EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·6d ago·5 min read
Show HN: Parseable, an open observability datalake, handles 100M time-series/min
TL;DR
Parseable is an open observability datalake designed for telemetry data, capable of processing 100 million time-series per minute. Built in Rust, it offers a cost-effective solution for cloud-native data management.
✦ Why It Matters
Consider deploying Parseable to improve your telemetry data management and observability today.
Key Takeaways
- Deploy Parseable on public or private cloud environments.
- Utilize open Parquet format for data storage.
- Configure telemetry agents for seamless data collection.
- Leverage comprehensive views for alerts and metrics.
Full Summary
Parseable is a specialized observability datalake that efficiently handles telemetry data, processing up to 100 million time-series per minute. It is built using Rust, a programming language known for its performance and safety.
The platform follows an open core model, utilizing open Parquet format and adhering to open standards, making it accessible and flexible for various deployment scenarios. Users can deploy Parseable on public or private clouds and connect it to an object store for data management.
The system supports telemetry agents for easy configuration and provides comprehensive views including alerts, dashboards, logs, metrics, and distributed traces. This architecture allows for scalable data management as needs grow, making it a valuable tool for organizations looking to enhance their observability capabilities.