Unit Safety
The recent spate of NASA upsets in the Martian environment reminds us that, in spite of the many “provable” (sez who?) advances in academic risk analysis and software development, our practical trade remains subject to the most bizarre glitches. Accidents, by definition, happen in all walks and trips of life, but once having happened, are revealed by post-hoc scrutiny to have been eminently, nay, trivially “preventable”. Next time, we boast, we'll avoid spilling the salt, we'll bypass the banana skin under the ladder and we'll secure the loose horseshoe that lost the last war. More space-age specifically, we'll watch out for inelastic rubber washers, shun rash global identifiers, and work around the quirks of FORTRAN FOR loops, all of which have proved to be life- and dollar-threatening.
Of course, digging deeper into fashionable post-Darwinian theory, we must acknowledge that “social evolution”, without which this column might have emerged as a mysterious henge in some foreign field, is due to a long sequence of fortuitous accidents. Random memic mutations, some say, guarantee the survival of fitter crania, neural paradigms, languages, algorithms and software engineering methodologies. Whether we consciously “learn” from our mistakes or not, some argue that there is an ongoing natural “self-correctional” process that converges to error-free nirvana. Fat chance! The optimistic concepts of “inevitable improvement” and “human perfectibility”, fashionable when the previous millennium started [see Note], are hard to relinquish, although the alternatives are so damned depressing, leading to a self-fulfilling why-bother apathy.
The challenge for historians is selecting and recording “significant” events. The so-called random elements (Luther's constipation, Napoleon's insomnia, Hitler's rejected watercolors...) seem to have a ridiculous, chaotic impact on the grand deéroulement. My favorite historian, Barbara Tuchman, warns against the post hoc contingent narrative, but it's impossible to feign ignorance of what happened next. What if, say, Saint Linus had wealthy parents like Bill Gates? What if he had not grown up in the fractal Swedish-Finnish isogloss?
One of the most expensive, embarrassing lessons from the missing Mars probe mishaps was the lack of “unit safety”. We've spent all these years ensuring type-safety (not to mention the oxymoronic thread-safety), whereby oranges and lemons cannot be added without deliberate, fruitless miscasting, yet it seems that a given floating-point value was interpreted as Newtons rather than pounds. Or vice versa. Or was it an understandable confusion between parsecs, meters, yards, chains, rods, perches and poles? We'll get it right next time, unless there are bright Martians anxious to resist our inferior technology.

Today’s modular x86 servers are compute-centric, designed as a least common denominator to support a wide range of IT workloads. Those generic, virtualized IT workloads have much different resource optimization requirements than hyperscale and cloud applications. They have resulted in a “one size fits all” enterprise IT architecture that is not optimized for a specific set of IT workloads, and especially not emerging hyperscale workloads, such as web applications, big data, and object storage. In this report, you will learn how shifting the focus from traditional compute-centric IT architectures to an innovative disaggregated fabric-based architecture can optimize and scale your data center.
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Most companies incorporate backup procedures for critical data, which can be restored quickly if a loss occurs. However, fewer companies are prepared for catastrophic system failures, in which they lose all data, the entire operating system, applications, settings, patches and more, reducing their system(s) to “bare metal.” After all, before data can be restored to a system, there must be a system to restore it to.
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