Show HN: Parseable, an open observability datalake, handles 100M time-series/min (www.parseable.com)

Parseable has launched an innovative open observability data lake specifically designed to handle massive volumes of telemetry data, processing up to 100 million time-series data points per minute. Built using Rust with a focus on open standards and cost efficiency, Parseable provides a cloud-native architecture that can be deployed in both public and private environments. Its columnar design addresses high cardinality challenges, allowing seamless integration with existing telemetry agents and object storage, making it a versatile option for organizations looking to enhance their observability capabilities. This tool is significant for the AI/ML community as it incorporates both large language models (LLMs) and traditional machine learning models to analyze telemetry data, enabling teams to identify anomalies, summarize trends, and conduct root cause analysis effectively. Parseable’s unified platform supports essential observability features such as alerts, metrics, logs, and distributed traces, all governed by advanced access controls for security-conscious teams. With its open architecture and flexibility in deployment, Parseable empowers organizations to maintain ownership of their data while leveraging powerful observability and analytical capabilities, making it a go-to choice for enterprises seeking robust telemetry solutions.