LogOctopus

A single place to collect, explore, and analyze evidence from distributed test executions.

LogOctopus helps engineers understand why distributed tests fail. It automatically collects logs, metrics, and system data from remote devices over SSH and organizes everything into a single searchable test session, making root-cause analysis faster and easier.

Why LogOctopus?

A distributed test fails.

What happens next?

❌ Test failed
        ↓
SSH into device 1
Collect logs
        ↓
SSH into device 2
Collect logs
        ↓
Compare timestamps
        ↓
Find the root cause

With LogOctopus:

❌ Test failed
        ↓
LogOctopus already collected:

✅ Device logs
✅ System metrics
✅ Command outputs
✅ Test session data
        ↓
Open one session and investigate

Use LogOctopus when you need to answer:

"What happened during this failed test?"

Live Demo

👆 Click the preview above to open the interactive demo

Why not ELK / Grafana?

LogOctopus solves a different problem.

Capability	LogOctopus	ELK	Grafana	Manual SSH
SSH-based collection	✅	❌	❌	✅
No agent installation required	✅	❌	❌	✅
Test session grouping	✅	❌	❌	❌
Multi-device support	✅	✅	✅	⚠️
Ready to use quickly	✅	❌	❌	⚠️
Designed for test debugging	✅	⚠️	⚠️	❌

Quick Start

Docker

git clone https://github.com/kkuuba/LogOctopus.git

cd LogOctopus

nano .env

docker compose up -d

Open:

Frontend:
http://localhost:8100

Backend:
http://localhost:8050

Features

Multi-device collection

Collect data from multiple SSH-accessible devices:

• Linux
• Windows
• Raspberry Pi
• Network devices
• NAS systems
• Custom embedded devices

Supports:

• Direct SSH connections
• Gateway/jump hosts
• Network packet captures

Test-session based investigation

Every collection run creates a session containing:

• Logs
• Metrics
• Device information
• Scenario name
• Timestamps

Example:

reboot-test

├── server-01
│   ├── system logs
│   └── CPU metrics
│
├── router-01
│   └── network logs
│
└── device-01
    └── application logs

Log visualization

Text logs

• Unified timeline
• Filtering
• Highlighting
• CSV export

Chart logs

• Interactive charts
• Zoom and pan
• Device comparison

Network capture

• Collect packtes
• Decode packets info
• Custom tshark dissctors

Automation integration

Designed for automated tests:

Start collection
        ↓
Run test
        ↓
Stop collection
        ↓
Open session results

Integrate using REST API with:

• CI/CD pipelines
• Python tests
• Custom automation frameworks

Architecture

              React Frontend
                    |
                 REST API
                    |
              Flask Backend
                    |
                   SSH
                    |
      ------------------------------
      |             |              |
   Device A      Device B       Device C

Components:

• React frontend
• Flask backend
• SSH collection layer
• Local snapshot storage

No external database required.

Configuration

Devices are configured using JSON files.

Example:

{
  "device_name": "Linux Server",
  "ip_address": "192.168.1.10",
  "port": 22,
  "user": "test-user",

  "log_file_configs": [
    {
      "log_name": "system_log",
      "log_file_cmd": "journalctl",
      "log_type": "text"
    }
  ]
}

Example configurations:

docs/example_configs/

Includes:

• Linux
• Windows
• Cisco
• MikroTik
• pfSense
• Proxmox
• Raspberry Pi
• Synology NAS

REST API

The API allows:

• Start/stop collection
• Manage devices
• Query snapshots
• Retrieve logs

Example:

curl -X POST http://localhost:8050/api/start-logs-collection \
-H "Content-Type: application/json" \
-d '{"selected_devices":["server-01"],"session_scenario":"test"}'

Planned Features

• Historical test comparison
• Trend analysis
• AI-assisted configuration generation
• Improved device monitoring

Contributing

Pull requests are welcome.

License

MIT License