Capturing uncertainties through log analysis using DevOps Online publication date: Tue, 04-Apr-2023
by Rajeev Kumar Gupta; Arti Jain; Ruchika Kumar; R.K. Pateriya
International Journal of Data Mining, Modelling and Management (IJDMMM), Vol. 15, No. 1, 2023
Abstract: DevOps is an advancement of agile processes which is mainly used to improve the coordination between development and operation teams. Continuous practices survive within the core of the DevOps which ensures efficient pipelines and high-quality delivery of software. Using such practices in a synchronous, business dynamics compliance and ever-changing needs of clients can meet high performance and reliable final products. This research work is an attempt to propose a simplified solution, guideline and tools support for developing and maintaining quality of continuous practices that are used in the DevOps project. The system automates the correlation among various telemetry data to contribute towards enriching log analysis and reduces manual efforts. The proposed system undergoes in-depth analysis of logs, promotes quality assessments and feedback to developers, which in result, helps in deeper problem diagnosis of the telemetry data. In this work, an empirical study is carried out to gain conceptual clarity on integrated pipeline architecture and to address how automation in continuous monitoring accelerates and extends the feedback loop in the system.
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