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Show HN: Parseable, an open observability datalake, handles 100M time-series/min

parseable.com84 points24 comments
Screenshot of Show HN: Parseable, an open observability datalake, handles 100M time-series/min

Parseable is an open-core, object-store-native observability datalake built in Rust that unifies logs, metrics, traces and events in a columnar Parquet-backed format. It is OpenTelemetry-native, exposes PromQL and SQL queries, and is designed to handle extreme cardinality and scale (marketed for 100M time‑series/min) by keeping data in a stateless, columnar layout on cloud or private object storage. The product bundles a full observability UI (alerts, dashboards, service maps, traces) and a suite of tools (CLI, Slack bot, Kubernetes instrumentation, AI connectors) while emphasizing compression, distributed queries, and predictable cost efficiency for high-volume telemetry.

Deployment options span self-hosted AGPLv3 OSS, managed cloud, and enterprise offerings with BYOC, advanced access controls, governance, and priority support. AI-assisted investigation features combine LLMs and traditional ML to detect anomalies across signals and generate root-cause analysis from logs, metrics and traces. Integrations include Prometheus, Grafana, OpenTelemetry, Kafka/Redpanda, cloud providers, and LLM providers. Security and compliance are highlighted (GDPR, SOC 2 Type II) alongside claims of no vendor lock-in and full data ownership, positioning Parseable for teams seeking scalable, cost‑efficient, open-format observability with enterprise controls and AI-enabled troubleshooting.

Read on parseable.com24 comments on Hacker News

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