The advent of self driving labs as a fully autonomous implementation of a materials acceleration platform has broadened the purview of experimentation automation beyond traditional high throughput experimentation. Concomitantly, the materials automation community has envisioned international networks of laboratories that may be controlled by multi-agent AI systems and/or human-in-the-loop active learning. As new automated workflows are developed in isolation and then fed into broader networks of capabilities, instrument control software must be prepared to make the transition from single-workflow orchestration to participation in many-workflow automation schemes. Traditional lab automation software cannot effectively manage sharing of resources among workflows while maintaining an independent runtime environment for each workflow. We introduce HELAOasync as a framework for facilitating the automation of individual resources, their incorporation into workflows, and the interconnection of workflows. Combining object-oriented and asynchronous programming, HELAO-async abstracts resource managers and workflow orchestrators as FastAPI servers. Communication, both between servers and with additional programming instances such as web user interfaces and AI-driven experiment brokers, is implemented using FastAPI websockets and endpoints. In addition to a demo virtual instrument to facilitate learning about HELAO-async, the present work introduces the open source code repositories that house the automation software for a suite of materials acceleration platforms in the high throughput experimentation group at the California Institute of Technology.