Autonomic Management Framework for Cloud-Native Applications
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Autonomic Management Framework for Cloud-Native Applications ´ Joanna Kosinska
´ · Krzysztof Zielinski
Received: 27 November 2019 / Accepted: 2 August 2020 © The Author(s) 2020
Abstract In order to meet the rapidly changing requirements of the Cloud-native dynamic execution environment, without human support and without the need to continually improve one’s skills, autonomic features need to be added. Embracing automation at every layer of performance management enables us to reduce costs while improving outcomes. The main contribution of this paper is the definition of autonomic management requirements of Cloudnative applications. We propose that the automation is achieved via high-level policies. In turn autonomy features are accomplished via the rule engine support. First, the paper presents the engineering perspective of building a framework for Autonomic Management of Cloud-Native Applications, namely AMoCNA, in accordance with Model Driven Architecture (MDA) concepts. AMoCNA has many desirable features whose main goal is to reduce the complexity of managing Cloud-native applications. The presented models are, in fact, meta-models, being technology agnostic. Secondly, the paper demonstrates one possibility of implementing the aforementioned design
J. Kosi´nska () · K. Zieli´nski Department of Computer Science, Faculty of Computer Science, Electronics and Telecommunications, AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Krakow, Poland e-mail: [email protected] K. Zieli´nski e-mail: [email protected]
procedures. The presented AMoCNA implementation is also evaluated to identify the potential overhead introduced by the framework. Keywords Autonomic Computing (AC) · Cloud-native · Resource management · Policy-driven management · Observability
1 Introduction System components and software elements have been evolving for decades to deal with the increased complexity of system control, resource sharing and operational management [16]. While Cloud-native is not a novel concept, it remains at the forefront of software development. This approach has not yet been tested with Autonomic Computing (AC) [44], although its usage in this context seems to be a natural step. Such architectures can effectively address the overall complexity of resource management. Fundamentals of Autonomic Computing (AC) paradigm constitutes autonomic elements that are responsible for policydriven self-management of particular system components. The present paper focuses on autonomic management of Cloud-native applications (abbreviated as CNApps) through observation of all their internal components that simply are represented by autonomic elements. The observations are consumed by appropriate sensors of autonomic elements which in turn we propose to realize with the support of a rule engine.
J. Kosi´nska, K. Zieli´nski
CNApp represents a graph of communicating microservices running as containers. Its QoE and QoS are much determined by an orchestration process which is often defined [31] as the automated configurat
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