Automatically triage support emails and tickets, drafting responses for human review.
Have an agent SSH into an alerting server to run diagnostics and summarize the likely cause.
Try the whole workflow in demo mode with sample data before connecting real ticketing or alerting systems.
| skyone96/aiops | codedgar/three-fenestra | futureuniant/workshadow | |
|---|---|---|---|
| Stars | 42 | 42 | 42 |
| Language | TypeScript | TypeScript | TypeScript |
| Setup difficulty | moderate | easy | moderate |
| Complexity | 4/5 | 3/5 | 2/5 |
| Audience | ops devops | developer | general |
Figures from each repo's GitHub metadata at analysis time.
Requires Node.js 18+, Python 3.11+, and separate frontend/backend dependency installs.
AIOPS is a cross platform desktop assistant built to help IT operations staff handle everyday tasks and incidents, combining an Electron and React front end with a Python FastAPI backend that runs a LangGraph based AI agent. It works on Windows, Debian Linux, and the Chinese UOS operating system. The tool has two main modes. Ops mode connects to email systems like IMAP, Exchange, or Microsoft Graph to spot messages that need an operations response, drafts replies, and can pull tickets from systems like Jira or ServiceNow to propose a resolution, including drafting change request forms afterward. Duty mode is built for on-call work: it ingests alerts from monitoring tools like Zabbix, Prometheus Alertmanager, or Grafana, logs into affected servers over SSH to run diagnostic commands such as checking disk space or running processes, and puts together a report describing the likely impact and recommended next steps. The README is explicit that every risky action, including sending an email, submitting a change request, or running an SSH command, requires a human to review and approve it first, with dangerous commands like deleting files or rebooting a server needing extra confirmation. Credentials and API keys are stored locally on the user's own machine rather than uploaded anywhere, and the frontend and backend only talk to each other over a local address that isn't exposed to the network. Setting it up means installing Node.js and Python dependencies for the frontend and backend separately, then either running both in development mode or packaging the whole thing into a Windows installer or a Linux .deb package. The assistant can be connected to OpenAI, Azure OpenAI, Anthropic, or self-hosted models like Qwen or DeepSeek, and every integration, from mail servers to alerting systems, can also be run in a demo mode with sample data before connecting to a real environment.
A cross platform desktop AI agent that helps IT operations staff triage emails, tickets, and system alerts, with every risky action requiring human approval.
Mainly TypeScript. The stack also includes Electron, React, TypeScript.
Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.
Mainly ops devops.
This repo across BitVibe Labs
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