Kloudfuse offers comprehensive analytics, reporting, and dashboards across all observability streams, including metrics, events, logs, and traces. Powered by Apache Pinot, our real-time OLAP datastore ensures ultra-low-latency analytics at high throughput, designed for high volume observability data.
Kloudfuse’s patent-pending fingerprinting technology automatically extracts patterns from log messages during ingestion. This helps in analyzing logs by severity, source, version, and other parameters, aiding root cause analysis and detecting unexpected log signatures as anomalies for further investigation.
Visualize service dependencies and application relationships with interactive service maps and topology views. Investigate incidents in real time with drill-down dashboards or query using languages like PromQL, LogQL, TraceQL, GraphQL, and SQL. Kloudfuse also supports both embedded and external Grafana dashboards, providing users with flexible access and customization options.
Utilize our advanced anomaly and outlier detection methods, including rolling quantile, SARIMA, DBScan, and seasonal decomposition. For root cause analysis, we apply the Pearson Correlation Coefficient to correlate MELT data and employ techniques like Prophet to gain deeper insights.
