Re: IBM in talks to buy Sun

Tom Anderson wrote:
On Fri, 20 Mar 2009, Larry K. Wollensham wrote:
Lew wrote:
John B. Matthews wrote:
Larry K. Wollensham wrote:
That's in the form of separate 1TB disks without RAID, though. I expect* 14TB of RAID will top $10,000. That's still peanuts compared to a big company's IT budget, and still less than adding one vehicle to their motor pool.

Are you pricing high-reliability, 10K+ RPM SAS or SATA drives with large RAM buffers in a rack-mount format?

A 14 TB SATA system is roughly $21.8K plus maintenance. Call it $1,500 per TB, not including further costs.

Roughly twelve grand (plus maintenance) for 12 TB, and that's only 7200 RPM SATA. Call it $1,000 per TB, not including further costs.

One thing big-iron shops avoid is consumer-grade hardware.

That might change when they do the math.

To compensate for slower speeds, double the number of file servers behind a load-balancer, and ultimately the number of disks. This works as long as you don't need to serve *single* files *really* fast.

To compensate for lower reliability (but consumer grade hardware is getting better), assume a doubled disk replacement rate in the RAIDs.

Overall, that means four times the disks. If they're $200/TB each the above doublings produce $800 in place of the $1000-1500 you cite for the non-consumer-grade hardware.

Parallelism in various forms (multiprocessors, load-balanced clusters, RAID, and so forth) make consumer grade hardware able to "add up" to be equivalent to higher-grade hardware. Sometimes still with lower price tags.

If anyone still isn't persuaded by Larry's argument, they should consider Google. And i don't mean go and do a search. Google run their data centres in exactly this way, using vast amounts of cheap commodity hardware. It's an approach that doesn't work at the small scale, where a single better machine plus operating costs may well work out cheaper than two or more cheaper, less reliable ones, but at the large scale, it works out very well indeed.

Google uses that paradigm.

But:
- Google has its own file system, its own web server and its own
back end apps to manage it
- Google usage pattern is different from most OLTP usage

The Google case proves that it can be a good solution.

It does not prove that it will always be a good solution.

I find it difficult to see a traditional eCommerce Java EE
app with a relational database at the back utilizing that model.

Arne

.

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