Erisa

#!/bin/bash
set +x

version="${VERSION:-1.6.1}"
arch="${ARCH:-linux-amd64}"
bin_dir="${BIN_DIR:-/usr/local/bin}"

wget "https://github.com/prometheus/node_exporter/releases/download/v$version/node_exporter-$version.$arch.tar.gz" \
    -O /tmp/node_exporter.tar.gz

joemiller

FROM balabit/syslog-ng:3.35.1

COPY syslog-ng.conf /etc/syslog-ng/syslog-ng.conf

BoredHackerBlog

version: "3"

networks:
  loki:

services:
  loki:
    image: grafana/loki:2.4.0
    volumes:
      - ./loki:/etc/loki

p1nox

After researching a lot on how to use PyTorch with a RTX 3060 card, specially with older versions or torch (0.4.0) and torchvision (0.2.1), I noticed that it was either impossible or very hard to do. RTX 3060 and these packages apparently doesn't have compatibility with the same versions of CUDA and cuDNN. I tried to do this by using different combinations with compiled versions available in conda, but didn't work, maybe it could work if you recompile from source these versions.

After all this, actually I was able to use RTX 3060 effectively with latest versions of all these dependencies with two methods:

1. Using a conda env, and latest versions published in pytorch site (https://pytorch.org/get-started/locally):

conda create -n rtx_3060 python=3.6.5
conda activate rtx_3060
conda install pytorch torchvision torchaudio cudatoolkit=11.1 -c pytorch -c nvidia

christophersjchow

input {
  udp {
    port => 10514
    type => unifi_syslog
  }
}

filter {
  if [type] == "unifi_syslog" {
    grok {

superseb

k3s etcd commands

etcd

Setup etcdctl using the instructions at https://github.com/etcd-io/etcd/releases/tag/v3.4.13 (changed path to /usr/local/bin):

Note: if you want to match th etcdctl binaries with the embedded k3s etcd version, please run the curl command for getting the version first and adjust ETCD_VER below accordingly:

curl -L --cacert /var/lib/rancher/k3s/server/tls/etcd/server-ca.crt --cert /var/lib/rancher/k3s/server/tls/etcd/server-client.crt --key /var/lib/rancher/k3s/server/tls/etcd/server-client.key https://127.0.0.1:2379/version

superseb

Generate ECDSA CA, intermediate CA and server certificate with DNS alt names using Terraform in Docker and launch Rancher

Generate ECDSA CA, intermediate CA and server certificate

docker run --rm -v $PWD/testcerts:/tmp/certs/files -e TF_VAR_ip_addresses='["127.0.0.1"]' -e TF_VAR_dns_names='["yolo.seb.local"]' superseb/intermediate-ecdsa

Run Rancher

mikestecker

optimising-unifi-performance

NOTE: Content below is written by Adrian Mace. Click here for an updated version.

Below are the key settings that I apply on any unifi installation for optimal performance.

Settings

Settings > Site

• Ensure Enable Advanced Features is enabled
  This allows you to follow along with the guide in it's entirety.

iedmrc

import functools
import asyncio
from concurrent.futures import ThreadPoolExecutor


def to_async(func):
    """Turns a sync function to async function using event loop"""
    @functools.wraps(func)
    async def run(*args, loop=None, executor=None, **kwargs):
        if loop is None:

superseb

#!/bin/bash
if [ "$#" -lt 0 ]; then
  echo "Usage: $0"
  exit 1
fi

echo "Generating nip.io based on found external IP"
FOUNDIP=$(docker run --rm --net=host appropriate/curl https://api.ipify.org)
APIFQDN="minio-api.${FOUNDIP}.nip.io"
FQDN="minio.${FOUNDIP}.nip.io"