Even in private settings, cloud computing platforms enable agile and self-service management, which means that physical resources are shared more efficiently. Our dataset and tools are released to the research community.Ībstract Cloud computing considerably reduces the costs of deploying applications through on-demand, automated and fine-granular allocation of resources. Our heuristic hardware dependency detector and a hardware-aware Docker executor give early warnings upon missing dependencies instead of leading to silent or untimely failures. To improve the state of technology, we contribute novel tools to manage such images.

We first conduct a systematic one-year evolution analysis of a sample of Docker images concerning their use of hardware-specific features. This problem can be generalised to missing knowledge about the extent of any hardware-bound instructions within the images that may require elevated privileges. In contrast, little is known about the extent of hardware-dependent features in them such as processor-specific trusted execution environments, graphics acceleration or extension boards. Recent studies have investigated security vulnerabilities and runtime characteristics of Docker images. A container engine runs them with separated privileges according to namespaces. Docker images are used to distribute and deploy cloud-native applications in containerised form.

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