Map-Reduce Capabilities and Super Easy Concurrency (via Alan deLevie and IronResponse)

We came across a great contribution the other day from Alan deLevie that makes using IronWorker for a map-reduce pattern even easier than it already is. (Love seeing tweets announcing additions to the growing list of Iron.io community addons.)

I just wrote a gem that lets you write map-reduce style code using @getiron: https://t.co/49DNyLrXey. Makes Ruby “concurrency” super easy!
— Alan deLevie (@adelevie) August 9, 2013

IronWorker is a cloud-based on-demand service that out-of-the-box lets you do massively concurrent processing across slices of data – which is essentially the core of the map reduce pattern. (Here’s a good visual explanation of map reduce in action.) Continue reading “Map-Reduce Capabilities and Super Easy Concurrency (via Alan deLevie and IronResponse)”

Relify adds IronWorker to their Stack ➞ Ridiculously Simple Worker Scalability

Relify, a Recommendations as a Service engine, is one of the really cool customers that Iron.io serves. They offer a simple API that eliminates the complexity of developing a recommendation engine –which means you can greatly increase your relevance to your users.

Terry Horner is the Co-Founder and CEO of Relify. A recent blog post of his details their use of a scale-out processing pattern that, in concert with IronWorker, allowed them to significantly scale their recommendations service. All in a short period of time without any infrastructure or much cost.
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ProQuest’s Scalable, No Maintenance Cloud Stack

ProQuest chose IronMQ as a key part of their stack while building the website for WorldRiderz, a documentary on the Discovery Channel. They needed a robust, elastic and scalable architecture. Due to the nature of the project, traffic was always going to be patchy, with periods of heavy traffic, followed by idle periods, so controlling costs and being able to scale quickly was important. IronMQ was used to free the front end Heroku dynos from any heavy back end processing, essentially decoupling the front end from the back end.
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Guest Post: Using IronCache as a Persistent Key Value Store for Real-time Chat

While IronCache is a great option for caching, it can also be used to persist data more permanently. There are dozens of great uses for a persistent key/value store, however, we’ll be building a simple chat app with Sinatra using IronCache as our datastore.

This is a guest post by JP Silvashy, CTO of Motionloft. You can find him on Twitter or his blog.
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Guest Post: Iron.io + Team Healthify = Hacking Change in Healthcare

Sabrina Atienza and George Ramonov are emerging experts in the areas of big data and healthcare information. This is their story from xHack 2012, a hackathon sponsored by RadiumOne and via.me. 

Hello world, we’re two aspiring hackers from UC Berkeley: Sabrina Atienza and George Ramonov. We comprised Team Healthify at xHack 2012 held this past June. 
From the start, we were prepared to fulfill the stereotype of Berkeley crazy. Our vision for the hackathon appeared overly ambitious, borderline insane for only twenty-four hours, a likely dysfunctional mess, doomed to elicit a few chuckles at best.
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