How to use probabilistic inference programming for application orchestration in serverless architectures

" summary

Describes using probabilistic inference programming to orchestrate typed functions in serverless systems, comparing it to patterns like function chaining, rollback transactions, async HTTP, and fan-out. Names IBM OpenWhisk (action chaining/composites) and AWS Step Functions as existing tools, and presents an alternative approach that combines features of decision trees, state machines, flow-based programming and forward-chaining logic. Includes a live demo applying probabilistic inference programming to a complex IoT application.

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