Real-time directed acyclic graph (DAG) scheduling provides a rigorous basis for timing analysis and efficiency in component-oriented real-time systems (CORTS) such as autonomous driving systems, yet challenges remain from the perspectives of both theorists and practitioners. For theorists, no OS natively supports the DAG task model; algorithms are therefore evaluated only analytically or in simulation, ignoring real-hardware overheads. For practitioners, today's CORTS platforms (ROS~2 and AUTOSAR Adaptive Platform) are designed for service composition rather than timing analyzability; adopting DAG scheduling research therefore demands substantial code changes and developer discipline. This paper proposes Awkernel, the first open-source real-time operating system (RTOS) that natively supports real-time DAG scheduling research, bridging DAG scheduling theory and CORTS practice. For theorists, Awkernel is a real-hardware testbed: it exposes a modular OS-native DAG scheduler for easy algorithm implementation, plus a random workload generator and built-in metrics for evaluation. For practitioners, Awkernel is not a full replacement for today's platforms but a CORTS platform maximizing timing analyzability: its familiar publish/subscribe model keeps porting mechanical, mapping each callback to one subtask. Moreover, its function-as-subtask (FasS) API enforces DAG semantics (precedence constraints) without programmer discipline, yielding applications that match the theoretical DAG model and directly inherit its efficiency and safety guarantees. On a Raspberry Pi~4, microbenchmarks confirm microsecond-level scheduling overheads; a global earliest deadline first (GEDF) scheduler fits in 226~lines; and a practitioner ports part of an autonomous driving system using only the FasS API, without reasoning about DAG semantics.

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