Right now this is more an invitation to discussion than a request.
What modeling techniques does a data engineer need and for what use cases? Does anybody do simulation before actually designing a system / solution? If yes: what are the tools / approaches?
Following potential use cases came to my mind:
logical planning: if one wants to build an app which solves real-world problems, one wants to understand that problems. To avoid forgetting about some aspects of the problems or to discover not obvious aspects, one can do real-world simulation. In Python there is a library called simpy. Does anybody have experience using it? Also, diagrams (e.g. UML) can be used to do logical modeling for almost everything: state diagrams, data flow, components etc.
behaviour of distributed clusters (databases): I saw the following tool https://github.com/domclick/tuchanka, which imitates failures of a cluster node, waits for recovery, fixes failed node and cyclically continue testing. Anybody doing smth similar?
communication, networking, latency: I don't have much experience working with real-time environments - what are the typical techniques simulating / modeling real-time connectivity issues? Does one do performance measuring with some small dataset, and then extrapolates the results, or are there any other approaches?
Right now this is more an invitation to discussion than a request.
What modeling techniques does a data engineer need and for what use cases? Does anybody do simulation before actually designing a system / solution? If yes: what are the tools / approaches?
Following potential use cases came to my mind:
Python
there is a library calledsimpy
. Does anybody have experience using it? Also, diagrams (e.g. UML) can be used to do logical modeling for almost everything: state diagrams, data flow, components etc.