In " Conferences "
It’s been an exciting time for DNAnexus since launching our company at the recent Bio-IT World Conference & Expo in Boston. We’ve spoken with many of you about your experience using DNAnexus and received great feedback, much of which is already finding its way into future releases.
One thing that struck us at Bio-IT World was the pervasiveness of “cloud”: talks filled with discussions about experimenting with cloud, vendor exhibits praising the magic of the cloud, an entire pre-conference workshop dedicated to cloud computing, and a keynote presentation describing the awesomeness of Amazon Web Services by Deepak Singh. It seems the NIH is also aware of this trend, as the NHGRI recently held a workshop in DC to bring together researchers and thought leaders to discuss the impact cloud will have on genome informatics. One year ago, “cloud” wasn’t on the tip of everyone’s tongue like it is today. So is the excitement over cloud mostly hype?
There is certainly skepticism out there, and plenty of negative experiences. Vivien Marx wrote a great story in BioInform (Full disclosure: we were interviewed for the article) highlighting the ongoing debate over cloud computing, and gives examples of real problems people in the field have experienced. The challenges of using cloud are of course not unique to computational biology, and have been discussed for years, for example in this excellent report from the UC Berkeley RAD lab. The term “cloud” conjures up concerns about data transfer issues, security and control, platform lock-in, difficulty managing amorphous compute resources, the reliability of those resources, and over-crowding.
To address this skepticism, let’s first agree upon what we mean by “cloud” because the term is used by some to describe anything that runs in your web browser, while to others it’s just a fashionable marketing tool for IT infrastructure. Our definition for cloud is an elastic and scalable infrastructure for compute, storage, and networking. Elastic means that we can grow or shrink our use of those resources at any time. Scalable means there’s always room to grow your infrastructure. These two traits of cloud computing are incredibly powerful: Do you have 100 jobs to run? Launch 100 compute nodes and run them all in parallel. Pay the same as running them in a serial fashion, but finish in 1/100th the time. Need to store 10 Terabytes of data for a 6-month project? No problem, it’s available, just pay for 60 TB-months of storage. And when the day comes that you need to run 10,000 compute nodes or store 10 Petabytes of data, you don’t have to worry about building out a datacenter – the cloud will scale to those levels!
But as others have said, the cloud is not a utopia. It doesn’t magically support sequence analysis. It can be difficult to use, and your old applications generally won’t run in the cloud. But that’s because the cloud is not a solution in and of itself. It’s an infrastructure, or an engine that you can use to power your applications. And even if the cloud is like a super-charged V12 engine, it won’t take you anywhere by itself. To harness that energy you need to build a vehicle around the engine: the chassis, transmission, wheels, brakes, and steering wheel and console to present a user-friendly interface to the driver. Once you’ve built the car around the engine, suddenly it’s easy to use and hugely enabling.
DNAnexus’ use of the cloud mirrors this: we’ve built a web-based platform on top of the cloud to harness its power. All the sequence analysis and data management tools are available to you through your web browser, and we transparently manage all the cloud resources. Moving data around the cloud, figuring out where and how to store it reliably, launching compute nodes and coordinating their work – all this happens below the surface. We present an intuitive interface to you that removes all the challenges of using the cloud, while passing through all the benefits – tremendous scalability on-demand. Is it possible to build it without the cloud? Yes, but we wouldn’t be able to amortize the infrastructure costs over the thousands of people working with similar data. We wouldn’t be able to charge you a low per-sample cost.
So to answer the question: revolutionary or hype? It’s both. There’s a lot of hype, and as a result there’s understandably skepticism and disappointment. But once you go beyond that and look at the technology it enables, it’s truly revolutionary. DNAnexus’ goal is not to promote the hype. Our goal is to solve the next-gen sequencing data bottleneck. And we happen to use the cloud as a key component of our platform to solve it. As sequencing growth continues to outpace Moore’s law, you can be sure that your need for compute infrastructure will grow tremendously. We’re here to make that growth as painless and cost-effective as possible.