Approaches to Test?ng Mult?-Module Services based on Spr?ng Boot

This paper presents a systematic review of Infrastructure as Code (IaC) and GitOps, exploring their transformative roles in cloud automation and governance. IaC, an approach that defines and provisions infrastructure using code, automates cloud infrastructure management, offering significant improvements in consistency, scalability, and agility. GitOps, as an extension of IaC, leverages Git repositories as the single source of truth, enabling seamless continuous delivery and deployment (CI/CD) workflows. This review highlights the synergistic benefits of combining IaC and GitOps, including enhanced operational efficiency, faster scaling, and stronger governance. However, the review also identifies key challenges in their implementation, such as toolchain integration, complexity in large-scale environments, and ensuring governance and security across cloud platforms. Case studies and emerging trends, including AI-powered automation and multi-cloud strategies, are discussed to illustrate real-world applications and future opportunities. The paper concludes by identifying areas for future research, including the development of advanced automation tools, multi-cloud governance frameworks, and improved security compliance mechanisms.

Continuous Delivery is an agile software development practice in which developers frequently integrate changes into the main development line and produce releases of their software. An automated Continuous Integration infrastructure builds and tests these changes. Claimed advantages of CD include early discovery of (integration) errors, reduced cycle time, and better adoption of coding standards and guidelines. This paper reports on a study in which we surveyed 152 developers of a large financial organization (ING Nederland), and investigated how they adopt a Continuous Integration and delivery pipeline during their development activities. In our study, we focus on topics related to managing technical debt, as well as test automation practices. The survey results shed light on the adoption of some agile methods in practice, and sometimes confirm, while in other cases, confute common wisdom and results obtained in other studies. For example, we found that refactoring tends to be performed together with other development activities, technical debt is almost always self-admitted, developers timely document source code, and assure the quality of their product through extensive automated testing, with a third of respondents dedicating more than 50% of their time to do testing activities.

Software stability and reliability are the core concerns of DevOps. They are improved by tightening the collaboration between developers and operators in cross-functional teams on the one hand and by automating operations through continuous integration (CI) and infrastructure as code (IaC) on the other hand. Ideally, teams in DevOps are fully independent. Still, their applications often depend on each other in practice, requiring them to coordinate their deployment through centralization or manual coordination. With this work, we propose and implement the novel IaC solution µs ([mju:z] ”muse”), which automates deployment coordination in a decentralized fashion. µs is the first approach that is compatible with the DevOps goals as it enables truly independent operations of the DevOps teams. We define our research problem through a questionnaire survey with IT professionals and evaluate the solution by comparing it to other modern IaC approaches, assessing its performance, and applying it to existing IaC programs.

In the evolving landscape of software development, DevOps has emerged as a pivotal philosophy, blending software development (Dev) with information technology operations (Ops) to shorten the development lifecycle and provide continuous delivery with high software quality.Central to this paradigm is the concept of Infrastructure as Code (IaC), a practice that programmatically manages and provisions infrastructure through code rather than through manual processes. This paper delves into the integral role of IaC in actualizing DevOps objectives, highlighting how it catalyzes automation, ensures consistency and standardization, facilitates rapid deployment, and enhances collaboration. Through a comprehensive analysis, we explore how IaC not only automates and streamlines operations but also embeds compliance and security into the development process, aligning closely with the DevOps ethos of swift, reliable, and frequent deployments. Additionally, the paper addresses the challenges inherent in implementingIaC within a DevOps framework and proposes best practices to navigate these complexities effectively.The future of software development and IT operations is envisaged as a continuum where IaC and DevOps co -evolve, paving the way for more agile, efficient, and secure IT infrastructure management.

Web applications are essential to the digital world but remain susceptible to common threats like SQL Injection (SQLi) and Cross-Site Scripting (XSS). Automated vulnerability scanners are vital for security, yet many current solutions are too slow and resource-intensive. This makes them impractical for rapid development cycles or for integration into modern Software-Defined Security (SDS) systems. This paper proposes that focused, lightweight scanners are wellsuited as specialized modules within SDS, offering quick, targeted feedback for immediate security policy enforcement. To demonstrate this, we developed a lightweight, Pythonbased automated vulnerability scanner. Its design emphasizes a focused, modular architecture, using Python’s efficient processing and minimal libraries for enhanced performance. We quantitatively assessed its effectiveness, benchmarking detection speed and accuracy (true positive and false positive rates) against the Open Web Application Security Project Zed Attack Proxy (OWASP Zed) Attack Proxy on a standard vulnerable test site. Results show a significant performance improvement: the scanner reduced average scan time from about 55 minutes to just 58.7 seconds. In terms of accuracy, it successfully identified and confirmed an exploitable SQL Injection vulnerability with a low false positive rate. This research confirms that a targeted, lightweight approach can effectively close the performance gap in automated scanning, providing a practical solution for environments needing fast feedback, like Continuous Integration and Continuous Delivery (CI/CD) pipelines. Future work will expand its coverage to include more complex vulnerabilities while retaining its performance benefits.

The rapid pace of software development and deployment in today's digital world demands an integrated approach to security, particularly in Continuous Integration/Continuous Deployment (CI/CD) pipelines. Traditional approaches to security, where it is added at the end of the development lifecycle, have proven inadequate in addressing the complexities and vulnerabilities introduced by fast-moving development cycles. DevSecOps (Development, Security, and Operations) represents an evolution of the DevOps culture that integrates security as an essential component throughout the development process, rather than as an afterthought. This paper explores the role of DevSecOps in ensuring continuous security integration within CI/CD pipelines, focusing on its principles, practices, and impact on both security and development efficiency. DevSecOps emphasizes the shift-left approach, where security is integrated early in the software development lifecycle (SDLC) to identify and mitigate vulnerabilities before they reach production. By embedding security practices into CI/CD workflows, organizations can achieve continuous security validation and testing in tandem with software development activities. Key components of a successful DevSecOps implementation include automated security testing, real-time vulnerability scanning, infrastructure as code (IaC) security, and threat intelligence integration. Through the use of tools like static application security testing (SAST), dynamic application security testing (DAST), and software composition analysis (SCA), DevSecOps facilitates the continuous monitoring of code, configurations, and infrastructure for security issues. This paper also examines the cultural shift required to adopt DevSecOps within development teams. It highlights the importance of fostering collaboration between development, security, and operations teams to ensure seamless integration of security practices into the CI/CD pipeline. By aligning security teams with development and operations, DevSecOps fosters a culture of shared responsibility for security, breaking down silos that traditionally hinder effective security integration.

As enterprises embrace multi-cloud strategies to enhance agility, reduce vendor lock-in, and meet regulatory requirements, the need for scalable and reliable infrastructure management becomes critical. GitOps a paradigm that leverages Git as the single source of truth for declarative infrastructure offers a transformative approach to manage Infrastructure as Code (IaC) across heterogeneous cloud environments. This paper explores scalable GitOps models tailored for multi-cloud deployments, highlighting key architectural patterns, toolchains, and workflows that enable secure, auditable, and automated infrastructure operations. The study analyzes the strengths and limitations of leading GitOps tools such as ArgoCD and Flux in coordinating cross-cloud configurations and reconcile loops. The study also examines strategies for repository structuring, modularization of IaC, policy-as-code integration, and dynamic secrets management to support enterprise-scale deployments. The study propose a reference architecture that addresses the challenges of scalability, compliance, and resilience in multi-cloud GitOps workflows. My findings demonstrate that, when correctly implemented, GitOps can serve as a powerful operational model for achieving continuous delivery and governance in complex cloud-native ecosystems.

Continuous Delivery refers to a software development practice where members of a team frequently integrate their work, so that the process of delivery can be easily conducted. However, this continuous integration and delivery requires a reliable collaboration between development and IT operation teams. The DevOps practices support this collaboration since they enable that the operation staff making use of the same infrastructure as developers for their systems work. Our study aims at presenting a practical DevOps implementation and analyzing how the process of software delivery and infrastructure changes was automated. Our approach follows the principles of infrastructure as code, where a configuration platform – PowerShell DSC – was used to automatically define reliable environments for continuous software delivery. In this context, we defined the concept of “stage for dev”, also using the Docker technology, which involves all the elements that enable members of a team to have the same production environment, locally configured in their personal machines and thus empowering the continuous integration and delivery of system releases.

The healthcare industry is increasingly vulnerable to cyberattacks, with sensitive patient data and critical operations becoming prime targets for malicious actors. In response, healthcare organizations are embracing the Zero Trust security model, which operates on the principle of "never trust, always verify." This model assumes that threats can emerge both outside and within the network and requires strict identity verification for every user and device attempting to access resources, regardless of their location. When combined with DevOps practices, Zero Trust strengthens security while maintaining the speed and agility necessary for modern healthcare systems. By embedding security into every phase of the development lifecycle, DevOps enables healthcare organizations to continuously monitor, test, and update their systems, ensuring that security measures evolve alongside emerging threats. Infrastructure as Code (IaC) plays a key role in this integration, automating the deployment and management of secure, scalable infrastructure, while continuous integration/continuous delivery (CI/CD) pipelines ensure that updates are deployed swiftly and securely. The synergy between Zero Trust and DevOps transforms healthcare IT operations, enabling real-time monitoring, dynamic threat response, and better protection of sensitive patient data. This article explores how healthcare providers are adopting this approach to meet compliance requirements, improve system resilience, and safeguard patient privacy, all while maintaining the operational efficiency and innovation required in today?s fast-paced digital landscape. With Zero Trust and DevOps working hand in hand, healthcare organizations can build a more secure, agile, and future-proof foundation for their digital transformation initiatives.

Continuous Integration and Delivery Pipelines Evolution and Restructuring: A Qualitative and Quantitative Study

This article comprehensively analyzes strategies and architectures for scaling continuous integration and continuous delivery (CI/CD) pipelines to support high-throughput engineering teams. As organizations grow from dozens to hundreds or thousands of developers, traditional pipeline architectures often become bottlenecks that impede development velocity and increase infrastructure costs. The article examines the evolution from centralized to distributed CI/CD models, highlighting how cloud-native technologies, Kubernetes orchestration, and ephemeral compute resources enable linear scaling capabilities. Through a detailed article on optimization techniques—including multi-level caching strategies, dependency tracking, and dynamic test distribution—the article demonstrates how organizations can maintain consistent performance while controlling costs. Article case studies from microservices environments reveal that properly implemented distributed pipelines can reduce build times while supporting significantly higher deployment frequencies. The article addresses technical implementation and developer experience considerations, providing a roadmap for organizations at different growth stages. The article indicates that the strategic implementation of distributed CI/CD architectures represents a competitive advantage for engineering organizations, enabling them to maintain productivity and innovation cycles even as they scale significantly.

Modern heterogeneous System-on-Chip (SoC) devices combine CPUs, GPUs, FPGAs, and AI accelerators into compact and energy-efficient platforms. However, the construction of bootable images for these systems remains complex because of fragmented tools, opaque dependencies, and inflexible workflows. SoCks (System-on-Chip blocks) introduces a lightweight and modular build framework that partitions an SoC image into encapsulated blocks, each built independently with standardized interfaces. This modularization simplifies development, encourages component reuse, enables distributed collaboration, and integrates seamlessly with modern Continuous Integration and Continuous Delivery (CI/CD) pipelines. Within back-end development for the Phase-2 upgrade of the Compact Muon Solenoid (CMS) experiment, SoCks has been used to build the bootable image for the Kria K26 System-on-Module (SoM) on the Serenity-S data processing board. The image utilizes an AlmaLinux-based operating system that employs a layered root file system, combining a read-only network-mounted lower layer with a writable local upper layer, to ensure consistency across boards. Furthermore, the Serenity-S image is optimized for a fully network-based boot process, allowing synchronized deployment across multiple Serenity-S boards and remote updates.

The article describes how artificial intelligence has changed the field of platform engineering in the context of continuous integration and continuous delivery (CI/CD) pipelines. Intelligent, self-healing systems with the ability to optimise themselves autonomously are the next paradigm shift in the integration of AI capabilities that changes the process of manual management to a more intelligent and self-aware system. It is an investigation of how machine learning algorithms can be used to improve test selection, provide high-level monitoring of pipelines, and allow autonomous failure remediation. The article reveals key concerns to be considered by organisations that are exploring AI-enhanced platform engineering, such as data quality requirements, model selection approaches, and incorporating existing toolchains. It also explores new trends that are set to transform software delivery ecosystems, such as generative AI to define the infrastructure, federated learning with engineering teams, and end-to-end optimization at the entire software delivery lifecycle. Through a combination of the results of various studies, this article will give a general overview of how AI is transforming the field of platform engineering and give a basis for what is to be expected in the evolution of intelligent automation to achieve software delivery.

Modern software development approaches rely extensively on tools. Motivated by practices such as continuous integration, deployment and delivery, these tools are used in a fashion where data are automatically accumulated in different databases as a side-effect of everyday development activities. In this paper we introduce an approach for software engineering data visualization as a mash up that combines data from issue management, software development and production use. The visualization can show to all stake holders how well continuous delivery is realized in the project. The visualization clearly shows the time spent to specify and develop the features as well the length of the delivery cycle. Further more the visualization shows how much work is unfinished and waiting for delivery. This can help the development team to decrease the amount of unfinished work and by that help them to keep up in continuous delivery mind set. In addition to development data usage of the features is also visualized.

As enterprises increasingly adopt Azure DevOps for continuous integration and continuous deployment (CI/CD), ensuring robust security and compliance in cloud-based DevOps pipelines has become a critical challenge. This article explores the complex landscape of security and compliance within Azure DevOps, focusing on the hurdles faced by organizations during deployment and operation at scale. We delve into common security risks, such as unauthorized access, data breaches, and configuration vulnerabilities, while also addressing the complexities of adhering to industry-specific compliance frameworks, including GDPR, HIPAA, and SOC 2. The study reviews current best practices for integrating security into the DevOps pipeline, emphasizing the importance of Infrastructure as Code (IaC), identity and access management (IAM), automated security testing, and monitoring tools. Additionally, the article evaluates how Azure DevOps tools, such as Azure Security Center, Azure Policy, and Azure Blueprints, can help streamline compliance management and mitigate risks. Through real-world case studies and expert interviews, this article provides practical solutions for enterprises seeking to enhance their security posture while ensuring compliance within their Azure DevOps workflows. The findings highlight the importance of automated security checks, compliance automation, and the need for a culture of security across DevOps teams to address the challenges of scaling enterprise deployments securely and efficiently.