -   block waits until the lock is released.

           -   none  skips  locking  at  all.   Caller  has to ensure a proper
               locking which should be  compatible  with  "fcntl(fd,  F_SETLK,
               ...)".

           Some utilities have command line options (--locking) which override
           this variable.

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>

1.10.3                            2026-05-25                        RRDTOOL(1)
