markuskont

// see Robert Sedgewick :: Left-leaning Red-Black Trees

const RED   = true;
const BLACK = false;

var Node = function(key, value) {
         this.key   = key;
         this.value = value;
         this.color = RED;
         this.N = 1;

markuskont

#!/bin/bash
# apt-get install python-pip
# pip install elasticsearch-curator

RETAINDAYS=14
INDICES=( suricata apache cee syslog samba logstash )

for i in "${INDICES[@]}"
do
  echo "${i}"

markuskont

for indice in `pcregrep --color -o1 '^\S+\s+\S+\s+(\S+)' indices.txt `; do 
  curl -ss -XPUT localhost:9200/$indice/_settings -d '
    {
      "index" : {
          "number_of_replicas" : 0
      }
    }'
done 

markuskont

curl -ssk -XPUT localhost:9200/_cluster/settings -d '{
  "transient" :{
      "cluster.routing.allocation.exclude._name" : "node-8-es-01,node-9-es-01"
   }
}'

markuskont

#!/usr/bin/python
# A testing implementation of binary trees
# Very primitive (key = value, no duplicates, only integers)
# http://www.algolist.net/Data_structures/Binary_search_tree/Insertion
# http://stackoverflow.com/questions/2598437/how-to-implement-a-binary-tree-in-

class Node:
    def __init__(self, val):
        self.l = None
        self.r = None

markuskont

#!/usr/bin/env python

import sys

def openfile(argv):
    with open(argv, 'r') as file:
        lines = [line.rstrip('\n') for line in file]
    return lines

PUPPET_TPL = """auditd::rule { "audit-rule-%(INDEX)s":

markuskont

#!/usr/bin/env python
# A simple python playground for playing with top-k algorithms
# process data stream S and return most frequent K elements
# in my case, I create a unix socket and process syslog stream from syslog-ng
# syslog template only contains host, program and message; no timestamp
# as this is a naive implementation, with native python data structures (dictionaries)
# thus only useful for testing, not real data streams

import socket
import os, os.path

markuskont

destination d_auditd {
    file("/var/log/auditd.json" template("$(format-json .auditd.*)\n"));
};

parser p_auditd {
    linux-audit-parser (prefix(".auditd."));
};

filter f_auditd {program("audispd")};

markuskont

lvm2:
  pkg.installed: []

/dev/sdb:
  lvm.pv_present:
    - require:
      - pkg: lvm2

DATA:
  lvm.vg_present:

markuskont

[alerta]
  # Configure Alerta.
  enabled = true
  # The Alerta URL.
  url = "http://192.168.0.197:8080"
  # Default authentication token.
  token = ""
  # Default environment.
  environment = "Production"
  # Default origin.