The Right Data in the Right Place
So far, we have assumed that we are going to be replicating
our entire data estate in all the places where we have appli-
cations. In some scenarios, this may be the best (and only)
option. However, with careful planning and potentially some
changes to our applications and their interactions, we can
take a more efficient and effective approach.
Many organizations have application sets that can work
independently with regard to their associated data. As we
move closer and closer to a microservices architecture, we
want that independence in order to achieve the agility and
functional isolation that microservices offer. But even prior
to achieving microservice nirvana, we probably have appli-
cations that only need to update other data sets infre-
quently and with small amounts of additions and updates.
Consider a scenario where we have applications in one pub-
lic cloud which primarily do data analytics for operational
capabilities like machine learning. It is entirely probable that
the majority of the data required will stay resident within
that cloud provider, with new data being added from exter-
nal sources (ingress). The results from the machine learning
models could be fed to other clouds or back to the on-prem-
ises environment in small chunks, avoiding large costs and
other factors such as latency.
Public Internet
Premise Data Center
Figure 6: The right data in the right place, multicloud approach
64 | THE DOPPLER |
SPRING 2019
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