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@wallin
wallin / script.js
Created April 12, 2011 21:11 — forked from jacobk/script.js
$(function() {
$('div.content').live('showoff:show', function(evt) {
var bg_img = $('img[alt=background]', evt.target);
var old_bg = '';
if (bg_img.size() > 0) {
var src = bg_img.attr('src');
bg_img.hide();
// Set new background on body
old_bg = $('body').css('background-image');
$('body')
@benjchristensen
benjchristensen / index.html
Created August 16, 2011 03:21
Animated Line Graphs / Sparklines using SVG Path and d3.js
<html>
<head>
<title>Animated Sparkline using SVG Path and d3.js</title>
<script src="http://mbostock.github.com/d3/d3.v2.js"></script>
<style>
/* tell the SVG path to be a thin blue line without any area fill */
path {
stroke: steelblue;
stroke-width: 1;
fill: none;
@massat
massat / supervisord
Created October 12, 2011 06:52
init script for supervisord
#!/bin/sh
#
# /etc/rc.d/init.d/supervisord
#
# Supervisor is a client/server system that
# allows its users to monitor and control a
# number of processes on UNIX-like operating
# systems.
#
# chkconfig: - 64 36
@chrishamant
chrishamant / s3_multipart_upload.py
Created January 3, 2012 19:29
Example of Parallelized Multipart upload using boto
#!/usr/bin/env python
"""Split large file into multiple pieces for upload to S3.
S3 only supports 5Gb files for uploading directly, so for larger CloudBioLinux
box images we need to use boto's multipart file support.
This parallelizes the task over available cores using multiprocessing.
Usage:
s3_multipart_upload.py <file_to_transfer> <bucket_name> [<s3_key_name>]
@alq666
alq666 / cloudwatch.awk
Created March 5, 2012 20:52
aws crawler stats
BEGIN {
skipped = 0;
processed = 0;
}
/Skipped/ {
skipped++;
}
/Saving/ {
@jboner
jboner / latency.txt
Last active May 3, 2024 15:17
Latency Numbers Every Programmer Should Know
Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference 0.5 ns
Branch mispredict 5 ns
L2 cache reference 7 ns 14x L1 cache
Mutex lock/unlock 25 ns
Main memory reference 100 ns 20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy 3,000 ns 3 us
Send 1K bytes over 1 Gbps network 10,000 ns 10 us
Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD
@bcambel
bcambel / gist:2844136
Created May 31, 2012 15:24
DDAGENTSRV_LOG
2012-05-31 15:17:40,719 - root - INFO - Logging to /tmp/dd-agent.log
2012-05-31 15:17:40,719 - root - WARNING - Pid file: /tmp/dd-agent.pid
2012-05-31 15:17:40,719 - root - INFO - Running in foreground
2012-05-31 15:17:40,719 - agent - DEBUG - Collecting basic system stats
2012-05-31 15:17:40,738 - agent - DEBUG - System: {'nixV': ('Ubuntu', '10.04', 'lucid'), 'cpuCores': 2, 'machine': 'x86_64', 'platform': 'linux2', 'pythonV': '2.6.5', 'processor': ''}
2012-05-31 15:17:40,738 - agent - DEBUG - Creating checks instance
2012-05-31 15:17:40,785 - agent - INFO - Running on EC2, instanceId: i-fdf2929e
2012-05-31 15:17:40,786 - checks - INFO - Dogstream parsers: []
2012-05-31 15:17:40,788 - checks - INFO - Starting checks
2012-05-31 15:17:40,788 - checks - DEBUG - SIZE: <function getApacheStatus at 0x2ca5a28> wrote 5 bytes uncompressed
@mlambie
mlambie / apache_extended_status
Created July 11, 2012 03:26
Extended output
root@arcee:/var/log# curl http://localhost/server-status?auto
BusyWorkers: 1
IdleWorkers: 9
Scoreboard: _W.________.....................................................................................................................................................................................................................................................
VS.
mlambie@blitzwing:~$ curl http://localhost/server-status?auto
Total Accesses: 557
Total kBytes: 17924
@alq666
alq666 / gist:3174101
Created July 25, 2012 02:50
Datadog functions

A short introduction to Datadog functions

You can apply functions to metric queries in the graph editor, as long as you use the JSON editor.

The general format is:

function(metric{scope} [by {filter}])

In case of binary operators (+, -, /, *), the format is:

@alq666
alq666 / dogapi.sh
Created August 29, 2012 22:39
Deploy the dog cli in your home directory
#!/bin/bash -e
# Check python 2.6 or greater
python -V 2>&1 | awk '$2 !~ /^2.[67]|^3/ {exit 1}'
# Download virtualenv
curl https://raw.github.com/pypa/virtualenv/master/virtualenv.py > virtualenv.py
python virtualenv.py $HOME/datadog
source $HOME/datadog/bin/activate
# Install dogapi
pip install dogapi
# Set up the dog alias