16%
17.06.2011
,200, comprising 55 different commands, were issued. The system, a server with 768MB RAM and a Pentium 3 CPU, took a total of 22 seconds to answer them, the longest response took 32 milliseconds, the shortest
16%
30.05.2021
Linux will be a community-based 1:1 binary replacement for Red Hat Enterprise Linux and currently ships with Gnome 3.32, Linux kernel 4.18.0-240.22.1.el8, SQLite 3.26, virt-what 1.18, Samba 4.12.3, DNF 4
16%
20.03.2014
on virtual machines. In fact, most of what you will find in Cloudify recipes can be achieved by integrating Chef Cookbooks.
Looking Forward: Cloudify 3.0
The current Cloudify version 2.6 has already been
16%
01.08.2019
INPUT
iptables -A INPUT -m state --state RELATED,ESTABLISHED -j ACCEPT
iptables -A INPUT -i eth0 -j DROP
iptables -A INPUT -i eth1 -p tcp --dport 22 -j ACCEPT
iptables -A INPUT -i eth1 -j DROP
16%
29.09.2020
and doubles the cache size (from 3 to 6MB), in exchange for a small drop in baseline clock speed – 2.3 to 2.2GHz (peak drops from 3.2 to 3.1GHz).
Major Surgery
Legend has it that no one has ever
opened
16%
01.04.2014
applications on virtual machines. In fact, most of what you will find in Cloudify recipes can be achieved by integrating Chef Cookbooks.
Looking Forward: Cloudify 3.0
The current Cloudify version 2.6 has
16%
07.10.2014
/test
[zk: localhost:2181(CONNECTED) 11] get /test
HelloWorld!
cZxid = 0xa1f54
ctime = Sun Jul 20 15:22:57 CEST 2014
mZxid = 0xa1f54
mtime = Sun Jul 20 15:22:57 CEST 2014
pZxid = 0xa1f54
cversion = 0
16%
05.08.2024
:
curl git pkg-config
0 upgraded, 3 newly installed, 0 to remove and 1 not upgraded.
Need to get 3,409 kB of archives.
After this operation, 19.5 MB of additional disk space will be used.
Get:1 http
16%
18.07.2013
attach xq eth0
21
22 set cpu idle
23 boot cpu
The first step in the OpenVMS installation is to write a so-called "save set" of the operating system from the CD to the hard drive:
backup dua3:vms073
16%
02.02.2021
i < 1000:
21 my_data.append(data_w_weekend(i / 1000))
22 i += 1
23
24 # add some noise
25 random_gain = 0.1 # factor for the noise
26 i = 0
27 while i < 1000:
28 my_data[i] += np
