A Non-Intrusive Framework for Deferred Integration of Cloud Patterns in Energy-Efficient Data-Sharing Pipelines

As data mesh architectures gain traction in federated environments, organizations are increasingly building consumer-specific data-sharing pipelines using modular, cloud-native transformation services. Prior work has shown that structuring these pipelines with reusable transformation stages enhances both scalability and energy efficiency. However, integrating traditional cloud design patterns into such pipelines poses a challenge: predefining and embedding patterns can compromise modularity, reduce reusability, and conflict with the pipelines dynamic, consumer-driven nature. To address this, we introduce a Kubernetes-based tool that enables the deferred and non-intrusive application of selected cloud design patterns without requiring changes to service source code. The tool supports automated pattern injection and collects energy consumption metrics, allowing developers to make energy-aware decisions while preserving the flexible, composable structure of reusable data-sharing pipelines.