39%
14.08.2017
) with Google, helped incubate Prometheus to get it ready for production when working for SoundCloud in 2012. Starting in 2014, other companies began taking advantage of it. In 2015, the creators published
39%
06.10.2022
The Quick UDP Internet Connections (QUIC) protocol [1] originated in 2012 as a Google project led by Jim Roskind to improve security and performance over TCP. The protocol made the leap to four
39%
28.11.2022
, the OpenStack Summit were surrounded by something like a mystical aura: 8,000 participants and more regularly joined the private cloud computing environment camp to catch up on the latest technology. In 2012
39%
08.10.2015
is a professional software tool, and the fan base appreciates its solid operating principles. Version 1.0 was released in mid-1999 [1], followed by 2.0 in 2000. The latest stable branch 2.1 appeared about 12 years
39%
03.12.2015
the distributed prefixes was not enough. Wahl started to develop dhcpy6d. As the name indicates, the tool is written in Python. After a few years of work at the Institute, Wahl released the software in 2012 [6
39%
30.01.2020
Receiving objects: 100% (2955/2955), 971.57 KiB | 915.00 KiB/s, done.
Resolving deltas: 100% (1934/1934), done.
The README file recommends installing the ansi2html
and detect-secrets
packages
39%
18.02.2018
In Windows Server 2016, a Storage Spaces Direct (S2D) can comprise several hard disks, but also several servers, that can be connected to a cluster to increase data storage flexibility. S2D
39%
05.02.2019
:
$ curl http://169.254.169.254/openstack
2012-08-10
2013-04-04
2013-10-17
2015-10-15
2016-06-30
2016-10-06
2017-02-22
To retrieve a list of supported versions for the EC2-compatible metadata API, enter
39%
11.06.2014
, and infinitely performant. It's the best of both worlds for technical people and bean counters alike. Google Compute Engine is a stellar IaaS (Infrastructure as a Service) example that is part of a larger suite
39%
02.06.2020
and storage capacity. In contrast, comparatively little has happened in the core algorithms of AI. Deep learning and convolutional neural networks are still based on ideas from the 1980s and 1990s. The success
