title	DevOps Incident Suite
emoji	🚨
colorFrom	red
colorTo	blue
sdk	gradio
sdk_version	5.29.0
python_version	3.11
app_file	app.py
pinned	false

Multi-Agent DevOps Incident Analysis Suite

A VS Code-ready GenAI project that uses LangChain + LangGraph to analyze DevOps logs and generate remediation guidance, runbooks, Slack notifications, and JIRA tickets.

What This Project Demonstrates

• Multi-agent architecture
• LangGraph orchestration
• LangChain LLM usage
• DevOps/SRE log analysis
• Automated incident classification
• Remediation recommendation
• Runbook generation
• Optional Slack and JIRA integration
• Gradio UI

Agent Flow

User uploads logs
   ↓
Log Parser Agent
   ↓
Incident Classification Agent
   ↓
Remediation Agent
   ↓
Runbook Generator Agent
   ↓
Slack/JIRA Notification Agent

Project Structure

devops_incident_vscode/
├── agents/
│   ├── log_agent.py
│   ├── classifier_agent.py
│   ├── remediation_agent.py
│   ├── runbook_agent.py
│   └── notification_agent.py
├── graph/
│   └── workflow.py
├── integrations/
│   ├── slack.py
│   └── jira.py
├── utils/
│   └── llm.py
├── data/sample_logs/
├── app.py
├── state.py
├── requirements.txt
├── .env.example
└── README.md

Setup in VS Code on Windows

1. Open folder in VS Code

Open the devops_incident_vscode folder.

2. Create virtual environment

py -m venv .venv

3. Activate virtual environment

.\.venv\Scripts\Activate.ps1

If PowerShell blocks activation, run:

Set-ExecutionPolicy -Scope CurrentUser RemoteSigned

Then activate again:

.\.venv\Scripts\Activate.ps1

4. Install dependencies

py -m pip install --upgrade pip
py -m pip install -r requirements.txt

5. Configure environment

Copy .env.example to .env.

copy .env.example .env

Add your OpenRouter key:

OPENAI_API_KEY=your_key_here
OPENAI_BASE_URL=https://openrouter.ai/api/v1
LLM_MODEL=openai/gpt-4o-mini

The app also works without an API key using fallback rule-based classification.

6. Run the app

py app.py

Open the local URL shown in the terminal, usually:

http://127.0.0.1:7860

Run in Google Colab

Upload the project folder or zip file, then run:

!pip install -r requirements.txt
!python app.py

For public Colab link, change the last line in app.py from:

demo.launch()

to:

demo.launch(share=True)

Deploy to Hugging Face Spaces

1. Create a new Hugging Face Space
2. Select Gradio as SDK
3. Upload all project files
4. Add secrets in Space settings:
   • OPENAI_API_KEY
   • OPENAI_BASE_URL
   • LLM_MODEL
   • optional Slack/JIRA values
5. Hugging Face will install requirements.txt and run app.py