Kloudfuse version 3.0 enhances observability by introducing continuous profiling to identify performance bottlenecks, enabling DevOps teams to target specific lines of code more effectively.
The Prophet tool boosts anomaly detection and forecasting accuracy by factoring in missing data and seasonality, ensuring that confidence bounds are reliable across varying dataset sizes.
With K-Lens visualization, Kloudfuse utilizes outlier detection techniques to streamline analysis of numerous attributes, expediting the debugging process and improving incident resolution times.
Introducing FuseQL provides multi-dimensional log query capabilities, allowing for advanced filtering and aggregations, while also integrating powerful search tools like LogFingerprinting for improving data management.
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