How to Install and Uninstall rrdtool Package on openSuSE Tumbleweed
Last updated: November 22,2024
1. Install "rrdtool" package
Please follow the instructions below to install rrdtool on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
rrdtool
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2. Uninstall "rrdtool" package
In this section, we are going to explain the necessary steps to uninstall rrdtool on openSuSE Tumbleweed:
$
sudo zypper remove
rrdtool
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3. Information about the rrdtool package on openSuSE Tumbleweed
Information for package rrdtool:
--------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : rrdtool
Version : 1.8.0-4.4
Arch : x86_64
Vendor : openSUSE
Installed Size : 384.0 KiB
Installed : No
Status : not installed
Source package : rrdtool-1.8.0-4.4.src
Upstream URL : https://oss.oetiker.ch/rrdtool/
Summary : Round Robin Database Tool to store and display time-series data
Description :
RRD stands for Round Robin Database. RRD is a system to store and
display time-series data (i.e. network bandwidth, machine-room temperature,
server load average). It stores the data in a compact way that will not
expand over time, and it presents useful graphs by processing the data to
enforce a certain data density. It can be used either via simple wrapper
scripts (from shell or Perl) or via frontends that poll network devices and
put a friendly user interface on it.
--------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : rrdtool
Version : 1.8.0-4.4
Arch : x86_64
Vendor : openSUSE
Installed Size : 384.0 KiB
Installed : No
Status : not installed
Source package : rrdtool-1.8.0-4.4.src
Upstream URL : https://oss.oetiker.ch/rrdtool/
Summary : Round Robin Database Tool to store and display time-series data
Description :
RRD stands for Round Robin Database. RRD is a system to store and
display time-series data (i.e. network bandwidth, machine-room temperature,
server load average). It stores the data in a compact way that will not
expand over time, and it presents useful graphs by processing the data to
enforce a certain data density. It can be used either via simple wrapper
scripts (from shell or Perl) or via frontends that poll network devices and
put a friendly user interface on it.