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Lightweight Docker monitoring dashboard with anomaly detection & Telegram alerts. One-liner install, zero config.

15 starsPython

DockWatch – Docker monitoring, anomaly detection, Telegram alerts

by dohelper·Mar 1, 2026·1 point·0 comments

AI Analysis

●●●BangerSolve My ProblemNiche GemShip It

Replaces Prometheus+Grafana complexity with one container, zero config install.

Strengths
  • Genuinely minimal footprint: 4 deps, ~50MB memory, single HTML file dashboard—no build step.
  • Friction-free install with interactive setup and Cloudflare Tunnel baked in, not bolted on.
  • Six concrete anomaly detection rules with Telegram alerts and sane cooldown logic address real pain.
Weaknesses
  • SQLite-only metrics storage has no retention policy or export; cluster monitoring impossible.
  • Anomaly thresholds hardcoded; no custom rules, alerting templates, or multi-channel option beyond Telegram.
Target Audience

Self-hosted Docker operators, homelab runners, small teams managing few containers

Similar To

Portainer · Prometheus+Grafana · cAdvisor

Post Description

I built this because existing monitoring solutions (Prometheus+Grafana, Portainer) felt like overkill for simply watching a few Docker containers.

DockWatch is a single container that provides: - Real-time dashboard (CPU, memory, network, disk, temperature) - 6 anomaly detection rules with Telegram alerts - Self-signed HTTPS or Cloudflare Tunnel for remote access - Single HTML file dashboard — no build step

Stack: FastAPI, aiodocker, Chart.js, SQLite. 4 Python dependencies total. ~50MB memory.

Design philosophy: do one thing well. Monitor containers, detect anomalies, send alerts. No container management, no custom metrics, no query language.

Install: git clone https://github.com/deep-on/dockwatch.git && bash install.sh

I'd love feedback on the architecture and what features would make this more useful. The anomaly detection rules in particular — are the default thresholds reasonable?

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