Create dashboards that visualize the most important metrics for your AI systems. Combine real-time widgets with historical trends and drill downs to accelerate incident response and drive continuous improvement.

Organize dashboards by audience: executive summaries, daily operations, and deep technical analysis. Use consistent color and layout systems, and include links to saved queries and runbooks.

Design Principles

1. 1

   Prioritize signal Surface actionable KPIs at the top, with clear thresholds and states.

2. 2

   Enable drill down Link widgets to queries and detailed views for investigation.

3. 3

   Segment by context Support filters for project, environment, user segment, and feature flag.

4. 4

   Share and review Snapshot dashboards for releases and incident reviews; annotate key changes.

dashboard = {
  "name": "AI Health Overview",
  "refresh": "30s",
  "sections": [
    {"title": "System Health", "widgets": ["status", "latency_p95", "error_rate"]},
    {"title": "Quality", "widgets": ["overall_score", "groundedness", "helpfulness"]},
    {"title": "Cost", "widgets": ["cost_per_request", "daily_spend", "token_usage"]}
  ]
}