The need to reduce datacenter carbon footprint is urgent. While many sustainability techniques have been proposed, they are often evaluated in isolation, using limited setups or analytical models that overlook real-world dynamics and interactions between methods. This makes it challenging for researchers and operators to understand the effectiveness and trade-offs of combining such techniques. We design OpenDC-STEAM, an open-source customizable datacenter simulator, to investigate the individual and combined impact of sustainability techniques on datacenter operational and embodied carbon emissions, and their trade-off with performance. Using STEAM, we systematically explore three representative techniques - horizontal scaling, leveraging batteries, and temporal shifting - with diverse representative workloads, datacenter configurations, and carbon-intensity traces. Our analysis highlights that datacenter dynamics can influence their effectiveness and that combining strategies can significantly lower emissions, but introduces complex cost-emissions-performance trade-offs that STEAM can help navigate. STEAM supports the integration of new models and techniques, making it a foundation framework for holistic, quantitative, and reproducible research in sustainable computing. Following open-science principles, STEAM is available as FOSS: https://github.com/atlarge-research/OpenDC-STEAM.

翻译：减少数据中心碳足迹的需求刻不容缓。尽管已有多种可持续性技术被提出，但它们通常仅在有限的设置或忽略实际动态及方法间交互的分析模型中被单独评估。这使得研究人员和运维人员难以理解组合此类技术的有效性及权衡。我们设计了OpenDC-STEAM，一个开源可定制的数据中心模拟器，用于研究可持续性技术对数据中心运营碳排放和隐含碳排放的单独及综合影响，及其与性能之间的权衡。利用STEAM，我们系统性地探索了三种代表性技术——水平扩展、利用电池和时移调度——并结合多样化的代表性工作负载、数据中心配置及碳强度时间序列。我们的分析表明，数据中心动态性可能影响技术有效性，组合策略能显著降低排放，但会引入复杂的成本-排放-性能权衡，而STEAM可辅助导航。STEAM支持新模型与技术的集成，为可持续计算的整体、定量及可重复性研究奠定基础框架。遵循开放科学原则，STEAM以自由开源软件形式提供：https://github.com/atlarge-research/OpenDC-STEAM。