Integration of DevOps Practices for Continuous Delivery and System Optimization
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Abstract
The growing demand for rapid software delivery and efficient system performance has led to the widespread adoption of DevOps practices in modern software engineering. This study evaluates the integration of DevOps practices for achieving continuous delivery and system optimization by comparing traditional development models, Agile methodologies, DevOps, and DevOps combined with continuous delivery (CD). The analysis is supported by three figures illustrating key performance metrics, including deployment frequency, lead time, change failure rate, mean time to recovery (MTTR), response time, throughput, resource utilization, and system availability. The findings indicate that traditional development approaches exhibit low deployment frequency, high lead time, and poor system performance due to limited automation and rigid processes. Agile methodologies improve flexibility and reduce development cycles; however, they provide only moderate improvements in operational performance. In contrast, DevOps practices significantly enhance system efficiency by integrating development and operations, enabling continuous integration, automated testing, and faster deployment cycles. The results highlight the importance of automation, collaboration, and continuous monitoring in achieving system optimization. By enabling rapid and reliable software releases, DevOps practices contribute to improved system reliability and scalability in dynamic environments. This study provides valuable insights for organizations seeking to optimize their software development processes and adopt modern DevOps practices to achieve continuous delivery and high system performance.
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References
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