The Role of Predictive Analytics in Modern SRE Practices: A Path to Self-Healing Systems
DOI:
https://doi.org/10.32628/CSEIT251112350Keywords:
Site Reliability Engineering (SRE), Predictive Analytics, Self-Healing Systems, Machine Learning Operations, Infrastructure AutomationAbstract
The integration of predictive analytics into Site Reliability Engineering (SRE) practices represents a transformative shift in managing complex digital systems. This article examines how predictive analytics is revolutionizing traditional SRE approaches, enabling organizations to transition from reactive incident management to proactive system maintenance. The article explores the evolution of SRE practices, analyzing how machine learning and statistical models enhance pattern recognition, automate response mechanisms, and optimize resource allocation. The article demonstrates that predictive analytics not only improves technical performance but also delivers significant environmental, economic, and societal benefits. Through comprehensive analysis of implementation challenges and best practices, the article provides insights into successful adoption strategies. The article indicates that organizations implementing predictive analytics in SRE achieve substantial improvements in service reliability, cost efficiency, and operational effectiveness, paving the way for truly self-healing systems.
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