Design and implementation of a monitoring framework for a DevOps life-cycle based on semantic techniques and the OSLC standard

Víctor Álvarez Provencio. (2022). Design and implementation of a monitoring framework for a DevOps life-cycle based on semantic techniques and the OSLC standard. Final Career Project (TFM). Universidad Politécnica de Madrid, ETSI Telecomunicación.

Abstract:
The adoption of the DevOps method has increased considerably in technology companies. This is due to the agility it provides to the life cycle of a software product, as well as the ease of integration between two of the most important fields in technology companies: development and operations. On the one hand, a more fluid relationship between the components of these two fields means faster management of unexpected changes, as well as allowing the automation of deployments or processes that can be of vital importance to respond to an increase in demand for services by the IT company demand for services from users. In the technological architecture of these companies, more than one DevOps tool is usually used, each for the lifecycle phase for which it is useful. This implies the need to have these tools interrelated with each other in a way that is interoperable and easy to manage. This is not always possible, since each tool can have its own configurations and be independent of the rest of the tools. On the other hand, having these tools correctly monitored to be able to respond to anomalous changes or changes in other tools of the architecture becomes one of the fundamental pillars of these companies. In this context, this work proposes a solution to the problem of integration of different DevOps tools through the use of the open standard OSLC and the principles of the semantic web. On the other hand, this work proposes a framework for monitoring software metrics of the Stackstorm tool, as well as social metrics by extracting and analyzing data from social sources such as Twitter. This work is part of the SmartDevOps project whose function is to integrate DevOps tools with semantic technologies and Big Data approach, and this work is intended to serve as an example for a specific use case