Server agent

One small agent. Your whole fleet, watched.

A single lightweight agent runs on each server, reports to Risal and warns you before things break — with AI root-cause delivered to Telegram. Soon open-source on GitHub.

Install in one line from Servers → Add server — you get a scoped command. The agent is a single Python file; it opens no inbound ports and only calls out to the Risal API.

ziyarago online

3 disks · 8 services · Postgres

42%

CPU

61%

RAM

86%

Disk

disk_full · /var · 86% threshold 90%
AI: /var/log grew 24h — journald vacuum frees ~3.2 GB.
Postgres · 163 MB · 14 conn backup 2h ago

What it reads

System

CPU, RAM/swap, load, every mounted disk, network, disk I/O and the top processes.

Services

systemd units, Docker containers and PM2 processes — plus any service you pin to watch.

Web & TLS

Automatic nginx + Apache vhost discovery with live status, and SSL certificate expiry.

Databases

Postgres, MySQL/MariaDB, MongoDB and Redis — size, connections and cache-hit.

Jobs & backups

cron and systemd timers, including backup-job freshness so a silent backup gets noticed.

Telephony / PBX

Asterisk / Issabel — the call-event spool, audio flow, AMI status (read-only) and call activity.

Alerts & thresholds

Alerts are debounced and carry an AI root-cause summary to Telegram — not just "CPU high", but the likely cause and next actions. Every threshold has a sensible default and is overridable per server.

Plus disk-fill forecasting — "/var fills in ~3 days" — and basic security regressions.

Disk full 90%
High CPU 90%
High RAM 90%
High load (per core) 4.0
TLS expiry warning 14 days
Service / backup down on

Where alerts land

Push on your phone

Risal now

🔴 disk_full · ziyarago

/var is 86% full — projected to fill in ~3 days.

In Telegram

R Risal Monitor bot

🔴 disk_full · ziyarago · /var 86%

Cause: /var/log grew ~3.2 GB in 24h (journald).

Fix: journald vacuum → frees ~3.2 GB.

confidence: high · 10:21

Actions you can run

Open source — soon

The agent is a single, auditable Python file. We are opening it on GitHub so you can read exactly what runs on your servers.