Abstract
Modern software delivery systems generate operational data across source repositories, CI/CD pipelines, deployment platforms, cloud infrastructure, observability tools, and incident management systems. These systems record valuable information, but they usually preserve it as isolated events, logs, metrics, tickets, and configuration records. As a result, engineers and diagnostic systems must repeatedly reconstruct operational context whenever a failure occurs. This disclosure introduces an Operational Evolution Graph (OEG), a continuously evolving operational knowledge model that persistently captures relationships among software changes, infrastructure updates, deployments, runtime events, investigations, and remediation outcomes. The OEG converts fragmented operational records into reusable operational memory. By maintaining historical relationships and investigation lineage over time, the OEG enables deterministic analytics, graph algorithms, machine learning models, and large language models to reason over existing operational knowledge rather than rebuilding context for each incident.
Creative Commons License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 License.
Recommended Citation
Kunjir, Snehal, "Operational Evolution Graph: A Continuous Operational Knowledge Model for Software Delivery Systems", Technical Disclosure Commons, (July 28, 2026)
https://www.tdcommons.org/dpubs_series/11177