Jul 7, 2009 by Sinclair Schuller
One topic that fascinates me is the discussion of commodity hardware. Recently, Abe Sultan, our VP of Engineering at Apprenda, spoke on a panel with a few other great folks regarding the topic of leveraging commodity hardware. People LOVE to talk about commodity hardware, but what does it really mean in the context of SaaS and SaaS enablement? Before understanding what it means, I think we really need to understand what the fuss over commodity hardware is, and what the landscape might look like.
First, let’s chat about commodity hardware in general. First, commodity hardware enables commodity computing. The basic idea is that we’ve moved away from supercomputers, or “scale-up” systems (i.e. throw more memory, CPU, and disk at a single physical box to make it better) and to a scenario where we can “scale-out” by adding more inexpensive physical units as a solution to scale problems. Normally, this is done as a reactive measure to a mounting scale problem. We see this in everything from plain old websites to SaaS architectures. As inbound load increases, we add hardware to resource pools thereby increasing capacity, we then load balance, and voila, all better! Interestingly, infrastructure as a service (dialing up raw resources like servers on EC2) makes this even more practical as a solution. It used to be that “commodity hardware” meant real iron, but now we can deal with this virtually and in an “elastic” fashion (the ‘E’ in ‘EC2′) We’ll categorize this reactive commodity-based measure as naïve scale-out. I don’t mean this in the pejorative, but rather in the formal sense; systematic scale-out of this type exploits coarse grained application level allocation and “bolts on” new capacity with the notion that any new capacity be only minimally aware (if at all) of the “old capacity” and the scale problem it is actually solving, hence the word naïve. Assuming that dynamic scale out needs are real enough to justify using cloud hardware (e.g. EC2, GoGrid), then we have an amazing tool to solve our problems.
Naïve commodity scale-out is amazingly powerful and has catalyzed web-scale operations, but is it the “end all” solution? Not even close. Commodity hardware, at least for most of computing, has allowed us to “back into” older software like RDBMS, traditional application servers (e.g. IIS, JBoss) and build certain types of software architectures in response to scale-problems. Realistically, however, it’s not terribly innovative on its own. What I find most intriguing is the “what’s next” discussion. If we look at the past few years, we should have good indication of what commodity hardware, and more specifically, commodity hardware in the cloud, is allowing us to do.
Let’s use Amazon as a focal point (for no particular reason other than they exemplify where some of the change is headed) When we first think of Amazon, we think of infrastructure as a service: raw servers via, EC2 and web scale storage via S3. But now, Amazon is starting to evolve. Recently, they announced Elastic Map Reduce, which is essentially a step up the stack to the algorithm layer made possible by the mass parallelization offered by commodity cloud hardware. In my opinion, we’re going to see a revolution where “the cloud” will no longer mean boring servers that can be “fired up” on command, but rather a whole array of tools like Elastic Map Reduce that are the software layers that expose commodity hardware’s real value. We even see this with our beloved SaaSGrid – rather than being a traditional “single server” or “single cluster” application server, SaaSGrid establishes a “fabric” across arrays of servers (commodity) and creates a unified hosting layer, allowing the applications it hosts to trivially leverage an expanse of servers. This is a great thing to see, given that the complexity of engineering software to actually leverage commodity hardware layers is a difficult thing to do correctly, and will open the door to a host of SaaS applications that weren’t physically or economically possible before.
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