A Chaos Engineering Approach for Improving the Resiliency of IT Services Configurations

Poltronieri, Filippo; Tortonesi, Mauro; Stefanelli, Cesare

doi:10.1109/noms54207.2022.9789887

Cited by 6 publications

(1 citation statement)

References 15 publications

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“…For instance, CloudStrike implemented CE principles by introducing system failures and defects to cloud resources to study cybersecurity breaches caused by human errors and misconfigured resources [37], [38]. In [39], the authors introduced an information technology (IT) service management framework that integrates CE techniques with DTs to test the resiliency of complex IT services deployed in hybrid cloud scenarios. This integration allowed them to assess the robustness of deployed IT services and identify potential weaknesses.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Operational Resilience of Critical Infrastructure Processes Through Chaos Engineering

Dedousis,

Stergiopoulos,

Arampatzis

et al. 2023

IEEE Access

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Modern cyber-physical systems (CPS) are interdependent, mechanical and IT components that support operations in most of society's critical infrastructures. Time and again history has proven that CPS are vulnerable to numerous types of threats, ranging from safety accidents to cybersecurity malicious attacks. Current research focuses in analyzing the various input vectors in CPS, whether mechanical or IT, to detect and patch flaws and vulnerabilities to mitigate potential impact in operation. Still, there is little work that can inherently analyze the software-based implementation of modern CPS with complex behavior and failure modes. The only vaguely relevant approach involves an operations-based experimentation methodology from NetFlix named chaos engineering (CE) that tests use-cases on complex Content Delivery Networks (CDN) to build confidence in their capability to withstand turbulent conditions in production. Conditions can range from hardware failures to DoS attacks, to a malformed injection appearing in a runtime configuration parameter. Yet this approach was only tested on software based CDN, and not on CPS with industrial actuators and mechanical parts that control physical processes. In this paper, we introduce a novel framework that combines CE with digital twin (DT) technology to enhance the detection of operational vulnerabilities and increase the resilience of CPS. To achieve this objective, we integrated CE experimentation into the simulation phase of DT models using material flow networks. This allows us to assess system resilience during the operational stage without disrupting critical operations and identify vulnerable flows and processes within the modeled system. To evaluate the effectiveness of our approach, we conduct experiments on a DT that models a real-world Liquefied Petroleum Gas purification process from an existing oil refinery in the Mediterranean area. The results of these experiments demonstrate the methods effectiveness to capture the heightened susceptibility of the Gas purification process to adverse events.

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Section: Related Workmentioning

confidence: 99%

Enhancing Operational Resilience of Critical Infrastructure Processes Through Chaos Engineering

Dedousis,

Stergiopoulos,

Arampatzis

et al. 2023

IEEE Access

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Exploring the impact of chaos engineering with various user loads on cloud native applications: an exploratory empirical study

Al-Said Ahmad,

Al-Qora’n,

Zayed

2024

Computing

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One of the most popular models that provide computer resources today is cloud computing. Today’s dynamic and successful platforms are created to take advantage of various resources available from service providers. Ensuring the performance and availability of such resources and services is a crucial problem. Any software system may be subject to faults that might propagate to cause failures. Such faults with the potential of contributing to failures are critical because they impair performance and result in a delayed reaction, which is regarded as a dependability problem. To ensure that critical faults can be discovered as soon as possible, the impact of such faults on the system must be tested. The performance and dependability of cloud-native systems are examined in this empirical study using fault injection, one of the chaos engineering techniques. The study explores the impacts and results of injecting various delay times into two cloud-native applications with diverse user numbers. The performance of the applications with various numbers of users is measured in relation to these delays, which accordingly reflects measuring the dependability of those systems. Firstly, the systems’ architecture were identified, and serverless with two Lambda functions and containerised microservices applications were chosen, which depend on utilising and incorporating cloud-native services. Secondly, faults are injected in order to quantify performance attributes such as throughput and latency. The results of several controlled experiments carried out in real-world cloud environments provide exploratory empirical data, which promoted comparisons and statistical analysis that we utilised to identify the behaviour of the application while experiencing stress. Typical results from this investigation include an overall reduction in performance that is embodied in an increase in latency with injecting delays. However, a remarkable result is noticed at a particular delay in which defects and availability problems appear out of nowhere. These findings assist in highlighting the value of using chaos engineering in general and fault injection in particular to assess the dependability of cloud-native applications and to find unpredicted failures that could arise quickly from defects that aren’t supposed to spread and result in dependability issues.

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Cloud-native systems resilience assessments based on kubernetes architecture graph

Wang,

Liu,

Yue

et al. 2024

SOCA

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A Chaos Engineering Approach for Improving the Resiliency of IT Services Configurations

Cited by 6 publications

References 15 publications

Enhancing Operational Resilience of Critical Infrastructure Processes Through Chaos Engineering

Enhancing Operational Resilience of Critical Infrastructure Processes Through Chaos Engineering

Exploring the impact of chaos engineering with various user loads on cloud native applications: an exploratory empirical study

Cloud-native systems resilience assessments based on kubernetes architecture graph

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