On Noah Part 3

This is the third part in a series on Noah. Part 1 and Part 2 are available as well

In Part 1 and 2 of this series I covered background on Zookeeper and discussed the similarities and differences between it and Noah. This post is discussing the technology stack under Noah and the reasoning for it.

A little back story

I’ve told a few people this but my original intention was to use Noah as a way to learn Erlang. However this did not work out. I needed to get a proof of concept out much quicker than the ramp up time it would take to learn me some Erlang. I had this grandiose idea to slap mnesia, riak_core and webmachine into a tasty ball of Zookeeper clonage.

I am not a developer by trade. I don’t have any formal education in computer science (or anything for that matter). The reason I mention this is to say that programming is hard work for me. This has two side effects:

So in the interest of time, I fell back to a language I’m most comfortable with right now, Ruby.

Sinatra and Ruby

Noah isn’t so much a web application as it is this ‘api thing’. There’s no proper front end and honestly, you guys don’t want to see what my design deficient mind would create. I like to joke that in the world of MVC, I stick to the M and C. Sure, APIs have views but not in the “click the pretty button sense”.

I had been doing quite a bit of glue code at the office using Sinatra (and EventMachine) so I went with that. Sinatra is, if you use sheer number of clones in other languages as an example, a success for writing API-only applications. I also figured that if I wanted to slap something proper on the front, I could easily integrate it with Padrino.

But now I had to address the data storage issue.


Previously, as a way to learn Python at another company, I wrote an application called Vogeler. That application had a lot of moving parts - CouchDB for storage and RabbitMQ for messaging.

I knew from dealing with CouchDB on CentOS5 that I wasn’t going to use THAT again. Much of it would have been overkill for Noah anyway. I realized I really needed nothing more than a key/value store. That really left me with either Riak or Redis. I love Riak but it wasn’t the right fit in this case. I needed something with a smaller dependency footprint. Mind you Riak is VERY easy to install but managing Erlang applications is still a bit edgy for some folks. I needed something simpler.

I also realized early on that I needed some sort of basic queuing functionality. That really sealed Redis for me. Not only did it have zero external dependencies, but it also met the needs for queuing. I could use lists as dedicated direct queues and I could use the built-in pubsub as a broadcast mechanism. Redis also has a fast atomic counter that could be used to approximate the ZK sequence primitive should I want to do that.

Additionally, Redis has master/slave (not my first choice) support for limited scaling as well as redundancy. One of my original design goals was that Noah behave like a traditional web application. This is a model ops folks understand very well at this point.


When you think asynchronous in the Ruby world, there’s really only one tool that comes to mind, EventMachine. Noah is designed for asynchronous networks and is itself asynchronous in its design. The callback agent itself uses EventMachine to process watches. As I said previously, this is simply using an EM friendly Redis driver that can do PSUBSCRIBE (using em-hiredis) and send watch messages (using em-http-request since we only support HTTP by default).


Finally I slapped Ohm on top as the abstraction layer for Redis access. Ohm, if you haven’t used it, is simply one of if not the best Ruby library for working with Redis. It’s easily extensible, very transparent and frankly, it just gets the hell out of your way. A good example of this is converting some result to a hash. By default, Ohm only returns the id of the record. Nothing more. It also makes it VERY easy to drop past the abstraction and operate on Redis directly. It even provides helpers to get the keys it uses to query Redis. A good example of this is in the Linking and Tagging code. The following is a method in the Tag model:

	def members=(member)
	  member.tag! self.name unless member.tags.member?(self)

Because Links and Tags are a one-to-many across multiple models, I drop down to Redis and use sadd to add the object to a Redis set of objects sharing the same tag.

It also has a very handy feature which is how the core of Watches are done. You can define hooks at any phase of Redis interaction - before and after saves, creates, updates and deletes. the entire Watch system is nothing more than calling these post hooks to format the state of the object as JSON, add metadata and send the message using PUBLISH messages to Redis with the Noah namespace as the channel.

Distribution vectors

I’ve used this phrase with a few people. Essentially, I want as many people as possible to be able to use the Noah server component. I’ve kept the Ruby dependencies to a minimum and I’ve made sure that every single one works on MRI 1.8.7 up to 1.9.2 as well as JRuby. I already distribute the most current release as a war that can be deployed to a container or run standalone. I want the lowest barrier to entry to get the broadest install base possible. When a new PaaS offering comes out, I pester the hell out of anyone I can find associated with it so I can get deploy instructions written for Noah. So far you can run it on Heroku (using the various hosted Redis providers), CloudFoundry and dotcloud.

I’m a bit more lax on the callback daemon. Because it can be written in any language that can talk to the Redis pubsub system and because it has “stricter” performance needs, I’m willing to make the requirements for the “official” daemon more stringent. It currently ONLY works on MRI (mainly due to the em-hiredis requirement).

Doing things differently

Some people have asked me why I didn’t use technology A or technology B. I think I addressed that mostly above but I’ll tackle a couple of key ones.


The main reason for not using 0mq was that I wasn’t really aware of it. Were I to start over and still be using Ruby, I’d probably give it a good strong look. The would still be the question of the storage component though. There’s still a possible place for it that I’ll address in part four.


This was something I simply had no idea about until I started poking around the CloudFoundry code base. I can almost guarantee that NATS will be a part of Noah in the future. Expect much more information about that in part four.


You have got to be kidding me, right? I don’t trust my data (or anyone else’s for that matter) to a product that doesn’t understand what durability means when we’re talking about databases.

Insert favorite data store here

As I said, Redis was the best way to get multiple required functionality into a single product. Why does a data storage engine have a pubsub messaging subsystem built in? I don’t know off the top of my head but I’ll take it.

Wrap up - Part 3

So again, because I evidently like recaps, here’s the take away:

If you haven’t guessed, I’m doing one part a night in this series. Tomorrow is part four which will cover the future plans for Noah. I’m also planning on a bonus part five to cover things that didn’t really fit into the first four.