Carbon-Aware Test Scheduling in Agentic CI/CD: Risk-Proportionate Agent Tier Routing and Grid-Intensity Deferral

This paper introduces a carbon-aware test scheduler for the K11tech Agentic AI QA System that reduces CI/CD pipeline carbon emissions through two complementary mechanisms: risk-proportionate tier routing, which maps PR risk score to agent tier (CHEAP, MEDIUM, or FULL) to eliminate unnecessary full-suite execution; and grid-intensity deferral, which schedules expensive agents to the lowest-carbon time window in the next six hours using the Green Software Foundation Carbon Aware SDK. Evaluation on 180 real pull requests demonstrates that tier routing reduces per-PR CI carbon by 52.5% for low-risk PRs and 38.7% overall; grid-intensity deferral reduces carbon intensity by 52.4% for full-tier agents, saving 16.80 g CO₂ (31.4% of baseline) for HIGH/CRITICAL workloads. Both mechanisms preserve defect detection quality (F1 = 0.931). Deferred jobs wait a median of 2.1 hours. The scheduler is validated through a five-phase test suite of 197 tests covering unit, integration, agentic, end-to-end, and carbon accounting layers. It integrates with any agentic QA pipeline via a zero-modification adapter pattern and is released as open-source software under the Apache 2.0 license. This work aligns with the EU Corporate Sustainability Reporting Directive (CSRD) and the Green Software Foundation Software Carbon Intensity (SCI) specification.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-28
DOI
https://doi.org/10.5281/zenodo.21036497
Primary Topic
Modular Robots and Swarm Intelligence
Type
preprint
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preprint

Carbon-Aware Test Scheduling in Agentic CI/CD: Risk-Proportionate Agent Tier Routing and Grid-Intensity Deferral

Kavita Jadhav
Zenodo (CERN European Organization for Nuclear Research)
Modular Robots and Swarm Intelligence
preprint

Carbon-Aware Test Scheduling in Agentic CI/CD: Risk-Proportionate Agent Tier Routing and Grid-Intensity Deferral

Kavita Jadhav
preprint en

Abstract

This paper introduces a carbon-aware test scheduler for the K11tech Agentic AI QA System that reduces CI/CD pipeline carbon emissions through two complementary mechanisms: risk-proportionate tier routing, which maps PR risk score to agent tier (CHEAP, MEDIUM, or FULL) to eliminate unnecessary full-suite execution; and grid-intensity deferral, which schedules expensive agents to the lowest-carbon time window in the next six hours using the Green Software Foundation Carbon Aware SDK. Evaluation on 180 real pull requests demonstrates that tier routing reduces per-PR CI carbon by 52.5% for low-risk PRs and 38.7% overall; grid-intensity deferral reduces carbon intensity by 52.4% for full-tier agents, saving 16.80 g CO₂ (31.4% of baseline) for HIGH/CRITICAL workloads. Both mechanisms preserve defect detection quality (F1 = 0.931). Deferred jobs wait a median of 2.1 hours. The scheduler is validated through a five-phase test suite of 197 tests covering unit, integration, agentic, end-to-end, and carbon accounting layers. It integrates with any agentic QA pipeline via a zero-modification adapter pattern and is released as open-source software under the Apache 2.0 license. This work aligns with the EU Corporate Sustainability Reporting Directive (CSRD) and the Green Software Foundation Software Carbon Intensity (SCI) specification.

Zenodo (CERN European Organization for Nuclear Research)
LPA Software Solutions (United States) (US)
Responsible consumption and production
Modular Robots and Swarm Intelligence
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