$ tar -xvf vmName.ova
$ vi vmName.ovf
test: | |
multiline: | | |
f4x6aaBtLPQk898Ymfkn | |
TQsi69wDY40aluFbdp99 | |
jqdGOkx9CN2xgWOM8JeI | |
M4lXnXyctLTDejDb2eZu | |
XBPmvqXJStQFZIQwHzLF | |
by0cxOYjrY3On6hj3oqk | |
Xu0Ze6Sz8EbC7udHsyxE | |
jNv0M7lWNJCfegOlDCJH |
*.img | |
*.raw |
import requests | |
import time | |
import icalendar | |
import datetime | |
import pytz | |
from colored import fg, bg, attr | |
def loopme(): | |
r = requests.get('https://fahrplan.chaos-west.de/35c3chaoswest/schedule/export/schedule.ics') |
variable "hcloud_token" { | |
} | |
provider "hcloud" { | |
token = "${var.hcloud_token}" | |
} | |
resource "hcloud_server" "kube-master" { | |
name = "kube-master" | |
image = "ubuntu-18.04" |
#!/bin/bash | |
# Reminds you in xx minutes with notify-send, using at/atd | |
MINUTES=${1} | |
MESSAGE=${2:-reminder} | |
at now + "${MINUTES}" minutes << EOF | |
notify-send -c reminder -u critical 'Reminder from ${MINUTES} minutes ago' '${MESSAGE}' | |
EOF |
Running a Django app with gunicorn in a Docker container gets a bit tricky, when you try to expose Prometheus metrics (with e.g. https://github.com/korfuri/django-prometheus).
Every worker thread in gunicorn will be an entirely separate process, all RRD behind a single port. So, if you are running more than one worker thread (which you most likely do and should) you will need to let the workers each listen on a dedicated port, so your metrics will not get confused. You could try to add additional labels, but that still would come with a lot of problems. Running on a range of ports is supported quite well with korfuri/django-prometheus, as described here: https://github.com/korfuri/django-prometheus/blob/master/documentation/exports.md#exporting-metrics-in-a-wsgi-application-with-multiple-processes
This will be a bit uncomfortable though, especially if your app is hidden behind an ingress reverse proxy and you do not want to punch lots of holes into your firewall config, or create lots and lots of vhosts.
This simple script will take a picture of a whiteboard and use parts of the ImageMagick library with sane defaults to clean it up tremendously.
The script is here:
#!/bin/bash
convert "$1" -morphology Convolve DoG:15,100,0 -negate -normalize -blur 0x1 -channel RBG -level 60%,91%,0.1 "$2"
python manage.py shell |