Abstract

Abstract

Abstract
Creating and using software documentation presents numerous challenges, namely in what concerns the expression of knowledge structures, consistency maintenance and classification. Adaptive Software Artifacts is a flexible approach to expressing structured contents that tackles these concerns, and that is being realized in the context of a Software Forge. Copyright © 2013 by the Association for Computing Machinery, Inc. (ACM).

Abstract
Software architecture is reflected across multiple artifacts, making it difficult to communicate without proper documentation, which often becomes outdated or unreliable. We propose an approach to support Living Documentation by generating architectural diagrams from Docker Compose files. We implement our approach as a prototype tool that we name Infragenie and conduct an empirical study to show the viability of the approach. The study involved sending questionnaires to maintainers of 378 GitHub repositories. We received 36 responses. Infragenie-generated diagrams were rated as better or much better for most of the 12 projects with previous diagrams. Over 70% of the respondents agreed that our approach improved documentation completeness, consistency, and accessibility, and more than 90% recognized its effectiveness in capturing key architectural elements. We conclude that by using Docker Compose files we were able to provide useful architectural diagrams.

Abstract

Abstract
Observability helps ensure the reliability and maintainability of cloud-native applications. As software architectures become increasingly distributed and subject to change, it becomes a greater challenge to diagnose system issues effectively, often having to deal with fragmented observability and more difficult root cause analysis. This paper builds upon our previous work and introduces three design patterns that address key challenges in monitoring cloud-native applications. Distributed Tracing improves visibility into request flows across services, aiding in latency analysis and root cause detection, Application Metrics provides a structured approach to instrumenting applications with meaningful performance indicators, enabling real-time monitoring and anomaly detection, and Infrastructure Metrics focuses on monitoring the environment in which the system is operated, helping teams assess resource utilization, scalability, and operational health. These patterns are derived from industry practices and observability frameworks and aim to offer guidance for software practitioners.