The supercomputers of South Ural State University are at the core of the University's research performance. These facilities enable researchers to perform a broad range of computationally demanding tasks in the fields of engineering, natural and human sciences, and IT. The powerful capabilities of SUSU supercomputers are currently used for more than 250 research projects, including commercial projects as part of the Industry 4.0. The first-class facilities are ranked among the world's most powerful supercomputers by various ranking agencies.

SUSU Supercomputer Resources for Industry and fundamental Science

Microservice architecture is a cloud application design pattern that implies that the application is divided into a number of small independent services, each of which is responsible for implementing of a certain feature. The need for continuous integration of developed and/or modified microservices in the existing system requires a comprehensive validation of individual microservices and their co-operation as an ensemble with other microservices. In this paper, we would provide an analysis of existing methods of cloud applications testing and identify features that are specific to the microservice architecture. Based on this analysis, we will try to propose a validation methodology of the microservice systems.

Microservices validation: Mjolnirr platform case study

The paper deals with a model and method for building of set of undominizing (the best in described set) alternatives based on building of logic function by of alternatives or object belonging to arbitrary subject area. Comparison of suggested models and methods with fuzzy models and methods of optimization to find the most effective multi-criteria evaluation of investigated objects is conducted. Results for calculation experiments on multi-criteria evaluation and optimization of topologic structures are shown.

http://proceedings.spiiras.nw.ru/ojs/index.php/sp/article/download/1363/1227

Модели и методы многокритериальной оптимизации альтернатив

The paper addresses the relevant problem related to the development of scientific applications (applied software packages) to solve large-scale problems in heterogeneous distributed computing environments that can include various infrastructures (clusters, Grid systems, clouds) and provide their integrated use. We propose a new approach to the development of applications for such environments. It is based on the integration of conceptual and modular programming. The application development is implemented with a special framework named Orlando Tools. In comparison to the known tools, used for the development and execution of distributed applications in the current practice, Orlando Tools provides executing application jobs in the integrated environment of virtual machines that include both the dedicated and non-dedicated resources. The distributed computing efficiency is improved through the multi-agent management. Experiments of solving the large-scale practical problems of energy security research show the effectiveness of the developed application for solving the aforementioned problem in the environment that supports the hybrid computational model including Grid and cloud computing.

Orlando Tools: Energy Research Application Development Through Convergence of Grid and Cloud Computing

Dmitrii Savchenko Testing microservice applications Lappeenranta, 2019 59 p. Acta Universitatis Lappeenrantaensis 868 Diss. Lappeenranta-Lahti University of Technology LUT ISBN 978-952-335-414-2, ISBN 978-952-335-415-9 (PDF), ISSN-L 1456-4491, ISSN 14564491 Software maintenance costs are growing from year to year because of the growing software complexity. Currently, maintenance may take up to 92 percent of the whole project budget. To reduce the complexity of the developed software, engineers use different approaches. Microservice architecture offers a novel solution to the problem of distributed applications’ complexity. The microservice architecture relies on the comprehensive infrastructure, which reduces the complexity of the application. Several large companies have successfully adopted the microservice architecture, but not many studies have examined microservice applications testing and quality assurance. In addition, smaller companies are showing interest in the microservice architecture and trying to adopt it using different infrastructure solutions to reduce software development and maintenance costs or to integrate legacy software into newly developed software. Therefore, we explore the possible approaches to microservice testing, describe the microservice testing methodology, and use design science to implement the microservice testing service that adopts the described methodology. This study provides an analysis of different software testing techniques and offers a methodology for microservice testing. In addition, an example implementation illustrates the described methodology.

Testing microservice applications

One of the important classes of computational problems is problem-oriented workflow applications executed in distributed computing environment. A problem-oriented workflow application can be represented by a directed graph whose vertices are tasks and arcs are data flows. For a problem-oriented workflow application, we can get a priori estimates of the task execution time and the amount of data to be transferred between the tasks. A distributed computing environment designed for the execution of such tasks in a certain subject domain is called problem-oriented environment. To efficiently use resources of the distributed computing environment, special scheduling algorithms are applied. Nowadays, a great number of such algorithms have been proposed. Some of them (like the DSC algorithm) take into account specific features of problem-oriented workflow applications. Others (like Min---Min algorithm) take into account many-core structure of nodes of the computational network. However, none of them takes into account both factors. In this paper, a mathematical model of problem-oriented computing environment is constructed, and a new problem-oriented scheduling (POS) algorithm is proposed. The POS algorithm takes into account both specifics of the problem-oriented jobs and multi-core structure of the computing system nodes. Results of computational experiments comparing the POS algorithm with other known scheduling algorithms are presented.

/pdf/methods-of-resource-management-in-problem-oriented-computing-1t9koljko4.pdf

Methods of resource management in problem-oriented computing environment

The use of a component-oriented approach to the development of distributed applications can significantly extend the scalability of the software systems. In this article we describe the Mjolnirr platform, providing deployment of private cloud PaaS systems, based on the component-oriented approach. Any library or Java application can be implemented on the basis of the Mjolnirr platform as a service. From a developer perspective, an application on the basis of the Mjolnirr platform is a set of independent components, which communicate through a message passing interface. We will discuss an architecture and basic aspects of the implementation of the Mjolnirr platform, consider a problem of workflows scheduling, approaches to simulation of cloud platforms by means of the private cloud PaaS-systems simulation system. Also, we will discuss the results of tests of the platform.

Component-based development of cloud applications: a case study of the Mjolnirr platform

One of important classes of computational problems is the class of problem-oriented workflow applications executed in distributed computing environment. The problem-oriented workflow application can be represented by the oriented graph with the tasks as the nodes and the data flows as the edges. For the problem-oriented workflow application, we can predict the execution time of the task and the amount of data to be transferred between the tasks. Nowadays, the significant number of scheduling algorithms for the distributed computing environment are proposed. Some of them (like DSC algorithm) take into account the peculiarity of problem-oriented workflow applications. Others (like Min-min algorithm) take into account the many core structure of the node of computational network. However, no one of them take into account both these properties. We developed the new Problem-Oriented Scheduling (POS) algorithm for distributed cluster computing environment, which is able to plan the launch of a task on several processor cores, taking into account the limit of task scalability.

Anastasia Shamakina

Papers

Methods of resource management in problem-oriented computing environment

Component-based development of cloud applications: a case study of the Mjolnirr platform

Evaluation of POS scheduling algorithm for distributed computing environment