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

TL;DR

This paper introduces a Kubernetes-based tool that non-intrusively applies design patterns to cloud data pipelines, enhancing energy efficiency and reusability without modifying service code.

Contribution

It presents a novel, non-intrusive framework for deferred pattern application in cloud data pipelines, supporting energy-aware optimization and preserving service reusability.

Findings

Enables non-intrusive pattern injection in data pipelines

Supports energy-aware decision making with collected metrics

Preserves reusability of transformation services across pipelines

Abstract

As data mesh architectures grow, organizations increasingly build consumer-specific data-sharing pipelines from modular, cloud-based transformation services. While reusable transformation services can improve cost and energy efficiency, applying traditional cloud design patterns can reduce reusability of services in different pipelines. We present a Kubernetes-based tool that enables non-intrusive, deferred application of design patterns without modifying services code. The tool automates pattern injection and collects energy metrics, supporting energy-aware decisions while preserving reusability of transformation services in various pipeline structures.