<p>Disk bandwidth is a critical resource for I/O-intensive applications that must transfer large volumes of data to and from persistent storage. Most multi-tenant infrastructures efficiently allocate CPU and memory resources to concurrent workloads, but typically lack mechanisms for allocating I/O bandwidth. As a result, users often resort to exclusive node reservations to avoid disk contention, which can lead to underutilisation of other node resources if not fully exploited. Another common issue is that users do not know the exact resource requirements of their applications. Even when this is known, applications rarely maintain peak resource usage throughout their entire execution, resulting in wasted resources that could otherwise benefit other users. Today, many users prefer cloud serverless platforms because of their ease of use and flexible billing. However, these platforms have inherent limitations and may not be suitable for workloads with specific requirements. In this paper, we present a serverless scaling mechanism that dynamically adjusts disk I/O bandwidth for containerised applications by scaling their allocation up or down based on real-time usage and configurable weights. In addition, the system incorporates automatic extension management capabilities for virtual disk devices, such as logical volumes. Our approach can be integrated with other serverless scaling mechanisms, such as CPU and memory management, to provide a comprehensive resource scaling solution. The experimental results have shown significant performance improvements, with overall runtime reductions of up to 53% for concurrent I/O-intensive workloads compared to running them without serverless capabilities.</p>