Applications servers, databases, storage servers, and cache etc. are all pretty much spread and segregated all over the world. Resources could be located among servers in different data centers, regions, states, countries or continents. If apps are tightly coupled to each other, Outage in one place could disastrously slow down complete or partial business operations. Also, lossy message communication could leave data inconsistent and/or unusable across apps.

1. Queue centric pattern
In a Queue centric pattern, we focus on solving speed and
safety problems using multiple queues.
Worker processors at each level pick a message, processes
it and drops it into next bucket on completion.
Failures during the processing will prompt for another trial;
eventually pushing onto the next bucket.

3. Advantages
Worker processors at each level pick a message, processes
it and drops it into next bucket on completion. Failures during
the processing will prompt for another trial; eventually
pushing onto the next bucket.
Such a containerization of message processing improves
speed and safety due to decoupled dependencies/resources,
permits retrial in the case of failures, and allows load leveling
to support throttling in the case of high volume.