On-Call Health is an open source tool designed to catch early warning signs of overload in on-call engineers before it leads to burnout. Its main purpose is to provide objective signals that make the case for change by monitoring various data points from integrated platforms.

The tool connects signals from multiple sources, starting with Rootly or PagerDuty for incident data, adding Linear for ticket workload, GitHub for after-hours signals, and Slack for communication patterns and context. It also collects sentiment through periodic short surveys sent via Slack, which are fast, low-friction, and designed to reduce stigma rather than create it.

On-Call Health computes individual risk scores from the ingested data, with scores ranging from 0-24 indicating maintain balance, 25-49 for monitor risk, 50-74 for early intervention, and 75-100 for immediate action. AI analyzes what changed and what's driving it, enabling users to act early with confidence by making informed decisions to protect engineers.

The unique approach involves using team and individual-specific baselines to track trends over time, rather than relying on fixed thresholds or comparing people to each other. This makes on-call health measurable and fair, with AI summaries helping stakeholders quickly get up to speed on trends.

Benefits include the ability to intervene early when trend shifts are spotted, allowing actions like rebalancing rotations, adding automation, pausing non-urgent work, or staffing up to prevent burnout. Use cases focus on maintaining engineer well-being through proactive measures.

The target users are on-call engineers and their teams, with integrations supporting Rootly, PagerDuty, GitHub, Linear, and Slack. It is open source under the Apache License 2.0 and available for free use.