Buying reserved instances upfront does force one to
think through the capacity and usage required, but
let’s be honest, most enterprises are not very good
yet at predicting server capacity on the cloud and
properly utilizing it to get the most of it.
Needless to say, these convoluted price structures
are extremely confusing to customers and in dire
need of simplification.
The Shift in Thinking
After the all-out price cuts on servers ended, cloud
providers got a little more sophisticated. Now, instead
of simply cutting prices for your virtual instances per
hour, most vendors are trying to cut back on the
amount of time they charge you. Amazon recently
announced that it is moving to a per-second price
model. That move was quickly mirrored by Google a
week later.
This recent shift in pricing seems to be focused on
removing cloud adoption friction by minimizing the
need for upfront planning. This more flexible pricing
arrangement (sub-minute billing) for VMs is bringing
some parity to already existing serverless offerings
(Azure functions, AWS Lambda, Google Cloud Func-
tions), by allowing you to address your computing
needs while paying by the second (or even less at times).
This change is another great step in bringing the true
promise of cloud elasticity and “pay as you go,” versus
“plan a ton upfront and hope you get it right”. How-
ever, that still leaves us with the focus on buying serv-
ers by the hour or minute or second, and I think that’s
wrong. I am not saying that saving money is not
important–it most definitely is. But I am saying that
placing a focus on “look, now you pay for each second
used instead of each hour” doesn’t significantly
change things for an average enterprise, and dis-
tracts you from other more important aspects and
benefits of the cloud, such as agility, flexibility, fea-
tures and capabilities. I see this as more of a market-
ing gimmick to outshine other providers.
Let’s Count Peanuts
To support my assertion about “not significantly
changing things,” I’m going to use an AWS price
structure (US-East Ohio) for this exercise. However,
other cloud pricing could work here just as well.
Use Case 1: Let’s say you’re an average size com-
pany with a distributed set of applications (some
commercial off-the-shelf, some home-grown Java,
.NET, etc.), and have 1000 VMs in a public cloud. Most
of those VMs never stop, running continuously to
support your production. Let’s say you are also one of
those advanced companies who stop all their Dev/
Test machines every day at 7 PM and restart them at
7 AM, and they’re never up on weekends. Let’s further
assume that 70% of your virtual machines are dedi-
cated to your Dev/Test environment. So if your
Now, instead of simply cutting prices for
your virtual instances per hour, most
vendors are trying to cut back on the
amount of time they charge you.
28 | THE DOPPLER | WINTER 2018