Log Pattern Recognition And Clustering

via “anomaly-detection-and-log-clustering”

Hi HN, I'm Robel. I built LogClaw because I was tired of paying for Datadog and still waking up to pages that said "something is wrong" with no context.LogClaw is an open-source log intelligence platform that runs on Kubernetes. It ingests logs via OpenTelemetry and detects anomalies

Unique: Uses hybrid statistical + LLM-based clustering that first applies frequency analysis and pattern matching to group obvious duplicates, then uses semantic similarity only for ambiguous cases, balancing speed with accuracy

vs others: More cost-effective than pure LLM-based anomaly detection (e.g., Splunk's AI) because it uses statistical baselines for 80% of cases and reserves LLM inference for edge cases and semantic grouping