Zephyrus2: On the Fly Deployment Optimization Using SMT and CP Technologies

Ábrahám, Erika; Corzilius, Florian; Johnsen, Einar Broch; Kremer, Gereon; Mauro, Jacopo

doi:10.1007/978-3-319-47677-3_15

Cited by 26 publications

(34 citation statements)

References 24 publications

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“…Neither proposals support the computation of optimal deployments. Our work is inspired by the Aeolus component model [8,9], the Zephyrus configuration optimizer [1], and ConfSolve [22]. The Aeolus model paved the way to reason on deployment and reconfiguration, proving some decidability results.…”

Section: Related Work and Conclusionmentioning

confidence: 99%

Optimal and Automated Deployment for Microservices

Bravetti

Giallorenzo

Mauro

et al. 2019

Fundamental Approaches to Software Engineering

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Microservices are highly modular and scalable Service Oriented Architectures. They underpin automated deployment practices like Continuous Deployment and Autoscaling. In this paper we formalize these practices and show that automated deployment -proven undecidable in the general case -is algorithmically treatable for microservices.Our key assumption is that the configuration life-cycle of a microservice is split in two phases: (i) creation, which entails establishing initial connections with already available microservices, and (ii) subsequent binding/unbinding with other microservices. To illustrate the applicability of our approach, we implement an automatic optimal deployment tool and compute deployment plans for a realistic microservice architecture, modeled in the Abstract Behavioral Specification (ABS) language.

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Section: Related Work and Conclusionmentioning

confidence: 99%

Optimal and Automated Deployment for Microservices

Bravetti

Giallorenzo

Mauro

et al. 2019

Fundamental Approaches to Software Engineering

Self Cite

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“…SmartDepl is open source, available at https://github.com/jacopoMauro/ 990 abs_deployer and to increase its portability it can be installed also by using Table 1 and given by the user in an ABS annotation), the cost 1000 annotations and the signature of every class (JSON internal representation derived from the structure of the ABS program and the user annotations). With this information SmartDepl is able in the second step to generate the input for Zephyrus2 17 [54,8,55], i.e., a configuration optimizer that given the user requirements and a universe of components, computes the optimal configuration 1005 satisfying the user needs. This process is quite straightforward since Zephyrus2 supports natively constructs and constraints that mirror those of SmartDepl.…”

Section: Toolchain Detailsmentioning

confidence: 99%

“…It is however natural to wonder what are the running times of SmartDepl for normal instances. Unfortunately,as also remarked in[54], there are no standard benchmarks that can be used for the optimization of application deployment. For this reason, in this work we will try to evaluate how good SmartDepl scales by measuring its running times 1405 using the real-world Fredhopper use case as a specific benchmark.In particular, we performed two kinds of scaling experiments.…”

mentioning

confidence: 99%

On the modeling of optimal and automatized cloud application deployment

Gouw

Mauro

Zavattaro

2019

Journal of Logical and Algebraic Methods in Programming

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We investigate the problem of modeling the optimal and automatic deployment of cloud applications. We follow an approach based on three main pillars: (i) the specification of the computing resources needed by software components and those provided by the executing environment (e.g. virtual machines or containers), (ii) the declarative description of deployment rules, (iii) and the computation of an optimal deployment that minimizes the total cost by using constraint solving techniques. We experiment with such an approach by applying it to the Abstract Behavioural Specification language ABS, and we validate it by modeling and simulating with ABS (and its tool-suite) the Fredhopper Cloud Services, a worldwide system offering e-Commerce services, currently deployed on Amazon EC2.

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“…Constrained optimization problems have been previously solved using: (1) exact: e.g. constraint programming [7] and SMT solving [1]; and (2) approximate [10] approaches.…”

Section: Introductionmentioning

confidence: 99%

“…To the best of our knowledge there is only the Zephyrus2 tool [1] using an SMT solver which addresses a problem similar to ours. The problem solved is that, given the application description (interaction constraints and hardware requirements) and VMs specifications, the aim is to minimize the cost and then the number of VMs leased for hosting the application.…”

Section: Introductionmentioning

confidence: 99%

Influence of Variables Encoding and Symmetry Breaking on the Performance of Optimization Modulo Theories Tools Applied to Cloud Resource Selection

Eraşcu¹,

Micota²,

Zaharie³

Kalpa Publications in Computing

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The problem of Cloud resource provisioning for component-based applications is very important. It consists in the allocation of virtual machines (VMs) from various Cloud Providers (CPs), to a set of applications such that the constraints induced by the inter- actions between components and by the components hardware/software requirements are satisfied and the performance objectives are optimized (e.g. costs are minimized). It can be formulated as a constrained optimization problem and tackled by state-of-the-art optimization modulo theories (OMT) tools. The performance of the OMT tools is highly dependent on the way the problem is formalized as this determines the size of the search space. In the case when the number of VMs offers is large, a naive encoding which does not exploit the symmetries of the underlying problem leads to a huge search space making the optimization problem intractable. We overcame this issue by reducing the search space by using: (1) a heuristic which exploits the particularities of the application by detect- ing cliques in the conflict graph of the application components fixing all components of the clique with the largest number of component instances, and (2) a lex-leader method for breaking variable symmetry where the canonical solution fulfills an order based on either the number of components deployed on VMs, or on the VMs price. As the result, the running time of the optimization problem improves considerably and the optimization problem scales up to hundreds of VM offers. We also observed that by combining the heuristic with the lex-leader method we obtained better computational results than by using them separately, suggesting the fact that symmetry breaking constraints have the advantage of interacting well with the search heuristic being used.

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Zephyrus2: On the Fly Deployment Optimization Using SMT and CP Technologies

Cited by 26 publications

References 24 publications

Optimal and Automated Deployment for Microservices

Optimal and Automated Deployment for Microservices

On the modeling of optimal and automatized cloud application deployment

Influence of Variables Encoding and Symmetry Breaking on the Performance of Optimization Modulo Theories Tools Applied to Cloud Resource Selection

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