pavinjosdev

Install packages

sudo zypper install yubikey-manager pam_u2f

Insert Yubikey and test

ykman info
ykman fido info

awoimbee

Sources:

• guide for ubuntu: https://support.yubico.com/hc/en-us/articles/360016649099-Ubuntu-Linux-Login-Guide-U2F
• guide for fedora: https://github.com/Zer0CoolX/Fedora-KDE-Yubikey-U2F-2FA-Logins-Guide/blob/master/README.md
• https://www.aukfood.fr/yubikey-parametrage-authentification-linux/

Commands:

# Generate the u2f keys/config
pamu2fcfg -u $(whoami) -opam://$HOSTNAME -ipam://$HOSTNAME > ~/u2f_keys

lcrilly

Prometheus exporter for NGINX Unit metrics

The NGINX Unit control API includes a /status endpoint for usage statistics. This is a solution for exposing these metrics in Prometheus format.

The application (run by Unit) queries the /status URI on the control socket and converts the JSON response into Prometheus text format. PHP and Python implementations are available.

These instructions assume an existing Unit installation with a working configuration. We will add a new listener on the default prometheus port (9090) and route it directly to the Prometheus app.

Step 0. Install the preferred Unit language module (unit-php or unit-python)

yogeshnile

import json
import boto3
import requests
from datetime import datetime, timedelta

CLIENT = boto3.client('ce')

SLACK_WEBHOOK_URL = '' # Enter the slack webhook url.

def lambda_handler(event, context):

tclh123

#!/bin/bash

set -eu

NAMESPACE=$1
PVCNAME=$2
TARGETZONE=$3

# SNAPSHOTID is optional, if you did a snapshot already, you can pass it
SNAPSHOTID=${4:-}

gfodor

Minimalist static FFmpeg build on Ubuntu 18.10 with Nvidia NVENC enabled.

Original guide with a standard build is here.

With this guide, I'm adding more instructions to enable support for NVIDIA CUVID and NVIDIA NPP for enhanced encode and decode performance.

First, prepare for the build and create the work space directory:

cd ~/

trautonen

# Edit your fish prompt with `funced fish_prompt` and
# add the following to a desired place in the function.
# Save the prompt after editing with `funcsave fish_prompt`.

# Set a variable for workspace color.
set -l tfworkspace_color (set_color green)

# Append the workspace name at the current prompt position if
# the directory contains a .terraform subdirectory
if test -d .terraform

kiki67100

#!/bin/bash

#Verify the quality with difference bitrate ( crf no work with h264_videotoolbox use -b:v ) 
#You can use the same audio codec change -c:a ac3 to -c:a copy i use it because it work my multimedia player
for bitrate in 500k 1000k 1500k 2500k 3000k 3500k;do 
   ffmpeg -i Movie.mkv -c:v h264_videotoolbox -c:a ac3 -b:a 128k  -y -b:v $bitrate -ss 00:01:00 -t 00:00:10 Movie_$bitrate.mp4;
done

#With 2500k bitrate 
ffmpeg -i Movie.mkv -c:v h264_videotoolbox -c:a ac3 -b:a 128k -y -b:v $bitrate -b:a 128k Movie_$bitrate.mp4;

Brainiarc7

Build VAAPI with support for VP8/9 decode and encode hardware acceleration on a Skylake validation testbed:

Build platform: Ubuntu 16.04LTS.

First things first:

Install baseline dependencies first

sudo apt-get -y install autoconf automake build-essential libass-dev libtool pkg-config texinfo zlib1g-dev libva-dev cmake mercurial libdrm-dev libvorbis-dev libogg-dev git libx11-dev libperl-dev libpciaccess-dev libpciaccess0 xorg-dev intel-gpu-tools

w495

# -*- coding: utf8 -*-

import av

# Откроем ресурс на чтение
input_resource = av.open(
    'rtmp://src_stream:1935/play'
)
# Откроем ресурс на запись.
output_resource = av.open(