Parseable: The Exascale Open Observability Datalake

Parseable is a high-performance, open-core observability infrastructure designed to function as a columnar data lake. It is specifically engineered to manage telemetry data at a massive scale, capable of processing $\approx 100,000,000$ time-series every minute. By leveraging OTel (OpenTelemetry) native integration and smart caching, it provides a cost-effective alternative to traditional observability stacks.

🏗️ Architectural Philosophy

Parseable moves away from rigid, expensive proprietary databases toward an open, stateless design. At its core, it utilizes the open Parquet format, ensuring that data remains portable and accessible.

Key Technical Pillars:

• Columnar Design: Specifically built to resolve the "high cardinality" problem that plagues traditional time-series databases.
• Object Store Native: Data lives in open formats on your own storage, ensuring vendor lock-in zero vendor lock-in.
• Unified Pipeline: A single binary handles the entire observability suite:
  • Metrics
  • Logs
  • Distributed Traces
  • Events

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🤖 AI-Driven Investigation

Parseable integrates Large Language Models (LLMs) and traditional Machine Learning to transform raw telemetry into actionable intelligence. Instead of manually hunting through dashboards, an AI Agent monitors your system $24/7$.

The AI Workflow:

1. Detection: The agent identifies an anomaly (e.g., an error rate spike of $12.6\%$ compared to a $1.2\%$ baseline).
2. Analysis: It automatically scans across all signals—logs, metrics, and traces.
3. Resolution: It pinpoint the exact root cause.

AI Root Cause Analysis Example: "Investigation complete: The underlying issue is a Connection pool exhaustion within the checkout-service.

• Impact: $6.45\text{K}$ users affected.
• Duration: $7\text{m } 32\text{s}$.
• Error Rate: $12.6\%$."

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🚀 Deployment & Versions

Whether you need a community-driven tool or an enterprise-grade platform, Parseable offers flexible deployment paths across public or private clouds.

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🔌 Ecosystem & Integrations

Parseable doesn't replace your existing tools; it enhances them. With over 60+ integrations, it fits into any modern CNCF stack.

Supported Integrations include:

• Data Sources/Agents: OpenTelemetry, Fluent Bit, Fluentd, Vector, eBPF.
• Infrastructure: Kubernetes, AWS, Azure.
• Storage/Streaming: MinIO, Tigris Data, Kafka, Redpanda.
• Visualization/Query: Prometheus, Grafana.
• AI/LLMs: OpenAI, Anthropic, vLLM.

Specialized Tooling

• MCP: Connects AI agents to live telemetry via structured tools.
• Slack Bot: Brings operational answers and investigations directly into chat.
• PAI: Automates the instrumentation of Kubernetes workloads.
• PB CLI: Allows for telemetry investigation directly from the terminal.
• OTex: An AI-powered observability engineer for planning and reviewing telemetry.

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🛡️ Security and Compliance

For teams with strict data residency and security requirements, Parseable provides enterprise-grade controls.

• Compliance: GDPR Certified and SOC 2 Type II.
• Ownership: You maintain complete ownership of your telemetry data.
• Privacy: Designed for security-conscious teams requiring private cloud deployments.

🛠️ Getting Started

You can deploy Parseable quickly using the following command:

# Quick setup via curl
$ curl -fsSL https://logg.ing/setup | bash

By unifying logs, metrics, and traces into a single, queryable open format, Parseable allows teams to maintain full-fidelity data without the prohibitive costs of traditional observability platforms.