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resources at massive scale than in eliminating workloads based on
technology choices.
Deployment Scorecard
So what have we learned? See
Figure 2.1
.
Figure 2.1
The deployment scorecard
We've learned that some of this is relative. Security, for example, is not
a great situation for any option, because it is not a strength of Hadoop.
Likewise, proximity depends on where the data is actually born. When data
is born in the cloud, proximity of cloud offerings would be better (assuming
the same service provider was used). However, for proximity I've scored
this based on a more general ability to integrate with other disparate data
sources throughout out an enterprise. At the time of this writing, the
majority of this kind of enterprise data sits on premise, which explains the
scoring.
Cloud deployments work well for the following:
• Elastic scale
• Kicking the tires
• Prototyping
On our scorecard, shown in
Figure 2.1
,
what shines through is that the
cloud offers that elusive flexibility and elastic scale that encourages
experimentation and works brilliantly for “bursty” workloads. However,
unless the data is consistently being born in the cloud (a mighty big
if
),
