argus

README

🔭 Argus

AI-powered observability CLI for SREs.

Argus connects to your Signoz instances and uses Anthropic Claude to analyze logs, metrics, and traces with natural language queries.

"Why is latency high on the payments service?" — Just ask Argus.

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Features

• 🤖 Natural language queries — Ask questions about your infrastructure in plain English
• 📡 Multi-instance support — Manage multiple Signoz environments (production, staging, etc.)
• 📋 Real log/trace/metric queries — Direct integration with Signoz query_range API (v3 + v5)
• 🔧 Service discovery — List services with call counts and error rates
• 📊 Dashboard view — Combined overview of health, services, and recent errors
• ⚡ Streaming AI responses — Real-time analysis output as tokens arrive
• 🎨 Beautiful terminal UI — Severity-colored logs, formatted traces, metric tables
• 🔧 Simple configuration — YAML config, multiple profiles, easy setup

Installation

From source

go install github.com/lbarahona/argus/cmd/argus@latest

Binary releases

Download from GitHub Releases.

Build from source

git clone https://github.com/lbarahona/argus.git
cd argus
make build
# Binary at ./bin/argus

Quick Start

# 1. Initialize configuration
argus config init

# 2. Check instance health
argus status

# 3. List services
argus services

# 4. Query logs with AI analysis
argus logs auth-service --query "any errors in the last hour?"

# 5. View traces
argus traces frontend --duration 30

# 6. Quick dashboard
argus dashboard

# 7. Ask free-form questions
argus ask "why is latency high on the payments service?"

Commands

Command	Description
argus version	Print version information
argus config init	Interactive configuration setup
argus config add-instance	Add a new Signoz instance
argus instances	List configured instances
argus status	Health check all instances
argus services	List services with call counts and error rates
argus logs [service]	Query and analyze logs
argus traces [service]	Query distributed traces
argus metrics [metric]	Query metrics
argus dashboard	Combined overview dashboard
argus ask [question]	Free-form AI analysis

Logs

# Query logs for a service
argus logs my-service

# Filter by severity
argus logs my-service --severity ERROR

# With AI analysis
argus logs my-service --query "find authentication failures"

# Specify instance, duration, and limit
argus logs my-service -i staging -d 120 -l 50

Services

# List all services with error rates
argus services

# From a specific instance
argus services -i production

Traces

# Query traces for a service
argus traces frontend

# With duration and limit
argus traces api-gateway -d 30 -l 50

# With AI analysis
argus traces frontend --query "find slow requests over 1s"

Metrics

# Query a specific metric
argus metrics cpu_usage

# With AI analysis
argus metrics http_request_duration --query "any anomalies?"

Dashboard

# Quick overview of everything
argus dashboard

# Look back further for errors
argus dashboard -d 120

Ask

# Free-form questions — gathers context from Signoz automatically
argus ask "what services had the most errors today?"
argus ask "is there a correlation between high CPU and slow responses?"

Configuration

Config is stored at ~/.argus/config.yaml:

anthropic_key: sk-ant-...
default_instance: production
instances:
  production:
    url: https://signoz.example.com
    api_key: your-signoz-api-key
    name: Production
    api_version: v3  # v3 for self-hosted, v5 for Signoz Cloud
  staging:
    url: https://signoz-staging.example.com
    api_key: your-staging-key
    name: Staging
    api_version: v5

API Version

• v3 (default) — For self-hosted Signoz instances (/api/v3/query_range)
• v5 — For Signoz Cloud (/api/v5/query_range)

Requirements

• A Signoz instance (self-hosted or cloud)
• An Anthropic API key for AI analysis features

Contributing

Contributions are welcome! Please open an issue or submit a PR.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'feat: add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

MIT © Lester Barahona