Reactive Orchestration Fabric for Auto-Scaling Cloud Pipelines
Keywords:
Cloud computing, event-driven architecture, event sourcing, workflow management, workflow execution, cloud elasticity, elastic cloud computing, cloud workflow, event-driven orchestration, cloud application management, cloud autoscaling, cloud data management, cloud fault tolerance, event-triggered automation, event-driven automation, event governance.Abstract
Elastic cloud environments span a wide range of platforms and services, and while flexibility and scalability are their defining strengths, they still lack the ability to respond automatically to external events—reacting only to incoming workloads. Recent work has explored using events to trigger control actions in the cloud, but these mechanisms have yet to be extended toward opening new cloud services, scaling existing ones, or constructing complex event-triggered workflows.
This paper addresses these gaps by introducing a new event-responsive automation framework for elastic cloud workflow execution, one that integrates event-driven cloud orchestration with workflow automata semantics. Workflows are modeled as a mapping between a set of core concepts—events, triggers, actions, and states—and corresponding state automata. Building on this foundation, we define five types of event-driven orchestration patterns, spanning a spectrum from fully reactive to fully proactive workflows, and distinguish them along the dimensions of fault tolerance, latency, and event handling.
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Copyright (c) 2025 Ravi Kumar Vankayalapati, Hiroshi Tanaka (Author)
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