**Compute Cycles** is a concept for standardization of unit of cloud computing usage consumption introduced first by Rackspace. Let us go deeper in Compute Cycles. Apparently, Compute Cycles has not been accepted universally. Let us see the basic concept of Compute Cycles, as it has the promise of at least being a precursor to a standard measurement.

## What is this Compute Cycles in Cloud Computing

As per The Rackspace Cloud, Compute cycles measure how much processing time your applications require on The Rackspace Cloud. Using 10,000 compute cycles in a month is roughly equivalent to running a server with a 2.8 GHz modern processor for the same period of time. 10,000 compute cycles is closely equivalent to 25 million requests for a static 15KB image.

### Points in favor and against such measurable unit like Compute cycles

In 2005, these were published, “but as I wrote earlier this week, an industry standard definition of CPU per hour usage doesn™t exist. There is no equivalent to kilowatt hours or the price of a barrel of oil for CPU usage. It™s some combination of hardware, Solaris 10, memory, a grid engine, storage, and whatever else goes into enabling grid nodes to be used with minimal hassle.”

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It is quite obvious, the above statement of the author, is kind of “I think its true, so it is true”. Kindly note it is not specifically about (or against) Compute Cycles itself, it is about CPU per hour or rather an an unit of measurement, which Compute Cycles also is. The statement is just bogus as simply with his / her logics, we can not define mileage of a car – is not it ? Obviously a modern car has more complex units than a server.

I am not saying that Compute Cycles is perfect, *Compute Cycles* as an unit probably never has been undergone standardization tests to make it as an universal unit of Cloud Computing. But Compute Cycles like idea is quite appreciable as it directly points out – if you can reduce the size of webpage, your Compute Cycles and webpage speed both will be reduced.

So, Compute Cycles becomes –

1 2 3 4 5 6 | Compute Cycles = k {(a x n0) + (b x n1) + (cxn3) + ... upto nth} / unit time # Where, # k= constant for a particular generic system neutralizing the known issues. # a, b, c ... = units consumed against physical units of n0 to nth value. # n0, n1, n2, n3 ... = Physically measurable units |

For example, no in Compute Cycles can be number of database tables or queries. Quite obviously, from my practical experience with Compute Cycles, if the database is cached (in WordPress), the growth of Compute Cycles is reduced. On the other hand, with proper HTML caching plus database caching, Compute Cycles do not increase significantly with the number of pageviews. Quite obviously, if we use CDN, Compute Cycles tends to decrease.

Quite obviously, Compute Cycles should have a null point. It has.

For a domain with almost zero visitors and no database, Compute Cycles remains as zero. Practically we can apply Newton’s Second Law too :

If applied to an object with constant mass (dm/dt = 0), the first term vanishes, and by substitution using the definition of acceleration. This is what we all know. So, in other words, Compute Cycles is the force that was used to drive a webpage or anything equivalent from the server side.

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