3 research outputs found
How bad can a bug get? An empirical analysis of software failures in the OpenStack cloud computing platform
Cloud management systems provide abstractions and APIs for programmatically configuring cloud infrastructures. Unfortunately, residual software bugs in these systems can potentially lead to high-severity failures, such as prolonged outages and data losses. In this paper, we investigate the impact of failures in the context widespread OpenStack cloud management system, by performing fault injection and by analyzing the impact of the resulting failures in terms of fail-stop behavior, failure detection through logging, and failure propagation across components. The analysis points out that most of the failures are not timely detected and notified; moreover, many of these failures can silently propagate over time and through components of the cloud management system, which call for more thorough run-time checks and fault containment
Fault Injection Analytics: A Novel Approach to Discover Failure Modes in Cloud-Computing Systems
Cloud computing systems fail in complex and unexpected ways due to unexpected
combinations of events and interactions between hardware and software
components. Fault injection is an effective means to bring out these failures
in a controlled environment. However, fault injection experiments produce
massive amounts of data, and manually analyzing these data is inefficient and
error-prone, as the analyst can miss severe failure modes that are yet unknown.
This paper introduces a new paradigm (fault injection analytics) that applies
unsupervised machine learning on execution traces of the injected system, to
ease the discovery and interpretation of failure modes. We evaluated the
proposed approach in the context of fault injection experiments on the
OpenStack cloud computing platform, where we show that the approach can
accurately identify failure modes with a low computational cost.Comment: IEEE Transactions on Dependable and Secure Computing; 16 pages. arXiv
admin note: text overlap with arXiv:1908.1164