Monkey Analytics Blog

You asked and we listened.  Preliminary support for sessions running The R Project code just went live.  And sorry, no we do not yet support CRAN installs - see our earlier post on the matter – but we will install whatever packages you request!

Monkey Analytics has achieved the trifecta – running the Matlab M language, Python, and The R Project all in the cloud.  Pretty darn cool toolbox if we do say so ourselves!

More to come later , but we wanted to get this early functionality out for you to play with and critique.  Enjoy!

At another user’s request, we have installed the Octave-Forge packages. We know many of you would like the ability to install packages yourself, but we don’t have a secure system to allow this yet (sorry – more details in our FAQ here).

In the interim, we will install packages for all users to use as part of our base computing package.  If your favorite package isn’t there, let us know and we’ll work to add it.

Keep hitting us up with the feature requests – and we’ll keep coming up with solutions so that you can compute away!

We launched a new feature last night – you can now upload your data files to the system. Have a favorite .wav file you’re crunching on? An image to process? Signed in users will notice a new link in the data section titled “Upload data”. Upload away!

We also have a ‘process’ for larger data sets – contact us and we’ll work to ftp / scp larger data sets directly into your Monkey Analytics user data area.  (Longer term plans should automate this, but at the current startup-stage, this solution works).

A few bug fixes too – not worth mentioning details, but we know some of you noticed glitches – we did too – and have worked to improve the product.

We love finding more bloggers talking about the potential for cloud computing with Matlab like computation.  Paul Gribble at GribbleLab has a post on high performance computing in the cloud where he details some of his computational requirements for arm simulations (24-36hr runs on whatever machines he can grab, 8-10 at a time max).

He also notes it would be cool if he could instead run many Amazon EC2 instances.  (And he can, see our earlier post).  But this clearly illustrates the problem – why should Paul have to beg borrow and steal computational resources when they already exist (and wouldn’t have to run overnight when the desktops aren’t otherwise in use, etc).

Paul’s commenters note that Amazon has limits to its scale, and 10k CPUs isn’t accessible anytime soon, but the principle is sound and we’re here to help Paul and others with similar needs get there simply and quickly.

If you search for cloud matlab you’ll find result #2 is the following question on Matlab’s help pages:

Can MATLAB take advantage of a cloud computing service… ?

This states that it is possible to run Matlab on Amazon EC2, and if you share name, phone, email, and more they’ll share this whitepaper with you detailing how to do it (it sounds complex but feasible).  Note that the paper is written for system administrators, not users.

Really, MathWorks – do you think the majority of your users actually want to setup their own Amazon EC2 instances, generate their own AMIs, manage their own backups at yet another location, and then purchase additional *expensive* Matlab licenses for the pleasure of all this?

To reiterate our raison d’etre – we think not.  We think professionals (such as ourselves) are annoyed whenever system administration, complexity, and cost stand in between us and our important algorithms, experiments, and computations.  We think professionals want a service like Monkey Analytics that delivers scalable computation in a box.  (We also think they want cloud features, not thick client software, but maybe that’s a generational thing).

We’re here, we’ve launched, and we believe in what we’ve built.  Come take a look and see if you don’t agree.  Let us know either way!

Now that we are live, we are starting to join the many discussions about how engineering / math / science computation will change as the benefits of the cloud have become apparent.  Two bloggers we’ve been following – Krishnan Subramanian and Hans Gilde – have both written about the topic.

Krishnan’s original post at CloudAve – MATLAB on Clouds – mentions a whitepaper describing how individuals could run MATLAB in Amazon’s cloud.  Very cool stuff, however this still requires that (a) you obtain an (expensive) MATLAB license, and (b) you also maintain your own Amazon cloud machines, storage, and payment account.  Not very convenient if you just want to get some computing done inexpensively while benefitting from the cloud.

Hans’ picked up the theme with his post on Matlab, Mathematica in the Cloud – echoing the strong user demand for such abilities, looking forward to R joining the discussion (as do we – if you want R, let us know… we’re still figuring out which computational engines to add next).

These are but two of many interested professionals who see the need we saw.  We think that cloud customers want more than just the ability to roll their own computation system – at the companies we worked at, much overhead was spent on managing the computation systems as opposed to actually doing computations.  True cloud computing abstracts the underpinnings and exposes what users truly want – instant access to features while removing the annoyance of running your own servers and managing your own data.

Monkey Analytics truly delivers Matlab in the cloud.  And we’re joining the discussion so that we can spread the gospel.  Feel free to join our part of the discussion here in the comments!

Rocket Monkey TM

(Update 1: now that we are launched, our about page addresses this too)

(Update 2: SeeMonkey has officially launched as well – DIY Photobooth)

We are Team Rocket Monkeys.  And we are building Monkey Analytics.  (As you can tell, we’re into monkeys).  James Yoneda is the original Rocket Monkey, which was just a fun domain he snatched up back in the wild west of the web.  Since then he’s become a successful freelancer, and we’ve become good friends.  We have lots of plans for projects to build out of our dev shop, but initially we are focusing on two – this one (Monkey Analytics) and a DIY Photobooth that James built for his wedding and is productizing.

I have been pushing hard on Monkey Analytics, but have recently taken a slight breather.  And I thought I’d share why – I just gave birth to my second child.  Love the children, love the time with them, but definitely puts a cramp in the startup style.  We’re getting there though – all back end code is complete, we are just refining the user interfaces.  (No sneak previews though – (1) not quite pulled together enough yet, and (2) we’re still in stealth mode).