Effectiveness of Automated Testing in Container Orchestration

Compliance is not security

Summary Modern information technologies, particularly the technology of very large data bases, Internet and modern mass media, have changed the processes of production, storage and dissemination of information. These technologies have a direct impact on the practical realization of citizens' rights to information. In democratic societies, in modern IT environment, information is produced and disseminated by many social and economic entities. Many producers and disseminators of information do not know or do not obey the criteria which should be met by any information delivered to the public. In this paper the advantages and the threats for the citizens' rights to information generated by the distribution and globalization of information processes in modern IT environment are discussed. It seems that for the protection of the citizens' rights to information, there is the need for specification and codification of quality criteria and standards for information produced and disseminated with the use of modern IT. Official statistics may and should play an important and active role in defining those criteria and standards. Professional ethics of statisticians and of official statistics seems to be the proper basis for that. Ethical principles of statistics are formulated in two basic documents: The fundamental principles of official statistics adopted by the UN Statistical Commission in 1994 and the ISI Declaration on statistical ethics adopted by the ISI in 1985.

In modern IT operations, anticipating and preventing system failures is critical to maintaining operational continuity and minimizing downtime. Traditional reactive monitoring approaches are needed in complex and dynamic IT environments. This paper explores the application of AI and machine learning (ML) in predictive monitoring for IT operations. We delve into advanced algorithms, data processing techniques, model deployment strategies, and the integration of predictive monitoring within IT infrastructure. Furthermore, we address the challenges of scalability, data quality, and model interpretability and discuss future trends that shape the landscape of predictive monitoring.

Abstract—In this article I have deployed a web-based applica- tion to Docker using Amazon web service (EC2 Instance). Elastic Cloud Compute service is used to the run the docker applications on scalable clusters. Amazon EC2 is fully managed and secured Container orchestration service that makes to deploy, manage and scale Dockerized web application. Docker containers on an EC2 instance to run a university management system website on the Amazon Web Services (AWS) cloud. For educational institutions, a university management system is a crucial tool that enables administrators to manage student records, course information, and other crucial data. The introduction to Docker, a containerization technology that makes it simple to build and manage web applications, follows a discussion of the advantages of hosting a university management system website on the cloud. The next section of the paper focuses on the AWS EC2 service and its capabilities, such as its capability for flexible computing and scalability. The paper also offers a step-by-step tutorial on how to use Docker to deploy a university administration system website on an EC2 instance, including instructions on how to set up the EC2 instance, install and configure Docker, and deploy the website code in a Docker container. Elastic Load Balancer and Auto Scaling, two AWS services, are used in the process of setting up security and scalability for the website. The benefits of using Docker to host a university administration system website on AWS EC2 are outlined in the paper’s conclusion, along with predictions for the development of cloud-based web application hosting. This research paper offers a thorough overview of the steps involved in hosting a university management system website using Docker on AWS EC2, making it a useful tool for educational institutions looking to improve their information management procedures and take advantage of cloud computing and Docker- Containerization.

This paper presents the containerization of virtualization method that is done to execute distributed application for smart urban farming system. Containerization is a virtualization method for executing distributed applications without the need of virtual machines. However, when dealing with container downtime, a backup solution is needed to ensure that no data lost and to ensure container is in functioning. A container downtime might be caused by connectivity failure or maximum CPU capacity utilization. Therefore, a micro services-based system was developed by leveraging on containerization technology such as Docker for its lightweight footprint in terms of infrastructure resources and container orchestration capabilities from Kubernetes to enable scalability and reliability of the overall system. The results showed that efficient data monitoring and management with the added advantage of self-healing nature of Kubernetes platform was achieved.

Relevancy of issue under investigation is stipulated by rapid changing of traditional assumptions about regions competitive strength. These tendencies are explicitly characterized by (I) digitization of IT processes and (II) convergence of tools enabling advancement and formation of particular territory image. Today’s on-line environment is simultaneously (I) a platform for presenting the region in virtual space and (II) a tool forming preferences of territorial product consumers. While handling the region’s reputation it is necessary to take into account ‘digital footprint’ as an element which is forming the region’s image and competitive strength. Goal of research — development of recommendations to enable task-oriented formation of territorial image in targeted public consciousness.Main methods of this case study are: analysis of theoretical framework and statistic data, monitoring of news media and social media.The present article is addressing special aspects of regional reputation formation in modern IT medium and foreign and national experience regarding territory advancement in IT environment. It displays the possibility of master data employment for the purpose of particular territory image formation in the consciousness of main targeted public.It becomes possible to improve reputation and, as a consequence, to raise competitive strength of the regions in condition of today’s information-communication environment through sequential, systematic and orderly going through ‘recognition and assumption’ stages both in off-line and on-line media which allows, using targeting, to promptly disseminate information with minimum financial costs.Materials presented herein, constitute practical value for active and consistent implementation of digital technologies not only at the level of individual enterprises but for regional authorities as well.

Purpose of the article: development of tools for building a cyber-stable private cloud. The relevance of building a cyber-resilient private cloud is confirmed by the dynamics of growth in the market volume of relevant solutions. According to PRnewswire, the market for private cloud solutions will reach 183 billion USD by 2025. At the same time, the average annual growth rate of the CAGR will be 29.4% during the forecast period. According to the analytical company Grand view research, the global market for private cloud solutions in 2018 was estimated at 30.24 billion US dollars, and it is expected that in the period from 2019 to 2025, the CAGR will be 29.6%. Research methods: It uses a set of open-source solutions that applies the advanced cloud technologies, including distributed data processing models and methods, container orchestration technologies, softwaredefined data storage architecture, and a universal database. Results: Developed tools for building a cyber-stable private cloud. Considered a possible approach to building a cyber-resilient private cloud based on the well-known and proprietary models and methods of the artificial immune systems (AIS), as well as technologies for distributed data processing, container orchestration, and others. In addition, the unique centralized fault-tolerant logging and monitoring subsystem has been developed for the described platform, as well as an innovative cybersecurity subsystem based on the following original technologies.

In recent years, the popularity of containerization technologies has been growing. When they are used, computational tasks are placed in lightweight containers that can be easily moved between different computing nodes. Containerization using Docker is especially popular at the moment. The use of these solutions opens up enormous opportunities for building distributed and cluster computing systems. To maintain the operability of such systems, special tools are used, and one of them is an orchestrator. However, existing orchestrators are focused on not-so-large computing systems in which performance can be maintained by simply moving computational tasks from non-working nodes to working ones. In large systems with many nodes and a huge number of computational tasks, it is also necessary to take into account the uneven consumption of resources by various tasks. This article proposes a system architecture that can solve the problem of container orchestration using machine learning methods and given the uneven consumption of resources by

Living IT infrastructures — An ontology-based approach to aligning IT infrastructure capacity and business needs

Component-based software systems (CBSSs) enable modular design and reuse, but their integration poses substantial testing challenges. Integration faults often stem from interactions between components and are difficult to detect with isolated unit testing. Existing integration testing practices require significant manual effort, particularly in configuring test environments and maintaining test suites as systems evolve.This dissertation introduces the Interaction-based Integration (IBI) Testing Approach, a novel approach to automate integration testing by reusing unit test cases. The IBI testing approach comprises the IBI Metamodel, which captures structural, behavioral, and interaction expectation aspects of CBSSs, and the IBI Testing Process, which operationalizes the IBI Metamodel. The approach leverages unit test cases to derive interaction expectations, and generate so called interaction test cases, by reusing the test outputs of one unit test case as inputs for another. It thereby simulates system behavior, enabling integration testing without the need for dedicated integration test cases or environments. In contrast to existing approaches, which require dedicated integration environments and handcrafted test cases, this work enables integration validation through existing unit test artifacts.The IBI testing approach is formalized using property graphs and regular path queries. It is implemented in the InterACt tool, evaluated through a demonstration case study on a microservice system and an exploratory case study in collaboration with an industry partner. The results confirm the feasibility of the IBI Testing Approach while identifying practical limitations that guide future improvements.This work contributes a reusable integration testing model, a formalized testing process, and a tool-supported implementation that provide a novel approach to integration testing of CBSSs. The findings highlight the potential of reusing unit test cases for integration testing, while also addressing the challenges and limitations of this approach in practice.

In modern IT infrastructure projects, optimizing system performance and security is crucial for ensuring reliability, efficiency, and compliance. This study explores the role of business analytics in improving IT infrastructure performance and mitigating cybersecurity risks. By utilizing real-world datasets rather than literature-based models, this research applies predictive analytics, machine learning algorithms, and business intelligence tools to enhance IT operations. The findings reveal a 26.7% reduction in CPU usage, 25% improvement in memory utilization, and a 29.2% decrease in network latency, demonstrating the effectiveness of data-driven performance optimization. Additionally, cybersecurity risk assessments using machine learning models resulted in a 14% improvement in threat detection accuracy, a 4% false positive rate, and a 75% reduction in compliance breach risks, ensuring better adherence to security frameworks like ISO 27001 and NIST. The integration of business intelligence dashboards (Tableau, Power BI) enables real-time monitoring of IT risks, enhancing decision-making and proactive threat mitigation. This study contributes to the field by providing a scalable, analytics-driven framework for IT performance enhancement and cybersecurity resilience, bridging the gap between operational efficiency and security risk management. Future research should explore advanced AI-driven automation and real-time adaptive security measures to further strengthen IT infrastructure

Legacy code in IT infrastructures poses significant challenges, including technological obsolescence, integration difficulties, scalability issues, and high maintenance costs. Effective management and modernization of legacy systems are crucial to prevent these outdated codes from hindering technological advancement and operational efficiency. This article examines the pervasive challenges associated with legacy code and proposes a multi-faceted approach to overcoming these issues. By adopting strategies such as incremental modernization, automation, refactoring, leveraging cloud technologies, and investing in workforce development, organizations can enhance the functionality of legacy systems within the modern IT landscape. These strategies not only mitigate the risks associated with legacy systems but also align them with contemporary business needs and technology standards.

This paper presents a comprehensive methodology for achieving precise colocation demand forecasts through a bottoms - up approach. Colocation services play a crucial role in modern IT infrastructure, necessitating accurate predictions for effective resource allocation. The bottoms - up methodology involves a detailed analysis of individual components within the colocation landscape, such as server capacity, network capabilities, and storage requirements. By dissecting the ecosystem into fundamental elements, this approach aims to enhance the granularity of the forecasting process, providing actionable insights for organizations. The exploration delves into key elements critical to the success of bottoms - up forecasting, addressing the nuances of understanding and quantifying server capacity, network capabilities, and storage requirements. This examination contributes to a nuanced understanding of the colocation landscape, enabling informed decisions based on specific infrastructure needs. This paper unfolds a comprehensive bottoms - up methodology designed to forecast colocation demand with unparalleled precision, aligning seamlessly with the evolving needs of AR/VR landscapes. Despite the benefits, implementing bottoms - up forecasting poses challenges, including issues of data accuracy, integrating diverse components, and external factors like technological advancements and market fluctuations. The paper identifies best practices to overcome these challenges, emphasizing continuous monitoring, adaptability to evolving technologies, and flexibility in the forecasting model.

Cloud-native performance testing has emerged as a critical discipline for ensuring application reliability and user experience in modern distributed systems. Unlike traditional testing methods designed for monolithic architectures, cloud-native approaches leverage distributed load generation, chaos engineering principles, and infrastructure-as-code frameworks to evaluate application behavior across dynamic, auto-scaling environments. By integrating comprehensive observability with performance testing, organizations can identify complex inter-service dependencies, container orchestration impacts, and resource contention issues that would otherwise remain undetected until production. The evolution from periodic testing events to continuous performance validation within CI/CD pipelines enables earlier detection of potential issues, substantially reducing customer impact and operational costs. Case studies across e-commerce, financial services, and media streaming sectors demonstrate how these advanced testing methodologies deliver significant improvements in transaction success rates, response times, and system availability while simultaneously reducing infrastructure costs.

The current global economic instability and the vulnerability of small island nations are providing the impetus for greater integration between the countries of the South Pacific region. This exercise is critical for their survival in today’s turbulent economic environment. Past efforts of regional integration in the South Pacific have not been very successful. Reasons attributed to this outcome include issues related to damage of sovereignty, and lack of a shared integration infrastructure. Today, the IT resources with collaborative capacities provide the opportunity to develop a shared IT infrastructure to facilitate integration in the South Pacific. In an attempt to develop a model of regional integration with an IT-backed infrastructure, we identify and report on the antecedents of the current stage of regional integration, and the stakeholders’ perceived benefits of an IT resources backed regional integration in the South Pacific. Employing a case study based approach, the study finds that while most stakeholders were positive about the potential of IT-backed regional integration, significant challenges exist that hinder the realisation of this model. The study finds that facilitating IT-backed regional integration requires enabling IT infrastructure, equitable IT development in the region, greater awareness on the potential of the modern IT resources, market liberalisation of the information and telecommunications sector and greater political support for IT initiatives.