Exploring Maintainability Assurance Research for Service- and Microservice-Based Systems: Directions and Differences

To ensure sustainable software maintenance and evolution, a diverse set of activities and concepts like metrics, change impact analysis, or antipattern detection can be used. Special maintainability assurance techniques have been proposed for service- and microservice-based systems, but it is difficult to get a comprehensive overview of this publication landscape. We therefore conducted a systematic literature review (SLR) to collect and categorize maintainability assurance approaches for service-oriented architecture (SOA) and microservices. Our search strategy led to the selection of 223 primary studies from 2007 to 2018 which we categorized with a threefold taxonomy: a) architectural (SOA, microservices, both), b) methodical (method or contribution of the study), and c) thematic (maintainability assurance subfield). We discuss the distribution among these categories and present different research directions as well as exemplary studies per thematic category. The primary finding of our SLR is that, while very few approaches have been suggested for microservices so far (24 of 223, ?11%), we identified several thematic categories where existing SOA techniques could be adapted for the maintainability assurance of microservices

Microservice Architecture Reconstruction and Visualization Techniques: A Review

Microservice system solutions are driving digital transformation; however, fundamental tools and system perspectives are missing to better observe, understand, and manage these systems, their properties, and their dependencies. Microservices architecture leads towards decentralization, which implies many advantages to system operation; it, however, brings challenges to their development. Microservice systems often lack a system-centric perspective that would help engineers better cope with system evolution and quality assessment. In this work, we explored microservice-specific architecture reconstruction based on static analysis. Such reconstruction typically results in system models to visualize selected system-centric perspectives. Conventional models involve 2D methods; however, these methods are limited in utility when services proliferate. We considered various architectural perspectives relevant to microservices and assessed the relevancy of the traditional method, comparing it to alternative data visualization using 3D space. As a representative of the 3D method, we considered a 3D graph model presented in augmented reality. To begin testing the feasibility of deriving such perspectives from microservice systems, we developed and implemented prototype tools for software architecture reconstruction and visualization of compared perspectives. Using these prototypes, we performed a small user study with software practitioners to highlight the potentials and limitations of these innovative visualizations used for common practitioner reasoning and tasks

Microvision: Static analysis-based approach to visualizing microservices in augmented reality

Microservices are supporting digital transformation; however, fundamental tools and system perspectives are missing to better observe, understand, and manage these systems, their properties, and their dependencies. Microservices architecture leans toward decentralization, which yields many advantages to system operation; it, however, brings challenges to their development. Microservices lack a system-centric perspective to better cope with system evolution and quality assessment. In this work, we explore microservice-specific architecture reconstruction based on static analysis. Such reconstruction typically results in system models to visualize selected system-centric perspectives. Conventional models are limited in utility when the service cardinality is high. We consider an alternative data visualization using 3D space using augmented reality. To begin testing the feasibility of deriving such perspectives from microservice systems, we developed and implemented prototype tools for software architecture reconstruction and visualization of compared perspectives

Microservice Transition and its Granularity Problem: A Systematic Mapping Study

Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying "micro-ing" architectures. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and -practice related to reasoning about microservice granularity; it reviews modelling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table

Ensuring and Assessing Architecture Conformance to Microservice Decomposition Patterns

Microservice-based software architecture design has been widely discussed, and best practices have been published as architecture design patterns. However, conformance to those patterns is hard to ensure and assess automatically, leading to problems such as architectural drift and erosion, especially in the context of continued software evolution or large-scale microservice systems. In addition, not much in the component and connector architecture models is specific (only) to the microservices approach, whereas other aspects really specific to that approach, such as independent deployment of microservices, are usually modeled in other views or not at all. We suggest a set of constraints to check and metrics to assess architecture conformance to microservice patterns. In comparison to expert judgment derived from the patterns, a subset of these constraints and metrics shows a good relative performance and potential for automation

Microservices Security Challenges and Approaches

The fast-paced development cycles of microservices applications increase the probability of insufficient security tests in the development pipelines and consequent deployment of vulnerable microservices. The distribution and ephemeral of microservices create a discoverability challenge for traditional security assessment techniques, especially for microservices being dynamically launched and de-registered. To address this in applications and networks, continuous security assessments are used for vulnerability detection. Detected vulnerabilities are thereafter patched, essentially reducing the chances for security attacks. This paper illustrates the microservices architecture and its components from the security perspective. It investigates, summarizes, and highlights the microservices security-related challenges and the suggested approaches and proposals for facing them. It addresses the security impact on the different microservice architectural perspectives

Towards Optimization of Anomaly Detection Using Autonomous Monitors in DevOps

Continuous practices including continuous integration, continuous testing, and continuous deployment are foundations of many software development initiatives. Another very popular industrial concept, DevOps, promotes automation, collaboration, and monitoring, to even more empower development processes. The scope of this thesis is on continuous monitoring and the data collected through continuous measurement in operations as it may carry very valuable details on the health of the software system. Aim: We aim to explore and improve existing solutions for managing monitoring data in operations, instantiated in the specific industry context. Specifically, we collaborated with a Swedish company responsible for ticket management and sales in public transportation to identify challenges in the information flow from operations to development and explore approaches for improved data management inspired by state-of-the-art machine learning (ML) solutions.Research approach: Our research activities span from practice to theory and from problem to solution domain, including problem conceptualization, solution design, instantiation, and empirical validation. This complies with the main principles of the design science paradigm mainly used to frame problem-driven studies aiming to improve specific areas of practice. Results: We present identified problem instances in the case company considering the general goal of better incorporating feedback from operations to development and corresponding solution design for reducing information overflow, e.g. alert flooding, by introducing a new element, a smart filter, in the feedback loop. Therefore, we propose a simpler version of the solution design based on ML decision rules as well as a more advanced deep learning (DL) alternative. We have implemented and partially evaluated the former solution design while we present the plan for implementation and optimization of the DL version of the smart filter, as a kind of autonomous monitor. Conclusion: We propose using a smart filter to tighten and improve feedback from operations to development. The smart filter utilizes operations data to discover anomalies and timely report alerts on strange and unusual system's behavior. Full-scale implementation and empirical evaluation of the smart filter based on the DL solution will be carried out in future work