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Lookup NU author(s): Saleh Mohamed, Dr Matthew ForshawORCiD, Dr Nigel Thomas
This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by ACM, 2017.
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Distributed stream processing and event-based systems are an increasingly critical component in contemporary largescale data processing applications, and are often subject to strict latency and reliability requirements. However, to achieve scalability demands, they are often deployed on distributed clusters of heterogeneous nodes, causing unpredictable runtime performance and complex fault characteristics. The behaviour of these systems is poorly understood, and existing performance and dependability evaluation techniques are ill-equipped to handle the challenges introduced by the complex and distributed nature of event-based systems. We develop a dynamic code-injection approach to evaluate the performance and dependability of stream processing and event-based systems. Our approach supports finegrained instrumentation of applications and their runtime infrastructure, and the dynamic injection of code mutations and faults into a production system at runtime. We demonstrate the proposed approach by performing instrumentation and code injection on a distributed Apache Spark cluster.
Author(s): Mohamed S, Forshaw M, Thomas N, Dinn A
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: ICPE '17: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering
Year of Conference: 2017
Pages: 349-352
Online publication date: 17/04/2017
Acceptance date: 15/12/2016
Date deposited: 25/04/2017
Publisher: ACM
URL: https://doi.org/10.1145/3030207.3030245
DOI: 10.1145/3030207.3030245
Library holdings: Search Newcastle University Library for this item
ISBN: 9781450344043