Continuous Integration and Continuous Deployment are known methodologies for software development that increase the overall quality of the development process. Several robotic software repositories make use of CI/CD tools as an aid to development. However, very few CI pipelines take advantage of using cloud computing to run simulations. Here, a CI pipeline is proposed that takes advantage of such features, applied to the development of ATOM, a ROS-based application capable of carrying out the calibration of generalized robotic systems. The proposed pipeline uses GitHub Actions as a CI/CD engine, AWS RoboMaker as a service for running simulations on the cloud and Rigel as a tool to both containerize ATOM and execute the tests. In addition, a static analysis and unit testing component is implemented with the use of Codacy. The creation of the pipeline was successful, and it was concluded that it constitutes a valuable tool for the development of ATOM and a blueprint for the creation of similar pipelines for other robotic systems.

Robot Operating System (ROS) applications are growing increasingly complex and distributed, incorporating multi-node architectures, real-time communication, and compute offloading to cloud or edge resources. Despite advances in containerization, large-scale robotics deployments often rely on ad hoc provisioning, updating, and scalability strategies. This paper’s key contribution is a module extension for an existing ROS-focused container framework that leverages Kubernetes’ capabilities—controlled rolling updates, ROS-adapted readiness checks, distributed workload management, and embedded observability—to bridge cloud-native practices with robotics development. The result is a unified tool that streamlines the entire ROS DevOps cycle. Experimental validation demonstrates stable operation with minimal message loss across diverse ROS communication patterns, including tests on an industrial mobile manipulator system. By simplifying orchestration and monitoring, this approach enables roboticists to concentrate on application logic rather than deployment and networking complexities.