SLM
Serverless log monitoring & threat alert system
A serverless security monitoring platform that processes logs, identifies suspicious patterns and surfaces threats in a centralized dashboard.
- Serverless architecture
- Rule-based detection
- Regex threat rules
- Severity classification
- Evidence storage
- Security monitoring
- Centralized dashboard
The challenge
Small teams generate logs across many services but have no security operations centre. They need detection that runs without servers to maintain and alerts that carry evidence.
The system
Logs stream into serverless functions that apply rule-based detection, including regex threat rules, classify severity and store evidence. A centralized dashboard shows alerts, patterns and history.
The experience
Alerts read like findings, not noise: what matched, where, how severe, and the evidence behind it.
The technology
Next.js on Vercel, Supabase for storage and auth, Node.js detection functions. Rules are data, so new threat patterns ship without a redeploy.
Inside SLM.
Interface composition · illustrative data
The system, in section.
Tiers from the surface people use down to the data it rests on. Every tier is a boundary we can test and replace on its own.
- Next.js
- Vercel
- Supabase
- Node.js
The result
Security monitoring that runs at the cost of the logs it processes.
Let’s buildsomething.
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- Studio
- Baluwatar-03, Kathmandu, Nepal