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August 31, 2011

StackIQ Widens Net

Steve Campbell

Continuing adventures in San Diego led me to StackIQ to meet with President and Co-founder Tim McIntire. Many of you will know StackIQ by their original name Clustercorp and the highly successful HPC cluster management suite Rocks.

Rocks was first developed at UCSD, circa 2000, and over a ten-year period, there are over ten thousand Rocks clusters worldwide. Many in traditional HPC environments but also growing installed base in the enterprises such as Aerospace, Automotive, Oil and Gas.  The one thing in common is managing large cluster installations in environments generating and processing vast amounts of data.

It is clearly an exciting time for StackIQ; a new name, new funding in place, new location and two of the original Rocks co-founders Greg Bruno and Mason Katz recently joining the team full time. More importantly, however, is the growing list of new customers for Rocks in their traditional HPC community and growing commercial enterprise installed base.

StackIQ is seeing growing acceptance in the new market segments of big data and naturally cloud computing. Recent alliances with Amazon for a port of Rocks to EC2 together with a recently announced OEM relationship with Amazon. In addition, their HPC expertise and heritage is well suited to Big Data solutions such as Apache Hadoop, Cassandra and others.  Rocks enables Hadoop clusters to be deployed in fraction of the time compared to conventional methods, StackIQ put a lot of emphasis on the ease of use and ease of deployment.

HPCc: You recently changed the company name from Clustercorp to StackIQ.  What’s behind the name change?

McIntire: Many people associated our previous name exclusively with High Performance Computing  (HPC). We wanted to change our name to better reflect what we do, which is to apply a decade of cluster computing expertize and experience to full-stack enterprise automation.
 
HPCc: I heard you also closed a round of financing.  Was this a private round or VC round and what can you tell me about it?

McIntire: It was a VC round, Series A. We secured the funding we needed to take the company to the next level by bringing in the resources to address the cloud and big data markets. We are very excited to be working with both Avalon Ventures and Anthem Venture Partners.
 
HPCc: How do you plan to spend the dollars raised?

McIntire: Some of it is focused on accelerating product development in the cloud and big data market segments while maintaining our leadership position in HPC. Some is earmarked to help us get our message out. We’ve been quite fortunate in building a strong community in the HPC space, but we need to let people outside of HPC know how much easier things are when you use Rocks+ to deploy and manage their servers.
 
HPCc: When I look at your website it is very clear that you have three distinct yet related segments, Clouds, Clusters and Big Data?  Starting with Clouds what is the plan?

McIntire: I’m glad you asked. Rocks is a horizontal platform for building out scalable solutions, but one of the things that made Rocks so successful in the cluster space was its ability to nail down a vertical solution (HPC) into a single, integrated stack. Open Source Rocks provided the first turnkey downloadable cluster ISO that allowed anybody — even researchers with little to no system administration experience — to build and manage a supercomputer.  

We are approaching the Cloud and Big Data verticals with the same strategy. You’ll notice that there is a complete downloadable stack for each of the segments on our website, so aspiring cloud and big data administrators can leverage the same simple turnkey solution we offer for HPC community. In addition, it’s free to use for clusters of up to 16 nodes.
 
HPCc: What about HPC clusters?

McIntire: Our roots are in HPC, and we’re proud of our position as the market leader in the HPC cluster management space. We are actively developing our HPC product line, and remain committed to delivering the best-of-breed cluster management solution for open source and commercial users.
 
There is a growing discussion of Big Data. What is your vision and why is this important to StackIQ and why is it such a hot topic in the world of data management?

The need to extract value from ever-growing volumes of both structured, and unstructured data is very real, and represents a tremendous business opportunity.

Apache Hadoop is a powerful, accessible open source tool that many are turning to, and at the heart of every Hadoop solution lies a high-performance cluster. Our HPC heritage puts us in the perfect position to bring best-of-breed technology to the foundation of Big Data solutions such as Apache Hadoop, Cassandra, and others. By laying the foundation of a rock-solid, predictable, reliable cluster at the base of each big data installation, Rocks+ leaves our customers free to focus on the business problem they’re trying to solve. Using conventional methods, building a working Hadoop solution can take weeks or months. Using our products, customers can bring up their Hadoop cluster in minutes.

HPCc: What’s the intersection of Big Data with Cloud Computing?

McIntire: The most interesting intersection I’ve seen is Amazon’s Elastic Map Reduce (EMR). Here, you have a market leading public cloud provider with customers who are generating a tremendous amount of data in the cloud. Rather than making customers deal with the difficult problem of downloading their data to a Hadoop cluster for analysis, Amazon brought compute to the data. They now have a very strong position in the big data space.

HPCc: Speaking of Amazon, are you also working to solve management problems in public cloud?

McIntire: Yes, one of our first cloud projects was a deep port of Rocks to support Amazon EC2. In June, we announced that Amazon has OEM’d Rocks+ (in much the same way they’ve done with Red Hat Enterprise Linux and Microsoft Windows) and now offers Rocks+ as an instance type. Thanks to Amazon, administrators can use the exact same management tools in public clouds that they use in their own data center. This can be a tremendous advantage. For example, you could leverage EC2 for development and testing purposes, running our Hadoop Roll there, tweak it to suit your needs, or you might even develop your own Roll. Then, should you decide to move your project in-house for large-scale deployment, you could simply download your Roll as an ISO and do complete bare metal provisioning of an in-house private cloud. You’d even have the same automated check-box installation Rocks users have become accustomed to.  

HPCc: You have been very successful with Rocks in the traditional HPC market. Are you changing direction and going after the commercial enterprise and if so why?

McIntire: The customers for our Cloud and Big Data solutions are primarily enterprises, but we’ve already seen great penetration in the enterprise HPC space. Therefore, while we are indeed marketing to the enterprise, we don’t see it as a change of direction. It’s just the next step along the path we were already on — bringing the power of Rocks to everyone who needs it.

HPCc: Can you do both markets? Do you have resources people and funds for both?

McIntire: Yes, one of the neat things about Rocks is its modularity.  Much of the work we do is applicable to all three verticals, which gives us a multiplying effect on the development side. By combining our architecture, leveraging the funding we talked about earlier, and some incredible work done by our partner network, we have everything we need to get the job done.
 
HPCc: Who is your primary competition and why should potential prospect choose you?

McIntire: There is no other product that can spin up Clouds, HPC Clusters, and Hadoop Clusters with the ease and efficiency of Rocks+. However, we do run in to different companies in certain spaces. Fortunately for us, most of them are in the early days of discovering all the ins and outs of deploying and managing large groups of connected servers at scale.

What we’ve seen is that people can be fairly successful in building small-scale clusters using less powerful tools, but once they grow beyond the test and proof-of-concept stage, the processes they’d been using fall short. We recommend people start with the end in mind, and use a proven cloud and cluster power tool right from the start. We make that easy by offering it free for clusters up to 16 nodes.
 
HPCc: What is you product roadmap, what’s next?

McIntire: I don’t like talking too far into the future when it comes to product features, however, there are some key items that are under development now.

We have a project underway that will significantly improve the Rocks user interface. We are also broadening the Big Data product line to include Cassandra, and plan to add other Big Data services to that package in the future as well.

In the Cloud space, work is well underway on an OpenStack product, and we are adding new capabilities to our Amazon EC2 offering. We’re also pushing ahead on the open source Rocks project, and plan to contribute RHEL and CentOS 6 support soon.
 
What’s your go to market approach?

We have a three-pronged Go-to-market approach:

-Hardware partners resell our software stacks to their customers to go along with their servers. Our current partners include Dell and HP, who have both given us tremendous support considering our company size.  Amazon, while not a traditional hardware partner, also fits into this channel go-to-market strategy.

-We also have a strong ISV partner network — we realize that our customers have a wide breadth of needs — our strategy here has always been to be supportive, yet agnostic at the applications layer.  For instance in HPC, we have Rocks Rolls for

Adaptive Computing’s Moab, Univa Grid Engine, and Altair PBS Pro.  You’ll notice we are executing the same strategy in the Big Data space, as we’ve already rolled out support for Apache Hadoop, MapR, and Cloudera.  In the coming months, you’ll see this list continue to grow.

-Lastly, StackIQ works directly with a number of customers who have pre-existing hardware and/or heterogeneous data centers.  Direct customers are usually more on the hyper-scale end of the size spectrum.  

What are the big trends you are seeing and how do they impact your vision?

We see a continuation of the trend towards more data and more compute — clusters are now mission critical to enterprise.  StackIQ is in the unique position of participating in a leading edge market segment with a mature, robust software solution.