deta 0.2.4

Infrastructure anomaly detection and monitoring tool

deta

AI Cost Tracking

• 🤖 LLM usage: $0.6000 (4 commits)
• 👤 Human dev: ~$200 (2.0h @ $100/h, 30min dedup)

Generated on 2026-04-30 using openrouter/qwen/qwen3-coder-next

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Infrastructure anomaly detection and monitoring tool for development environments.

Features

• Manifest Scanning: Scans docker-compose, OpenAPI, package.json, and pyproject.toml files up to 3 layers deep
• Topology Building: Builds service dependency graphs and detects anomalies
• Real-time Monitoring: Watches for config changes and probes HTTP health checks
• Anomaly Detection: Detects missing healthchecks, port conflicts, dependency cycles, and hardcoded secrets
• Toon Format: Generates Semcod-compatible toon output for ecosystem integration
• CLI Interface: Simple command-line interface with scan, monitor, and diff commands

Installation

pip install deta

Or with optional dependencies:

pip install deta[docker,toml]

Usage

Scan infrastructure

deta scan /path/to/project --depth 3 --output infra-map.json

Generate graph outputs (YAML / Mermaid / PNG)

# text graph + mermaid + json
deta scan /path/to/project --formats json,yaml,mermaid

# include online checks (localhost probes)
deta scan /path/to/project --formats json,yaml,mermaid --online

# try PNG (requires graphviz python package + graphviz binary)
deta scan /path/to/project --formats png

Generated files (configurable in deta.yaml):

• infra-map.json
• infra-graph.yaml
• infra-graph.mmd
• infra-graph.png
• infra.toon.yaml

Monitor in real-time

deta monitor /path/to/project --interval 30 --depth 3
deta monitor . --interval 30 --depth 3

# realtime watch from scan command (regenerates outputs on each change)
deta scan /path/to/project --watch --formats json,yaml,mermaid --online

Compare with baseline

deta diff --baseline infra-map.json /path/to/project

Python API

from pathlib import Path
from deta import build_topology

# Build topology from manifests
topology = build_topology(Path("/path/to/project"), max_depth=3)

# Detect anomalies
anomalies = topology.detect_anomalies()
for anomaly in anomalies:
    print(f"{anomaly['severity']}: {anomaly['type']}")

# Export to JSON
import json
output = json.loads(topology.to_json())

Architecture

deta/
├── scanner/          # Manifest parsing
│   ├── compose.py    # docker-compose.yml
│   ├── openapi.py    # OpenAPI specs
│   ├── npm.py        # package.json
│   └── python.py     # pyproject.toml
├── builder/          # Topology construction
│   └── topology.py   # Graph & anomaly detection
├── monitor/          # Real-time monitoring
│   ├── watcher.py    # File watching
│   ├── prober.py     # HTTP health checks
│   └── alerter.py    # Colored output
├── formatter/        # Output formats
│   └── toon.py       # Semcod toon format
├── integration/      # Ecosystem hooks
│   └── semcod.py     # sumd, pyqual, vallm
└── cli.py            # Command-line interface

Semcod Integration

deta integrates with the Semcod ecosystem:

from deta.integration import generate_for_sumd, pre_deploy_check

# Generate toon for sumd
generate_for_sumd(Path("."), output=Path("infra.toon.yaml"))

# Pre-deployment validation
passed, issues = pre_deploy_check(Path("."))
if not passed:
    print("Deployment blocked:", issues)

License

Licensed under Apache-2.0.