Despite the recent exponential growth in cloud adoption, businesses that handle sensitive data (e.g., health and financial sectors) are hesitant to migrate their on-premises IT infrastructure to the public cloud due to the lack of trust on the cloud provider. Confidential computing aims to move the cloud provider out of the trusted computing base. New hardware features such as AMD's SEV-SNP can run a full virtual machine (VM) with confidentiality and integrity protection against the cloud. However, there exist challenges in supporting legacy operating systems and enforcing security policies (e.g., firewalls) in confidential VMs.

Operating system (OS) extensions are more popular than ever. For example, Linux BPF is marketed as a "superpower" that allows user programs to be downloaded into the kernel, verified to be safe and executed at kernel hook points. So, BPF extensions have high performance and are often placed at performance-critical paths for tracing and filtering.

Unikernels leverage library OS architectures to run isolated workloads on the cloud. They have garnered attention in part due to their promised performance characteristics such as small image size, fast boot time, low memory footprint and application performance. However, those that aimed at generality fall short of the application compatibility, robustness and, more importantly, community that is available for Linux. In this paper, we describe and evaluate Lupine Linux, a standard Linux system that---through kernel configuration specialization and system call overhead elimination---achieves unikernel-like performance, in fact outperforming at least one reference unikernel in all of the above dimensions. At the same time, Lupine can run any application (since it is Linux) when faced with more general workloads, whereas many unikernels simply crash. We demonstrate a graceful degradation of unikernel-like performance properties.