What Is It? Real-time counting of rolled-up multi-dimensional metric data via HTTP service.

OK, now in english? Live graphs of events happening in real-time, for any measurable things you want to measure, grouped by any properties you want to define about these events.

Fire GET requests to log Events. Events can be optionally tagged with Dimensions, which are like properties (and can be nested!), and each Event has some Metrics, or measurable counting data.

For example, let's say you need to count today's revenue from various income streams and put a fancy graph in your admin panel. From the proper points in your sales and services software, you insert HTTP calls to send Events like these:

# Sold $200 in services
http://.../count?dimensions=services&metrics={"dollars": 200} 
# Bought $2000 in advertising
http://.../count?dimensions=advertising&metrics={"dollars": -2000} 
# Sold a $product_id for $500
http://.../count?dimensions={"sales": $product_id}&metric={"dollars": 500}

Notice that in the third example, the dimensions are nested. Now, using the jQuery widget, you can add a graph to your admin panel that will show "Overall Dollars", as well as any dimensions that exceed 10% of the total revenue stream (10% is the default threshold). Additionally, you can get a graph of "Sales Overall", which would also show any $product_id that represented 10% or more of the sales. More additionally still, you can get a graph of the average revenue per sale, because hailwhale adds an extra metric {hits: 1} to each event. Since hailwhale lets you perform transformations on metrics in real-time, graphing e.g. the click-through ratio on a page is as simple as tracking pageviews with one metric, and clickthroughs with another

For each dimension/metric combination, hailwhale provides graphs (flot) and summary data, at whatever roll-up intervals you want, via HTTP/JSON or with the provided jQuery plugin.

On the backend, Hailwhale is composed of two servers --

• The hail server is optional, and designed to quickly collect incoming events in high-traffic scenarios. Hail depends on Redis and Bottle.py.
• The whale server is required. It provides graphs, and allows for directly counting data when used without a Hail server. The whale stores data into a large datastore. Currently Redis is supported, MongoDB and cassandra coming soon.

Currently only tested on my macbook pro and Ubuntu servers. OSX:

brew install redis
git clone git://github.com/linked/hailwhale.git
cd hailwhale
sudo python setup.py
python hailwhale/wsgi.py

Ubuntu 11.10:

sudo apt-get install redis
git clone git://github.com/linked/hailwhale.git
cd hailwhale
sudo python setup.py
python hailwhale/wsgi.py

Ubuntu 10.04 i386:

wget -O redis.deb http://ftp.us.debian.org/debian/pool/main/r/redis/redis-server_2.4.5-1_i386.deb
wget -O libjemalloc-dev.deb http://ftp.us.debian.org/debian/pool/main/j/jemalloc/libjemalloc-dev_2.2.5-1_i386.deb
wget -O libjemalloc1.deb http://ftp.us.debian.org/debian/pool/main/j/jemalloc/libjemalloc1_2.2.5-1_i386.deb
sudo dpkg -i libjemalloc1.deb
sudo dpkg -i libjemalloc-dev.deb
sudo dpkg -i redis.deb
# Continue 11.10 instructions

Ubuntu 10.04 amd64:

wget -O redis.deb http://ftp.us.debian.org/debian/pool/main/r/redis/redis-server_2.4.5-1_amd64.deb
wget -O libjemalloc-dev.deb http://ftp.us.debian.org/debian/pool/main/j/jemalloc/libjemalloc-dev_2.2.5-1_amd64.deb
wget -O libjemalloc1.deb http://ftp.us.debian.org/debian/pool/main/j/jemalloc/libjemalloc1_2.2.5-1_amd64.deb
sudo dpkg -i libjemalloc1.deb
sudo dpkg -i libjemalloc-dev.deb
sudo dpkg -i redis.deb
# Continue 11.10 instructions

Ubuntu:

pip install supervisor
sudo vim /etc/supervisord.conf
ADD THESE LINES, TWEAK TO FIT:
  [program:hailwhale]
    command=/usr/bin/python /path/to/hailwhale/hailwhale/wsgi.py
    numprocs=1
    user=www-data
    autostart=true
    autorestart=true
    stdout_logfile=/var/log/hailwhale.log
    redirect_stderr=true
    startsecs = 5
    stopwaitsecs = 5

Done :) if port 8085 is exposed, you can access hailwhale from it. If 8085 is not exposed, you should setup a local reverse proxy. I like to use the following nginx config inside my server {} block:

upstream hailwhale {
    server 127.0.0.1:8085 fail_timeout=1;
}
server {
    listen 80; 
    server_name  hw.lwb.co;
    proxy_redirect off;
    location / { 
      // Fix the host name for hailwhale
      proxy_set_header Host $host;
      // Sites you want to be able to include cross-domain hailwhale graphs from
      proxy_set_header Access-Control-Allow-Origin http://hw.lwb.co;
      proxy_set_header Access-Control-Allow-Origin http://lwb.co;
      // If you set too many sites above, you have to increase these numbers below
      proxy_headers_hash_max_size 1024;
      proxy_headers_hash_bucket_size 256;
      proxy_pass http://hailwhale;
      break;
    }   
 }

I built this after studying a presentation on Rainbird by Brian Weil (of Twitter), and re-using a lot of recent work I've done in parameterized hit counting.

Full credit to Twitter for the inspiriation, and my project name (a pun on both the name "Rainbird" and their classic downtime logo).

Rainbird looked awesome I knew I had to have it, but after 5 months of waiting on release, I proceeded to roll my own solution. Now I can count things at webscale without losing my mind, if you know what I mean.

I'm using this in production at http://series.oftubes.com which is still pre-beta. In addition to benchmarks, I'm trusting it to count my own live data for a (unrelated) marketing campaign, and it's good enough for me. Use at your own risk.