Engineering
The Flowable Engine as a Serverless Function: Part II
Flowable core developers Filip Hrisafov and Joram Barrez continue the Flowable + serverless journey by looking at other technologies that make a serverless “process as a function” possible.
In part 1, they discussed what serverless is, its challenges with regards to the Flowable engines and demonstrated implementations using Flowable with Spring Cloud (including running it on AWS Lambda), Micronaut and GraalVM.
In this follow-up part, they look closer this time at implementing such a functions using Flowable combined with Spring Fu and building a native image with GraalVM. The end result is an incredible 13 milliseconds bootup time for a full-fledged Flowable-powered function!
BPMN is dead, long live BPMN
Tools like ChatGPT can handle a variety of business tasks, automating nearly everything. And it’s true, GenAI really can do a wide range of tasks that humans do currently. Why not let business users work directly with AI then? And what about Agentic AI?
Measuring model complexity – Part 3: Introducing Complexity Analyzer
In this post, we continue our exploration of workflow complexity - learn how key metrics like activity count and control flow reveal natural groupings of models, making it easier to identify and improve overly complex designs.
Measuring model complexity – Part 2: Putting theory into practice
In this post, we continue our exploration of workflow complexity - learn how key metrics like activity count and control flow reveal natural groupings of models, making it easier to identify and improve overly complex designs.