Hardware is Expensive, Programmers are Cheap

Isn't the real story of this "incompetence is expensive"? Seriously, that application design is worse than the worst implementation we've ever had in a failed outsourcing project. (I make Big Freaking Web Apps for Japanese universities at the day job.)<p>Up until recently universities pretty much had to overspend on hardware, though. (Virtualization/expandable-on-demand cloud computing may eventually get around to changing it, but the customers aren't ready for it and the programming costs to take advantage of it dwarf the benefits for our clients.)<p>Most of the important systems that need to scale have very, very bad usage patterns from a hardware buyer perspective: for example, take course registration. (Edit to clarify: They are probably not talking about course registration, because there is no way in heck that peak is only 50% more than the steady state.)<p>At a university with 10,000 students, about 360 days out of the year you can run the course registration on a laptop while it is being used to play World of Warcraft. Then there is course registration season, at which point your peak concurrency goes from 1 user per hour to generally a <i>multiple</i> of your student population all signed in at once. (Because, no matter what you do, they will open multiple windows/connections/etc because "the site is so slow, come on duuuuude, why the heck is this POS always so slow?")<p>All the accesses are dynamic. Most of them have writes attached. You have to get caching right because if you overbook a class and tell 15 students that they're confirmed a seat in a room which sits 12 because your cache got stale for three minutes, your customer gets yelled at, and they will turn around and yell at you. The end users are also typically incompetent at using the system (typically 1/4 of them have never used it before) and they will perform an impromptu fuzz test on it.<p>(Oh the stories I can't tell, sadly.)

Sometimes Hardware is Expensive, and so is time though.<p>I think often times in a startup, especially one thats bootstrapped, its easy to get caught up in trying to optimize everything too early on to scale for a million users before you have your first thousand. Sometimes you have to optimize for your development time first and product development goals, and leave the optimization till you get a bit of runway.

In other words, figure it out for yourself in your particular situation. Do the back of the envelope calcs. The reason why articles like this and the opposing view at Coding Horror are posted is because authors want to draw attention to management with preconceived notions.

Looking at things along the hardware/programmers are expensive/cheap axis (take your pick) is short sighted and highly subjective. Setting aside political considerations, the real thing decision makers should focus on are the organization's underlying time and efficiency constraints and unfortunately these things are most often overlooked, misunderstood or inaccurately represented.

This sounds like an edge case to me. Now that it's no longer 1998, most of us don't spec out $500,000 boxes for our stuff anymore. A $5,000 box will get you a long way for just about anything you need to do.<p>I suspect that the author is looking at a problem that would require tons of hardware regardless of how well it was optimized. Evidence of this can be found in the fact that even after tons of optimization, his $1.5M setup is still running at 20% load steady state.<p>Our single &#60;$5,000 box handles about 4M pageviews per day without moving the cpu above 5% steady state. That's the sort of baseline I'm used to from the Microsoft stack, so it causes me to question whether the author is really looking at a mainstream case.

This is not a problem of hardware vs software. It's a problem of vendor's money vs your own. Of course he doesn't care. Actually, the more you spend on hardware the cheaper the software seems.

there is a fundamental difference between software for sale and software as a service when it comes to this debate. the economic efficiency math is much different for licensed software because more than one company is using it.

Yeah, if you can make software run 100 times faster with lots of profiling and hand optimisations, that $300 laptop is basically a $30,000 laptop.

I think the problem is that the costs add up slowly. Your site starts getting slow? You just throw another dedicated server at it, increasing your cost 300-400 bucks a month.

Hm, why not find something to do with the remaining cycles?