Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.
$ python -m SimpleHTTPServer 8000
Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.
$ python -m SimpleHTTPServer 8000
#!/usr/bin/env ruby | |
recipe_path = ARGV[0] | |
if recipe_path.nil? | |
STDERR.puts "usage: chef-apply RECIPE_FILE" | |
exit 1 | |
end | |
recipe_path = File.expand_path(recipe_path) |
Operation: Decouple whisper from graphite.
Method: Create a graphite function that does a date histogram facet query against elasticsearch for a given query string for the time period viewed in the current graph.
Reason: graphite has some awesome math functions. Wouldn't it be cool if we could use those on logstash results?
The screenshot below is using logstash to watch the twitter stream of keywords "iphone" "apple" and "samsung" - then I graph them each, so we get an idea of popularity. As a bonus, I also do a movingAverage() on the iphone curve to show you why this is awesome.
In a perfect world, where things are done well, not just quickly, I would expect to find the following when joining the company:
Documentation
Accurate / up-to-date systems architecture diagram
Accurate / up-to-date network diagram
Out-of-hours support plan
Incident management plan
package main | |
import ( | |
"fmt" | |
"bytes" | |
"os" | |
"log" | |
"time" | |
"io" | |
"http" |