How to Install and Uninstall haproxy Package on openSuSE Tumbleweed
Last updated: November 07,2024
1. Install "haproxy" package
This is a short guide on how to install haproxy on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
haproxy
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2. Uninstall "haproxy" package
Please follow the guidelines below to uninstall haproxy on openSuSE Tumbleweed:
$
sudo zypper remove
haproxy
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3. Information about the haproxy package on openSuSE Tumbleweed
Information for package haproxy:
--------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : haproxy
Version : 2.9.6+git0.9eafce5dc-1.1
Arch : x86_64
Vendor : openSUSE
Installed Size : 7.8 MiB
Installed : No
Status : not installed
Source package : haproxy-2.9.6+git0.9eafce5dc-1.1.src
Upstream URL : http://www.haproxy.org/
Summary : The Reliable, High Performance TCP/HTTP Load Balancer
Description :
HAProxy implements an event-driven, mono-process model which enables support
for very high number of simultaneous connections at very high speeds.
Multi-process or multi-threaded models can rarely cope with thousands of
connections because of memory limits, system scheduler limits, and lock
contention everywhere. Event-driven models do not have these problems because
implementing all the tasks in user-space allows a finer resource and time
management. The down side is that those programs generally don't scale well on
multi-processor systems. That's the reason why they must be optimized to get
the most work done from every CPU cycle.
--------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : haproxy
Version : 2.9.6+git0.9eafce5dc-1.1
Arch : x86_64
Vendor : openSUSE
Installed Size : 7.8 MiB
Installed : No
Status : not installed
Source package : haproxy-2.9.6+git0.9eafce5dc-1.1.src
Upstream URL : http://www.haproxy.org/
Summary : The Reliable, High Performance TCP/HTTP Load Balancer
Description :
HAProxy implements an event-driven, mono-process model which enables support
for very high number of simultaneous connections at very high speeds.
Multi-process or multi-threaded models can rarely cope with thousands of
connections because of memory limits, system scheduler limits, and lock
contention everywhere. Event-driven models do not have these problems because
implementing all the tasks in user-space allows a finer resource and time
management. The down side is that those programs generally don't scale well on
multi-processor systems. That's the reason why they must be optimized to get
the most work done from every CPU cycle.