Vamos: Middleware for best-effort third-party monitoring

As the complexity and criticality of software increase every year, so does the importance of runtime monitoring. Third-party and best-effort monitoring are especially valuable, yet under-explored areas of runtime monitoring. In this context, third-party monitoring means monitoring with a limited knowledge of the monitored software (as it has been developed by a third party). Best-effort monitoring keeps pace with the monitored software at the cost of possibly imprecise verdicts when keeping up with the monitored software would not be feasible. Most existing monitoring frameworks do not support the combination of third-party and best-effort monitoring because they either require the full access to the monitored code or the ability to process all observable events, or both. We present a middleware framework, Vamos , for the runtime monitoring of software. Vamos is explicitly designed to support third-party and best-effort scenarios. The design goals of Vamos are (i) efficiency (tracing events with low overhead), (ii) flexibility (the ability to monitor a variety of different event channels, and to connect to a wide range of monitors), and (iii) ease-of-use. To achieve its goals, Vamos combines aspects of event broker and event recognition systems with aspects of stream processing systems. We implemented a prototype toolchain for Vamos and conducted a set of experiments demonstrating the usability of the scheme. The results indicate that Vamos enables writing useful yet efficient monitors, and simplifies key aspects of setting up a monitoring system from scratch.

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Publication Details

Journal
Science of Computer Programming
Published
2024-09-23
DOI
https://doi.org/10.1016/j.scico.2024.103212
Primary Topic
Real-Time Systems Scheduling
Type
article
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article

Vamos: Middleware for best-effort third-party monitoring

Fabian Muehlboeck, Marek Chalupa, Thomas A. Henzinger, Stefanie Muroya Lei
Science of Computer Programming
Real-Time Systems Scheduling
article

Vamos: Middleware for best-effort third-party monitoring

Fabian Muehlboeck, Marek Chalupa, Thomas A. Henzinger, Stefanie Muroya Lei
article en

Abstract

As the complexity and criticality of software increase every year, so does the importance of runtime monitoring. Third-party and best-effort monitoring are especially valuable, yet under-explored areas of runtime monitoring. In this context, third-party monitoring means monitoring with a limited knowledge of the monitored software (as it has been developed by a third party). Best-effort monitoring keeps pace with the monitored software at the cost of possibly imprecise verdicts when keeping up with the monitored software would not be feasible. Most existing monitoring frameworks do not support the combination of third-party and best-effort monitoring because they either require the full access to the monitored code or the ability to process all observable events, or both. We present a middleware framework, Vamos , for the runtime monitoring of software. Vamos is explicitly designed to support third-party and best-effort scenarios. The design goals of Vamos are (i) efficiency (tracing events with low overhead), (ii) flexibility (the ability to monitor a variety of different event channels, and to connect to a wide range of monitors), and (iii) ease-of-use. To achieve its goals, Vamos combines aspects of event broker and event recognition systems with aspects of stream processing systems. We implemented a prototype toolchain for Vamos and conducted a set of experiments demonstrating the usability of the scheme. The results indicate that Vamos enables writing useful yet efficient monitors, and simplifies key aspects of setting up a monitoring system from scratch.

Science of Computer ProgrammingVol. 240
Australian National University (AU), Institute of Science and Technology Austria (AT)
Openalex Percentile: Top 84%
Real-Time Systems Scheduling
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Vamos: Middleware for best-effort third-party monitoring — Fabian Muehlboeck, Marek Chalupa, et al. · Science of Computer Programming (2024) | TGRS Research Map | TGRS