The Future of SRE and Observability: Leveraging AI, Automation, and Culture for Resilience
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Abstract
Modern systems have reached unprecedented complexity levels which requires engineering teams to implement resilient methodologies. This paper examines the evolution of Site Reliability Engineering (SRE) and observability through the lens of emerging technologies including AI and predictive analytics. The selected tools allow engineering teams to build systems which demonstrate reliability while maintaining scalability and efficiency. Modern tool adoption combined with cultural realignment and shared reliability responsibility is essential for companies to remain competitive. Site Reliability Engineering and observability practices extend beyond technical solutions to serve as mechanisms that bring teams together toward common objectives. The research indicates that organizations must both improve continuously and adjust to evolving technological advancements while meeting user expectations.
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References
Datadog, “‘Monitoring and observability platform.’ Available:”
N. Relic, “‘Application performance monitoring.’ Available:”
Splunk, “‘Data platform for security and observability.’ Available:”
Elasticsearch, “‘Distributed search and analytics engine.’ Available:”
Logstash, “‘Server-side data processing pipeline.’ Available:”
Moogsoft, “‘AI-driven observability platform.’ Available:”
PagerDuty, “‘Incident response platform.’ Available:”
Prometheus, “‘Open-source monitoring and alerting toolkit.’ Available:”
Grafana, “‘Visualization and analytics software.’ Available:”
Kibana, “‘Data visualization and exploration.’ Available:”