This is a continuation of the earlier posts starting with this one: http://ravinote.blogspot.com/2020/09/best-practice-from-networking.html
Sometimes the trade-offs are not even from the business but more so from the compliance and regulatory considerations around housing and securing data. Public cloud is great to harness traffic to the data stores but there are considerations when data must be on-premise.
Customers have a genuine problem with anticipating growth and planning for capacity. The success of an implementation done right enables prospect but implementations don’t always follow the design and it is also hard to get the design right.
Similarly, customers cannot predict what technology will hold up and what won’t in the near and long term. They are more concerned about the investments they make and the choices they must face.
Traffic, usage and patterns are good indicators for prediction once the implementations is ready to scale.
Topology changes for deployment of instances are easier to manage when they are part of a cluster or a technology that allows elastic growth. This is one of the reasons why public cloud is popular. The caveat with initial topology design is that it is usually a top-down approach. Findings from bottom-up studies will also help here.
There is necessity to classify and segregate traffic in order to get more efficiency from the resources. Data is not all the same in transit but there is no classification in terms of quality of service either. Only the production support folks know the data flows and then these can be better streamlined for high performance and availability.
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