In the era of Internet of Things, there is an increasing demand for networked computing to support the requirements of timeconstrained, compute-intensive distributed applications. We present a container orchestration architecture for dispersed computing, and its implementation in an open source software called Jupiter. The system automates the distribution of computational tasks for complex computational applications described as an Directed Acyclic Graph (DAG) to efficiently distribute the tasks among a set of networked compute nodes and orchestrates the execution of the DAG thereafter. This Kubernetes based container-orchestration system supports both centralized and decentralized scheduling algorithms for optimally mapping the tasks based on information from a range of profilers: network profilers, resource profilers, and execution time profilers