论文标题
TriggerFlow：基于触发的无服务器工作流程的编排
Triggerflow: Trigger-based Orchestration of Serverless Workflows
论文作者
论文摘要
随着无服务器计算的越来越多的应用程序将更多的应用程序移至云，越来越有必要支持数据中心中这些应用程序的本地生命周期执行。但是，现有系统要么关注短运行的工作流（例如IBM Composer或Amazon Express Workfrows），要么施加了相当大的开销，以同步大规模并行作业（Azure Durable功能，Amazon Step Functions，Google Cloud Cloud Cloud Composer）。它们都不是开放系统，可以实现自定义工作流程的可扩展拦截和优化。我们提出triggerFlow：一种可扩展的基于触发的编排体系结构，用于在Knative Eventing和Kubernetes Technologies之上构建的无服务器工作流程。我们证明，TriggerFlow是一个新颖的无服务器构建块，能够构建不同的反应性调度程序（状态机，定向的无环形图，工作流程为代码）。我们还验证它可以支持大量事件处理工作负载，自动尺度按需和透明地优化科学工作流程。
As more applications are being moved to the Cloud thanks to serverless computing, it is increasingly necessary to support native life cycle execution of those applications in the data center. But existing systems either focus on short-running workflows (like IBM Composer or Amazon Express Workflows) or impose considerable overheads for synchronizing massively parallel jobs (Azure Durable Functions, Amazon Step Functions, Google Cloud Composer). None of them are open systems enabling extensible interception and optimization of custom workflows. We present Triggerflow: an extensible Trigger-based Orchestration architecture for serverless workflows built on top of Knative Eventing and Kubernetes technologies. We demonstrate that Triggerflow is a novel serverless building block capable of constructing different reactive schedulers (State Machines, Directed Acyclic Graphs, Workflow as code). We also validate that it can support high-volume event processing workloads, auto-scale on demand and transparently optimize scientific workflows.
