# CommC: A Multi-Purpose COMModity Hardware Cluster
## 6 Conclusions and Future Work  
The proposed CommC system effectively demonstrates the potential of repurposing commodity hardware into a high-performing, multi-purpose cluster. By integrating advanced virtualization and containerization technologies, including KVM, Docker, and Kubernetes, CommC provides a scalable, flexible, and cost-efficient solution tailored to diverse workload demands. This hybrid architecture optimizes underutilized hardware and significantly reduces operational costs while offering enhanced fault tolerance and security. The use of commodity hardware extends the lifecycle of existing systems, contributing to sustainability by addressing the growing concern about E-waste. Through strategic resource allocation and innovative management approaches, CommC empowers medium-sized enterprises and educational institutions to adopt high-performance computing solutions without incurring prohibitive costs. However, we were unable to find any recent (2024-2025) peer-reviewed publications specifically addressing the energy consumption and environmental impact of cloud providers. Many articles [33; 34; 35] exist, revealing the fact that over the past five years, the operation of data centers by major tech companies has led to more than USD 5.4 billion in public health costs due to air pollution. In 2023 alone, these costs were estimated at USD 1.5 billion, marking a 20% increase from the previous year. Google's data centers were identified as the largest contributors, accounting for USD 2.6 billion in health-related expenses between 2019 and 2023. The energy consumption of these centers, often reliant on fossil fuels, has been linked to air pollution's contribution to ailments such as cancer and asthma. Furthermore, popular cloud service providers do not offer a carbon emission estimator based on a chosen configuration, making it challenging to accurately assess the environmental impact of different setups. As a result, a direct comparison of energy consumption between our system and cloud-based alternatives remains difficult without standardized emission metrics. However, one of the key sustainability advantages of our approach is that it extends the lifespan of existing hardware, preventing it from being discarded as electronic waste. By repurposing commodity hardware instead of decommissioning it, our system reduces E-waste accumulation and contributes to a more sustainable computing model. The CommC system offers a cost-effective and scalable solution for leveraging commodity hardware, but it is not without its limitations. One significant challenge lies in the complexity of maintaining the architecture. The system integrates multiple advanced technologies, including KVM, Kubernetes, Docker, and Proxmox, which, while offering flexibility and functionality, introduce a level of operational complexity. Organizations with limited technical expertise or small IT teams may find it difficult to manage and troubleshoot such a setup. The steep learning curve associated with configuring and maintaining these tools could require considerable time and effort, potentially offsetting the system's benefits. Another limitation of CommC that is related to the underlying systems, mainly Proxmox, is the number of nodes that can be added to a single cluster. Proxmox relies on Corosync for synchronization, which can introduce overhead when achieving consensus. According to Proxmox's official documentation, \"There is no explicit limit for the number of nodes in a cluster. In practice, the actual possible node count may be limited by the host and network performance. Currently (2021), there are reports of clusters (using high-end enterprise hardware) with over 50 nodes in production\". However, other accounts indicate that Corosync may exhibit communication issues in clusters with more than 30 nodes. The primary bottleneck and root of these types of problems lies in the computers' network interface controllers, which, unfortunately, cannot be remedied without a hardware upgrade.