Oil and gas operators continue to seek better ways to unlock value from operational data and drive consistent, predictable performance while mitigating risk on a well-to-well basis. This paper describes how a wellsite Edgecomputing solution was developed to connect and orchestrate the well-activity plan with wellsite advisory systems, provide unified instructions for drilling automation systems, improve the human-to-system interface, and connect cloud-based data lakes to real-time wellsite operations. Crucially, the system leverages open technologies and frameworks to expand options and provide a low-barrier entry point to automation for all vendors. In this new environment, multiple engineering applications can execute in parallel in a distributed microservice-based system ensuring the most pertinent models are continuously leveraged and anchored to the current operational situation. The engineering outputs are then orchestrated against current and future operational context to manage drilling limiters while anticipating and mitigating possible dysfunctions and inefficiencies. As automation has become a mainstream technology in well construction, there is a need for open platforms that integrate both well-activity plans and engineering systems into automated decision-making rig systems. This paper provides details on how this gap has been closed through a vendor-agnostic platform, which aggregates high-frequency, low-latency real-time data with well-planning information and hybrid data-driven models to provide closed-loop control and context-based decision making that interoperates directly with surface and subsurface drilling-automation systems.