Some possible approaches might include ongoing back-
ground synchronization of the data selected for workloads
initially moved to the cloud, enabling low latency access to
the data at the cost of some replication lag and data stor-
age. Another approach, under the right circumstances,
might be to completely migrate logical portions of the data
to the cloud, carving away some of the on-prem data grav-
ity, which would provide low-latency cloud-based access at
the cost of higher-latency, queries from on-premises. Once
again, Company C’s use case provides another example of
the need to creatively deal with data gravity challenges in
the context of hybrid cloud.
We have already established that for the foreseeable future,
hybrid cloud is a given for the majority of companies: Stay-
ing completely off the cloud is a no-go for most organiza-
tions, and immediate, fully realized cloud-native is usually
only an option for relatively young companies. So where
does this leave us?
When it comes to enterprise data designs, there simply is
no perfect overarching architecture that serves all princi-
ples and priorities. Instead, it is necessary to evaluate the
company’s goals and design solutions, in light of the ongo-
ing conflicting priorities presented by the higher-level archi-
tecture constraints imposed by business strategy.
In the end, there are two key guidelines that can help us
navigate the challenges presented by data gravity in the
context of hybrid cloud:
1. Every overarching enterprise data architecture sys-
tem requires a unique balance of data principle
tradeoffs
2. The primary drivers for achieving each enterprise’s
optimum balance of data principle tradeoffs are data
gravity and latency, measured against consumption
use cases
As your large enterprise navigates challenges from the per-
spective of your hybrid cloud posture, be sure to evaluate
your designs, vendors and architectures with these guide-
lines in mind. They should help you ask the right questions,
make better decisions and derive better value from your
data and analytics.
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