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9.2Use Cases for AI in Observability
| Use Case | Input | AI Task | Output |
|---|---|---|---|
| Log anomaly detection | Structured log stream | Identify unusual patterns, new error types, frequency changes | Anomaly alerts with context |
| Latency spike analysis | Trace data + metrics | Correlate latency spikes with deployment events, dependency changes | Root cause hypothesis |
| Error clustering | Error logs | Group similar errors, identify new error classes | Deduplicated error reports |
| Capacity prediction | Time-series metrics | Forecast resource exhaustion | Proactive scaling recommendations |
| Incident summarization | Logs + traces + alerts | Synthesize an incident timeline | Incident summary for postmortem |
| Alert correlation | Multiple alert streams | Identify that 15 alerts share a common root cause | Grouped incident view |