eBPF programs significantly enhance kernel capabilities, but encounter substantial compatibility challenges due to their deep integration with unstable kernel internals. We introduce DepSurf, a tool that identifies dependency mismatches between eBPF programs and kernel images. Our analysis of 25 kernel images spanning 8 years reveals that dependency mismatches are pervasive, stemming from kernel source code evolution, diverse configuration options, and intricate compilation processes. We apply DepSurf to 53 real-world eBPF programs, and find that 83% are impacted by dependency mismatches, underscoring the urgent need for systematic dependency analysis. By identifying these mismatches, DepSurf enables a more robust development and maintenance process for eBPF programs, enhancing their reliability across a wide range of kernels.

Polling-based userspace storage stacks achieve great I/O performance. However, they cannot efficiently and securely share disks and CPUs among multiple tasks. In contrast, interrupt-based kernel stacks inherently suffer from subpar I/O performance but achieve advantages in resource sharing.

We present Robust Alternative Execution (RAE), an approach to transparently mask runtime errors in performance-oriented filesystems via temporarily executing an alternative shadow filesystem. A shadow filesystem has the primary goal of robustness, achieved through a simple implementation without performance optimizations and concurrency while adhering to the same API and on-disk formats as the base filesystem it enhances. While the base performance-oriented filesystem may contain bugs, the shadow implementation is formally verified, leveraging advancements in the verification of low-level systems code. In the common case, the base filesystem executes and delivers high performance to applications; however, when a bug is triggered, the slow-but-correct shadow takes over, updates state correctly, and then resumes the base, thus providing high availability.

In this article, we present an approach to systematically examine the schedulability of distributed storage systems, identify their scheduling problems, and enable effective scheduling in these systems. We use Thread Architecture Models (TAMs) to describe the behavior and interactions of different threads in a system, and show both how to construct TAMs for existing systems and utilize TAMs to identify critical scheduling problems. We specify three schedulability conditions that a schedulable TAM should satisfy: completeness, local enforceability, and independence; meeting these conditions enables a system to easily support different scheduling policies. We identify five common problems that prevent a system from satisfying the schedulability conditions, and show that these problems arise in existing systems such as HBase, Cassandra, MongoDB, and Riak, making it difficult or impossible to realize various scheduling disciplines. We demonstrate how to address these schedulability problems using both direct and indirect solutions, with different trade-offs. To show how to apply our approach to enable scheduling in realistic systems, we develop Tamed-HBase and Muzzled-HBase, sets of modifications to HBase that can realize the desired scheduling disciplines, including fairness and priority scheduling, even when presented with challenging workloads.

We present uFS, a user-level filesystem semi-microkernel. uFS takes advantage of a high-performance storage development kit to realize a fully-functional, crash-consistent, highly-scalable filesystem, with relative developer ease. uFS delivers scalable high performance with a number of novel techniques: careful partitioning of in-memory and on-disk data structures to enable concurrent access without locking, inode migration for balancing load across filesystem threads, and a dynamic scaling algorithm for determining the number of filesystem threads to serve the current workload. Through measurements, we show that uFS has good base performance and excellent scalability; for example, uFS delivers nearly twice the throughput of ext4 for LevelDB on YCSB workloads.

Researchers have long predicted the demise of the operating system [21, 26, 41]. As datacenter servers increasingly incorporate I/O devices that let applications bypass the OS kernel (e.g., RDMA [12] and DPDK [15] network devices or SPDK storage devices), this prediction may finally come true. While kernel-bypass devices do eliminate the OS kernel from the I/O path, they do not handle the kernel's most important job: offering higher-level abstractions. This paper argues for a new high-level, device-agnostic I/O abstraction for kernel-bypass devices. We propose the Demikernel, a new library OS architecture for kernel-bypass devices. It defines a high-level, kernel-bypass I/O abstraction and provides user-space library OSes to implement that abstraction across a range of kernel-bypass devices. The Demikernel makes applications easier to build, portable across devices, and unmodified as devices continue to evolve.