Skip to main content

🐳 DockAI – AI-powered Docker Log Analysis Tool (CLI + Cloud)

DockAI is an intelligent CLI tool that analyzes Docker container logs using Large Language Models (LLMs). It helps developers, DevOps engineers, and system administrators quickly identify issues, summarize logs, and provide actionable insights.


🚀 Features

  • AI Log Analysis Understands and summarizes logs using LLMs, identifying possible root causes and suggesting solutions.

  • Performance Monitoring (CPU & Memory) Measure container performance in real-time or over a time window using --perf or --instant-perf.

  • Local & Cloud AI Modes (Ollama + OpenAI) Analyze with a local model (e.g., llama3) or cloud-based OpenAI API:

    dockai analyze my-container --mode local
    dockai analyze my-container --mode cloud
    
  • Live Container Status Even when no logs are generated, DockAI provides a live summary including container status, restart count, and health.

  • Simple CLI Usage

    dockai analyze <container-name> --since 15m --tail 3000
    

📊 Example Output

🤖 AI Analysis:
**Summary:** Database connection failed.
**Root Cause:** TCP/IP connection refused.
**Solution:** 
- Restart the database service inside the Docker container.
- Check port accessibility and network configuration.

⚙️ Performance
- CPU p95: 0.3% | max: 1.1%
- Mem p95: 12.7%

🧠 Supported Models

  • Local: Ollama (e.g., llama3, mistral, gemma)
  • Cloud: OpenAI GPT-4, GPT-4o-mini

🔧 Default Model

By default, DockAI uses:

DOCKAI_OLLAMA_MODEL = "qwen2.5:7b-instruct"

This model offers excellent multilingual support (including Turkish 🇹🇷) and strong technical reasoning for analyzing Docker logs.

To override the model, set an environment variable:

export DOCKAI_OLLAMA_MODEL="aya:23b"

⚙️ Installation

pip install dockai

🧩 Ollama Installation (All Platforms)

macOS

brew install ollama
ollama pull qwen2.5:7b-instruct

Linux

curl -fsSL https://ollama.com/install.sh | sh
ollama pull qwen2.5:7b-instruct

Windows (PowerShell)

winget install Ollama.Ollama
ollama pull qwen2.5:7b-instruct

💡 Tip: DockAI automatically uses the model defined in the environment variable DOCKAI_OLLAMA_MODEL (default: qwen2.5:7b-instruct).


🧩 Developer Commands

make build       # build the package
make publish     # publish to PyPI
make testpublish # publish to TestPyPI

🧾 License

Apache License 2.0 Copyright (c) 2025 Ahmet Atakan


🧩 Plugin Architecture

DockAI supports a modular plugin system that allows developers to extend functionality without modifying the core codebase.
Each plugin can react to lifecycle hooks such as on_start, on_finish, or on_error.

🔌 How Plugins Work

  • Plugins are loaded automatically from:
    • dockai/plugins/ (built-in plugins)
    • ~/.dockai/plugins/ (user-installed plugins)
  • Each plugin defines a plugin.json file that describes:
    {
      "enabled": true,
      "name": "telemetry",
      "version": "0.2.0",
      "config": {
        "sqlite_path": "~/.dockai/usage.db"
      }
    }
    

✨ Example Plugin Hooks

def on_start(self, ctx):
    print("[plugin] analysis started")

def on_finish(self, ctx):
    print("[plugin] analysis completed")

📈 Telemetry & Usage Tracking

DockAI includes a built-in Telemetry Plugin for tracking usage and performance statistics.
This plugin helps monitor how DockAI is used, improving future versions and providing analytics for paid plans.

📊 Data Model

  • usage table — stores each analysis run (time, container, mode, latency, etc.)
  • findings table — stores detected errors/warnings and AI insights per run

🔒 Privacy

All telemetry data is stored locally in SQLite (~/.dockai/usage.db) and never sent externally.
Users can disable or extend telemetry via plugin configuration.


💰 Licensing & Monetization Roadmap

DockAI is open source (Apache 2.0) but designed to support optional monetization:

  • Free Plan: limited analysis history and findings
  • Pro Plan (License Key): unlocks unlimited telemetry, detailed analytics, and advanced plugins
  • Plugin Marketplace (future): third-party verified plugins with SHA-based signature validation

A JWT-based license verification system is planned to allow easy activation via:

dockai license activate --key <YOUR_LICENSE_KEY>

🗺️ Future Roadmap

  • 🧠 Enhanced AI reasoning & multi-model ensemble
  • 📊 Graphical performance reports (PDF or Web)
  • 🔐 Secure license key & API-based billing
  • 🧩 Plugin Store with auto-update mechanism
  • 🌍 Cloud telemetry dashboard

Release files for dockai 0.5.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for dockai 0.5.3
File Size Uploaded
dockai-0.5.3.tar.gz 29.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for dockai 0.5.3
File Interpreter ABI Platform
dockai-0.5.3-py3-none-any.whl Python 3 none any Details

Total release size: 62.6 kB

Release files / dockai-0.5.3.tar.gz

Download URL dockai-0.5.3.tar.gz
Size 29.7 kB
Tags Source
SHA-256 checksum
How to use checksums
086c1bc081c43f6936807855d9bed85646ac471efb9b747dabadb9d60c7a10a8
BLAKE2b-256 checksum
How to use checksums
9f206d1753611c3a41e050615441109ff7f6861a0824fba4b24a3a761152df45
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.14.0

Release files / dockai-0.5.3-py3-none-any.whl

Download URL dockai-0.5.3-py3-none-any.whl
Size 32.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
7f07fb135c812dbb9d8ea6437389b74e84f6bddd8f37f307b7288385781dd14d
BLAKE2b-256 checksum
How to use checksums
c3c9791766329db315bc2418c022c5e62d5d9ca153438cadd651e4fe84db7e9a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.14.0

Release history Release notifications | RSS feed

This release

0.5.3 This release

2 release files

0.5.2

2 release files

0.5.1

2 release files

0.5.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page