LogClaw

AI SRE that deploys in your VPC. Real-time anomaly detection, trace-correlated incident tickets, and AI root cause analysis — your logs never leave your infrastructure.

TL;DR — Try It

Option A: Managed Cloud (no install — fastest)

Try the full experience instantly at console.logclaw.ai — includes AI root cause analysis, API key management, multi-tenant isolation, and the complete incident pipeline. No Docker required.

Option B: Docker Compose (self-hosted, no Kubernetes)

curl -O https://raw.githubusercontent.com/logclaw/logclaw/main/docker-compose.yml
curl -O https://raw.githubusercontent.com/logclaw/logclaw/main/otel-collector-config.yaml
docker compose up -d

Open http://localhost:3000 — the LogClaw stack is running:

• Dashboard (:3000) — incidents, log ingestion, config
• OTel Collector (:4317 gRPC, :4318 HTTP) — send logs via OTLP
• Bridge (:8080) — anomaly detection + trace correlation
• Ticketing Agent (:18081) — AI-powered incident management
• OpenSearch (:9200) — log storage + search
• Kafka (:9092) — event bus

All images are pulled from ghcr.io/logclaw/ — no registry auth required.

Note: The local stack runs in single-tenant mode with LLM-powered root cause analysis disabled. For AI RCA, API key management, and multi-tenant isolation, use the managed cloud or deploy to Kubernetes with LLM_PROVIDER=claude|openai|ollama.

Option C: Kind Cluster (full Kubernetes stack)

git clone https://github.com/logclaw/logclaw.git && cd logclaw
./scripts/setup-dev.sh

This creates a Kind cluster, installs all operators and services, builds the dashboard, and runs a smoke test. Takes ~20 minutes on a 16 GB laptop.

Container Images

All LogClaw images are published to GHCR as public packages:

Pull any image directly:

docker pull ghcr.io/logclaw/logclaw-dashboard:stable

See It in Action

Incident Management	AI Root Cause Analysis
Log Ingestion	Dashboard Overview

Live demo: console.logclaw.ai | Video walkthrough: logclaw.ai

Open Source vs Cloud vs Enterprise

... View full README on GitHub