Green Cloud Computing: Reducing the Carbon Footprint of Microsoft Azure Workloads
DOI:
https://doi.org/10.61424/jcsit.v1i1.1076Keywords:
Green cloud computing, carbon footprint, Microsoft Azure, energy efficiency, carbon-aware computing, virtual machine consolidation, sustainabilityAbstract
Data centers underpinning cloud computing consume a substantial and growing share of global electricity, and the resulting carbon emissions have become a material sustainability concern for organizations that operate at cloud scale. Green cloud computing addresses this concern by combining resource-efficiency techniques, such as workload consolidation and right-sizing, with carbon-aware practices that account for when and where computation occurs relative to the availability of low-carbon electricity. This article examines how these techniques can be applied to reduce the carbon footprint of workloads hosted on Microsoft Azure, The article proposes a carbon-aware workload management architecture spanning grid carbon intensity signal ingestion, workload characterization, a central scheduling layer, and three green optimization actions, namely regional placement, right-sizing and consolidation, and deferred scheduling, compares six green computing techniques against their underlying principles and Azure implementation, and maps common sustainability challenges to specific mitigation approaches. Two tables and one architecture figure illustrate this analysis. The findings indicate that resource-efficiency techniques such as consolidation and autoscaling remain the most mature and broadly deployable levers available to Azure customers today, while carbon-aware temporal and spatial workload shifting, though demonstrated to meaningfully reduce emissions in research settings, requires workloads with sufficient scheduling flexibility to apply effectively. The article concludes with practical recommendations for organizations seeking to reduce the carbon footprint of their Azure workloads.
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