PPTAM$\eta$: Energy Aware CI/CD Pipeline for Container Based Applications

2026-02-12

AI Summary

This work addresses the lack of quantified energy-efficiency feedback in current CI/CD pipelines for containerized microservices, which hinders the evaluation of code changes’ energy impact. We propose an integrated approach that seamlessly embeds hardware-level power measurements into GitLab CI by orchestrating workload generation, container monitoring, and power probing to automatically collect comparable performance and energy metrics on every code commit. To our knowledge, this is the first method to incorporate hardware-grade energy monitoring directly into containerized continuous delivery workflows, enabling cross-version energy-efficiency comparisons and trend analysis. The feasibility and measurement validity of the proposed architecture were successfully demonstrated through four consecutive commits to a JWT authentication API, effectively bridging the gap in energy-aware feedback within CI/CD systems.

Technology Category

• Machine Learning: Hardware-aware ML
• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Plan Execution and Monitoring

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Security and Privacy: Large-scale security measurements
• Web Mining and Content Analysis: Web measurements

Abstract

Modern container-based microservices evolve through rapid deployment cycles, but CI/CD pipelines still rarely measure energy consumption, even though prior work shows that design patterns, code smells and refactorings affect energy efficiency. We present PPTAM$\eta$, an automated pipeline that integrates power and energy measurement into GitLab CI for containerised API systems, coordinating load generation, container monitoring and hardware power probes to collect comparable metrics at each commit. The pipeline makes energy visible to developers, supports version comparison for test engineers and enables trend analysis for researchers. We evaluate PPTAM$\eta$ on a JWT-authenticated API across four commits, collecting performance and energy metrics and summarising the architecture, measurement methodology and validation.

Problem

• energy consumption
• CI/CD pipeline
• container-based applications
• microservices
• software energy efficiency

Innovation

• energy-aware CI/CD
• containerized applications
• power measurement
• automated pipeline
• microservices