खंड 1 No. issue 11 ,Jan 2025 page 886-925 (2025): Advanced Observability Techniques: Revolutionizing Monitoring and Reliability in Site Reliability Engineering (SRE)

Abstract

The rise of microservices, serverless architectures, and multi-cloud deployments in distributed systems has created unique problems that Site Reliability Engineering must solve. The classic methods that monitor system health based on individual metrics, logs, and traces are not enough to ensure preemptive control of system reliability and performance. Observability helps us understand system health through outputs but its existing setup remains limited by data isolation, expensive operations, and insufficient future predictions.

Our research offers new observability solutions to transform how SRE teams work effectively. Key contributions include:

1. AI-Driven Anomaly Detection: Through adaptive thresholding and multivariate analysis the proposed system improves predictive maintenance by detecting abnormalities early and reduces unnecessary alerts by 35%.
2. Dynamic Log Prioritization: The innovative filtering method selects priority log data in real time resulting in 30% lower storage expenses yet preserves diagnostic precision.
3. Hybrid Observability Framework: This system unites log, metric, and trace data in action to provide better resource management and sharper monitoring capabilities while fixing common issues of separated data handling.
4. Contextualized Tracing Mechanisms: Special tracing features for microservices and serverless systems help track distributed events better and spot system blockages faster to achieve 40% quicker recovery times.

Our experiments prove enhanced system performance through better uptime by 15% and reduced expenses for widespread system usage. This research closes important gaps in current observability systems which creates new opportunities for AI-based monitoring tools and scalable analytics solutions. These results help SRE teams move beyond emergency fixes to develop better system strategies which establish new quality standards for distributed systems management.