Lightweight virtual machines (VMs) are prominently adopted for improved performance and dependability in cloud environments. To reduce boot up times and resource utilisation, they are usually "pre-baked" with only the minimal kernel and userland strictly required to run an application. This introduces a fundamental trade-off between the advantages of lightweight VMs and available services within a VM, usually leaning towards the former. We propose VMSH, a hypervisor-agnostic abstraction that enables on-demand attachment of services to a running VM---allowing developers to provide minimal, lightweight images without compromising their functionality. The additional applications are made available to the guest via a file system image. To ensure that the newly added services do not affect the original applications in the VM, VMSH uses lightweight isolation mechanisms based on containers. We evaluate VMSH on multiple KVM-based hypervisors and Linux LTS kernels and show that: (i) VMSH adds no overhead for the applications running in the VM, (ii) de-bloating images from the Docker registry can save up to 60% of their size on average, and (iii) VMSH enables cloud providers to offer services to customers, such as recovery shells, without interfering with their VM's execution.

The shielding of applications using trusted execution environments (TEEs) can provide strong security guarantees in untrusted cloud environments. When executing I/O operations, today's shielded execution frameworks, however, exhibit performance and security limitations: they assign resources to the I/O path inefficiently, perform redundant data copies, use untrusted host I/O stacks with security risks and performance overheads. This prevents TEEs from running modern I/O-intensive applications that require high-performance networking and storage.

Major cloud computing operators provide powerful monitoring tools to understand the current (and prior) state of the distributed systems deployed in their infrastructure. While such tools provide a detailed monitoring mechanism at scale, they also pose a significant challenge for the application developers/operators to transform the huge space of monitored metrics into useful insights. These insights are essential to build effective management tools for improving the efficiency, resiliency, and dependability of distributed systems.

Data provenance strives for explaining how the computation was performed by recording a trace of the execution. The provenance trace is useful across a wide-range of workflows to improve the dependability, security, and efficiency of software systems. In this paper, we present Inspector, a POSIX-compliant data provenance library for shared-memory multithreaded programs. The Inspector library is completely transparent and easy to use: it can be used as a replacement for the pthreads library by a simple exchange of libraries linked, without even recompiling the application code. To achieve this result, we present a parallel provenance algorithm that records control, data, and schedule dependencies using a Concurrent Provenance Graph (CPG). We implemented our algorithm to operate at the compiled binary code level by leveraging a combination of OS-specific mechanisms, and recently released Intel PT ISA extensions as part of the Broadwell micro-architecture. Our evaluation on a multicore platform using applications from multithreaded benchmarks suites (PARSEC and Phoenix) shows reasonable provenance overheads for a majority of applications. Lastly, we briefly describe three case-studies where the generic interface exported by Inspector is being used to improve the dependability, security, and efficiency of systems. The Inspector library is publicly available for further use in a wide range of other provenance workflows.