tolleiv

module prom-stat

go 1.21.1

require github.com/prometheus/prometheus v0.47.2

require (
	github.com/beorn7/perks v1.0.1 // indirect
	github.com/cespare/xxhash/v2 v2.2.0 // indirect
	github.com/dennwc/varint v1.0.0 // indirect

tolleiv

Movies Recommendation:

• MovieLens - Movie Recommendation Data Sets http://www.grouplens.org/node/73
• Yahoo! - Movie, Music, and Images Ratings Data Sets http://webscope.sandbox.yahoo.com/catalog.php?datatype=r
• Jester - Movie Ratings Data Sets (Collaborative Filtering Dataset) http://www.ieor.berkeley.edu/~goldberg/jester-data/
• Cornell University - Movie-review data for use in sentiment-analysis experiments http://www.cs.cornell.edu/people/pabo/movie-review-data/

Music Recommendation:

• Last.fm - Music Recommendation Data Sets http://www.dtic.upf.edu/~ocelma/MusicRecommendationDataset/index.html

tolleiv

Font Awesome Dashing Widget

This is a Dashing widget and all components needed to port the original radiator information into an Dashing Widget.

##Usage

To use this widget, copy fa.html, fa.coffee, and fa.scss into the /widgets/fa directory. Or simply run dashing install da8fcf69316b1d16fcf6 to let dashing do that for you.

To include the widget in a dashboard, add the following snippet to the dashboard layout file:

tolleiv

Fortigate 300c log parsing in Logstash

QA ca be done with:

logstash-1.4.2/bin/logstash rspec --format documentation test.rb

tolleiv

apiVersion: v2
actions:
  - name: "Run hey"
    events:
      - name: "sh.keptn.event.test.triggered"
    tasks:
      - name: "Run hey smoke tests"
        image: "tolleiv/rakyll-hey:v0.1.4" # just the official Dockerfile build 
        cmd:
          - /hey

tolleiv

#!/bin/bash
# see http://cmusphinx.sourceforge.net/wiki/tutorialam
# see http://mnemonicplace.blogspot.de/2010/06/cmu-sphinx-error-wave2feat-error-while.html

sudo apt-get install build-essential autoconf libtool automake python-dev subversion bison vim
export PATH=/usr/local/bin:/usr/local/libexec/sphinxtrain:$PATH
export LD_LIBRARY_PATH=/usr/local/lib
export PKG_CONFIG_PATH=/usr/local/lib/pkgconfig
mkdir ~/tutorial
cd ~/tutorial

tolleiv

#
# Configure php error log filtering
#
filter {
	if [type] == "php-error" {
		multiline {
			pattern => "%{SYSLOG5424SD:timestamp} PHP (?:%{LOGLEVEL:loglevel})"
			negate => true
			what => "previous"
		}

tolleiv

upstream tracker {
    server localhost:81;
    server localhost:82 backup;
}

# HTTP server
server {
  listen 80 default;

	location / {

tolleiv

# What's the cost of keeping the top 25 metrics within Amazon Managed Service for Prometheus
# 1 -> amount of samples per minute
count(topk(25, count by (__name__, job)({__name__=~".+"}))) * 1 * 60 * 24 * 1/10000 * 0.002

# What's the cost of keeping all metrics within Amazon Managed Service for Prometheus
# 1 -> amount of samples per minute
count({__name__=~".+"}) * 1 * 60 * 24 * 1/10000 * 0.002

# * Doesn't take into account that it's geeting cheaper beyond 50 billion samples - you'll figure that out

tolleiv

import pandas as pd
import numpy as np
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt
import matplotlib.cm as mcm

# data prep
df = pd.read_csv('input.csv')
df = df.iloc[::-1]
df = df[df['Value'] > 0]