Non-functional requirements optimisation for multi-tier cloud applications: An early warning system case study

Abstract

Modern software engineering tools, technologies and approaches can radically speed up the development and engineering of multi-tier cloud applications and may be applied to the cloud/edge/fog computing paradigm. The engineering of such cloud applications must take into account Non-Functional Requirements (NFRs), such as end-user, software and cloud infrastructure requirements for low-power computing, performance, availability, elasticity, operational cost and similar. Such requirements should be identified and considered early in the software engineering process and decisions must be taken on their trade-offs, e.g. greater service availability while balancing operational costs. This paper introduces a new multi-criteria decision making approach via the use of the Pareto method to aid the software engineers with NFR trade-off adjustment possibilities. Adjustment possibilities may include geographic distribution of application tiers, horizontal and vertical scaling of virtual resources (such as Virtual Machines and containers) and similar. This work builds on top of technologies and tools developed under the SWITCH and ENTICE projects. The impact of this approach is the ability to fully tailor the adjustments of non-functional properties of the multi-tier cloud application according to the decisions of its engineer. An early warning system cloud application is used to present the approach.

SWITCH workbench: A novel approach for the development and deployment of time-critical microservice-based cloud-native applications

“…In addition to developing and demonstrating the effectiveness of the SWITCH architecture, we went beyond the project's objectives and also developed an Multi-Objective Optimisation approach for the trade off between conflicting Non-Functional Requirements in order to assure enhanced QoS. However, details of this latter approach are out of scope of the present paper and can be found elsewhere [16].…”

“…ensuring latency is kept consistent [14]. For custom infrastructure planning and optimisation, techniques such as multi-objective optimisation [15,16] can map application requirements to infrastructure resources more effectively. This can then be used to identify violations of Service Level Agreements (SLA) [17].…”

“…Efficient provisioning is crucial for the enhanced QoS of running applications. Therefore various optimisation approaches are highly desired, such as Multi-criteria optimisation approach for the management of Non-Functional Requirements [16].…”

“…response time, monetary cost, etc.) [16]. Application components can then be deployed to these instances.…”

Formal Quality of Service assurances, ranking and verification of cloud deployment options with a probabilistic model checking method

“…The more criteria used, the higher the complexity of the decision-making process [17,18]. It is therefore necessary to design new methods that can support the deployment of microservices, and which may be integrated into existing workbenches, such as Juju, Fabric8 or SWITCH [19].…”