30%
04.08.2020
(minified by 25.99X)
from python:2.7-alpine - 84.3MB => 23.1MB (minified by 3.65X)
from python:2.7.15 - 916MB => 27.5MB (minified by 33.29X)
from centos:7 - 647MB => 23MB (minified by 28.57X)
from centos
30%
06.10.2019
the Debian-based, distributions install it along with openvpn – one exception being Ubuntu, which only offers easy-rsa starting with Cosmic Cuttlefish (Ubuntu version 18.10) [3].
The successor, Easy-RSA 3
30%
06.10.2019
Stax Insights [3]. The former enables flexible scalability in Cassandra clusters and consumption-based billing supported by the stability and performance enhancements of DataStax Enterprise, which monitors
30%
18.07.2013
backend3.example.com server;
05 backend4.example.com server down;
06 backend5.example.com backup server;
07 }
08
09 upstream fallback {
10 fallback1.example.com server: 8081;
11 }
12
13
14 server {
15 %
16
30%
12.09.2013
.pl
00:00:00.50023
The output shows the amount of computing time the database engine consumed. You can pass in the desired time as a CGI parameter:
$ curl http://localhost/cgi/burn0.pl\?3
00:00
30%
04.12.2024
. In this case you will select the Quiet Mode
Option. The final touch will be to make sure you get alerts when something fails at 3:00am, so you will be notified (or not). The Beep Control option is especially
30%
30.01.2013
, for a library that uses a specific compiler and MPI library, you would end up with a module names like atlas-3.10.0-opempi-1.6.2-open64-5.0
. The name is useful because it tells the user the library version
30%
05.12.2014
CellStyle(sheetSubTitle[[1,1]], csSubTitle)
52
53 # Body
54 rows <- addDataFrame(data,sheet,startRow=4,
startColumn=1, colnamesStyle = csTableColNames,
colStyle=list('2'=csBody, '3'=csBody))
55 set
30%
09.04.2019
, and you aren't using Kubernetes.
Linkerd 2.x [3], formerly Conduit, is a Kubernetes-only (faster) alternative to Linkerd 1.x. This complete service mesh features a native code sidecar proxy written in Rust
30%
07.06.2019
)
Call:
lm(formula = Sessions ~ wday + month, data = datPrep[datPrep$isTrainData, ])
Residuals:
Min 1Q Median 3Q Max
-464.80 -61.88 -6.52 62.38 479.19
Coefficients
