Catch overload before it burns out your incident responders
Free, open-source tool that helps spot unsustainable on-call workloads before they become a problem. It pulls signals from tools like Rootly, PagerDuty, GitHub, Linear, and Jira, combines them with self-reported check-ins, and tracks everything against personal and team baselines.
Hey Product Hunt! I'm Sylvain, Head of AI Labs at Rootly. As a former SRE, I've watched too many friends and co-workers burn out from on-call. The signs are always there: after-hours pages creeping up, weekends disappearing. But there's never been a good way to actually measure it.
That's why we built On-Call Health. It's free, open source, and helps engineering teams spot when on-call is drifting into overload before it's too late.
It works by combining two types of signals:
Observed data from tools your team already uses (Rootly, PagerDuty, Slack, GitHub, Linear, Jira) — incident volume, severity, after-hours activity, task load
Short self-reported check-ins inspired by Apple Health's State of Mind feature, where responders share how they're actually feeling
Everything is tracked against each person's own baseline over time — not static thresholds, not comparisons between people. Because what's routine for a 10-year SRE veteran might be overwhelming for someone 6 months into their first rotation.
We built this alongside engineering teams at Weights & Biases and Brex, and their feedback shaped the scoring and integrations we prioritized.
You can try it right now at oncallhealth.ai with mock data — no setup, no account required.
It's still early and we'd love your feedback. @spc__01, @hamza_hamza11 and I would love to know what would you want to see next? Issues and PRs are very welcome.
Nicolas Dessaigne
Hey Product Hunt! I'm Sylvain, Head of AI Labs at Rootly. As a former SRE, I've watched too many friends and co-workers burn out from on-call. The signs are always there: after-hours pages creeping up, weekends disappearing. But there's never been a good way to actually measure it.
That's why we built On-Call Health. It's free, open source, and helps engineering teams spot when on-call is drifting into overload before it's too late.
It works by combining two types of signals:
Observed data from tools your team already uses (Rootly, PagerDuty, Slack, GitHub, Linear, Jira) — incident volume, severity, after-hours activity, task load
Short self-reported check-ins inspired by Apple Health's State of Mind feature, where responders share how they're actually feeling
Everything is tracked against each person's own baseline over time — not static thresholds, not comparisons between people. Because what's routine for a 10-year SRE veteran might be overwhelming for someone 6 months into their first rotation.
We built this alongside engineering teams at Weights & Biases and Brex, and their feedback shaped the scoring and integrations we prioritized.
You can try it right now at oncallhealth.ai with mock data — no setup, no account required.
It's still early and we'd love your feedback. @spc__01, @hamza_hamza11 and I would love to know what would you want to see next? Issues and PRs are very welcome.