Cross-Client Anomaly Detection

System Monitoring Benchmarking Tableau

A unified benchmarking dashboard designed to detect performance deviations across multiple clients simultaneously, ensuring consistent service reliability.

The Challenge

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Multiple clients experienced inconsistent performance, but the engineering team lacked a unified way to detect and prioritize anomalies across the entire client base[cite: 173]. There was no standardized method to benchmark performance KPIs simultaneously for all clients, leading to fragmented analysis.

The Solution

I developed a Cross-Client Anomaly Detection framework that aggregated data into a single operational view.

Benchmarking: Developed cross-client models using statistical thresholds and moving averages to detect performance deviations[cite: 174].
Visualization: Built a large-scale Tableau dashboard providing a unified view of metrics like ATRT, hang counts, and OOM incidents across all clients[cite: 108, 174].
Standardization: Analyzed application performance metrics across systems to create standardized reporting requirements[cite: 112].

The Impact

Proactive Management: Improved anomaly detection efficiency by 30%, enabling teams to address degradation proactively before it impacted clients[cite: 175].
Workflow Streamlining: Streamlined analysis workflows across engineering teams, significantly speeding up resolution times[cite: 116].
Unified View: The dashboard became the central platform for monitoring operational performance across the organization[cite: 114].