24%
18.02.2018
public_key = "${file("${var.ssh_pub_key}")}"
07 }
08 resource "digitalocean_droplet" "mywebapp" {
09 image = "docker-16-04"
10 name: guest
11 region = "fra1"
12 size = "512mb"
13 ssh
23%
20.05.2014
Viewing Server Topology
01 # numactl --hardware
available: 8 nodes (0-7)
node 0 cpus: 0 1 2 3 4 5 6 7 8 9
node 0 size: 16373 MB
node 0 free: 15837 MB
node 1 cpus: 10 11 12 13 14 15 16 17 18 19
node 1
23%
25.03.2021
: pid=5872: Sat Jan 9 16:35:08 2021
read: IOPS=251k, BW=979MiB/s (1026MB/s)(2045MiB/2089msec)
[ ... ]
Run status group 0 (all jobs):
READ: bw=979MiB/s (1026MB/s), 979MiB/s-979MiB/s (1026MB
23%
21.01.2020
local server machine (Listing 1). In this example, the four drives sdb
to sde
in lines 12, 13, 15, and 16 will be used to create the NVMe target. Each drive is 7TB, which you can verify
23%
25.03.2020
local server machine (Listing 1). In this example, the four drives sdb
to sde
in lines 12, 13, 15, and 16 will be used to create the NVMe target. Each drive is 7TB, which you can verify
23%
13.04.2023
laytonjb laytonjb 4096 Mar 14 19:43 cache
12 -rw-rw-r-- 1 laytonjb laytonjb 11277 Mar 14 19:43 termcolor-2.2.0-pyhd8ed1ab_0.conda
4 drwxrwxr-x 4 laytonjb laytonjb 4096 Mar 14 19:43 termcolor-2.2.0-pyhd8ed1ab
23%
29.09.2020
-line operations.
To install Dockly [3], you can choose one of two routes: with npm (see the "Installation by npm" box for that route) and in a Docker container. For context, on my laptop, about 43MB of file space
23%
09.08.2015
resources = Resources(cpu = 0.1, ram = 20*MB, disk = 20*MB),
09 processes = [hello_world_process])
10
11 hello_world_job = Job(
12 cluster = 'test',
13 role = os.getenv('USER'),
14 task = hello
23%
04.08.2020
] are impressive, although Node.js, Ruby, Golang, Java, PHP, and other languages can be expected to achieve similar results.
Listing 1
Python Minify Results
from ubuntu:14.04 - 438MB => 16.8MB
23%
01.08.2019
CREATED SIZE
nginx f09fe80eb0e7 12 days ago 109MB
nginx latest 35640fed495c 12 days ago 109MB
Backdoor Access
Considering how well Docker Scan handled
