GoKawiilParseable's Data Lake Processes 100 Million Time-Series Data Points per Minute
Parseable has announced its open observability data lake capable of handling up to 100 million time-series data points every minute. The platform leverages large language models and traditional machine learning to analyze telemetry data, detect anomalies, and identify root causes in real-time. Recently, it identified a spike in error rates caused by exhausted connection pools in a checkout service, affecting over 6,400 users for more than seven minutes.
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This development highlights the increasing capacity of observability tools to process vast quantities of telemetry data rapidly, which could enable more proactive and precise system monitoring. It positions Parseable to support large-scale, real-time diagnostics that are critical for maintaining high availability in complex systems.
- Parseable's data lake can process 100M time-series points per minute.
- The platform uses AI and ML for anomaly detection and root cause analysis.
- Real-time insights can help reduce system downtime and improve reliability.
Source: parseable.com, 2026-10-06
Published there as: “Show HN: Parseable, an open observability datalake, handles 100M time-series/min”
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