Simple uptime monitor, built with AI
Reliable HTTP monitoring that tells you when something's wrong. No fluff, just useful alerts. Built as a personal experiment in AI-assisted software development.
Free while the project evolves.
Reliable and free
Instant alerts
Get notified by email, webhook, or Slack when downtime is confirmed — no noisy false alarms.
Response time tracking
See how fast your endpoints respond over time. Spot slowdowns before they become outages.
Incident history
Every outage is recorded. Review past incidents with start time, duration, and error details.
Checks every minute
Run checks on your preferred schedule, with monitoring intervals as low as 60 seconds.
Everything you need to stay informed
No bloat, no unnecessary add-ons. Just the monitoring features that actually matter.
- HTTP and HTTPS endpoint monitoring
- Configurable check intervals (1 min – 1 hour)
- Email, webhook, and Slack alerts on incidents
- Keyword-based response validation
- SSL certificate visibility
- Incident open and close notifications
- Real-time dashboard updates
- Up to 3 monitors on the free plan
For developers and indie hackers
Indie hackers and solo developers
Keep an eye on your side project without paying for enterprise tools.
Side projects and MVPs
Know the moment your new product goes down, even before users notice.
Personal portfolios and hobby sites
Get alerts when your portfolio is down. No complex setup required.
Experimental APIs and proof-of-concepts
Monitor unstable endpoints and track reliability as you iterate.
Built as a Personal AI Experiment
NetWatchly is more than just an uptime monitor. It's a personal experiment in AI-assisted software engineering. The goal is to explore how AI can support a real software development process. Most of the implementation was generated using AI-powered Specification Driven Development (SSD). The result is a small project that could become a simple alternative to pricey solutions.
Features are still being added, but the core uptime monitoring functionality is already in place. The project is free to use as long as people continue finding value in using it and learning from the experiment.
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