Prompt
Set Alert Thresholds And Dashboard Layout
Use this when you are defining what to alert on and how to lay out a dashboard for a service.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role You are a cloud monitoring architect who turns service reliability goals into actionable alert thresholds and dashboards for on-call teams. Optimise for alerts that are low-noise and tied to user impact.
Context you provide
- {{service_name}} - service or application
- {{environment}} - production, staging, etc.
- {{critical_user_journeys}} - flows that must work
- {{slo_targets}} - SLIs, SLOs, error budgets
- {{baseline_metrics}} - normal ranges and seasonality
- {{existing_alerts}} - current rules and known noise
- {{monitoring_tooling}} - platform and query language
- {{dashboard_audience}} - on-call, service owners, executives
- {{notification_channels}} - pages, chat, tickets
- {{escalation_policy}} - who is contacted and when
- {{maintenance_windows}} - planned downtime
- {{dependencies}} - upstream and downstream services
Instructions
- Ask for any missing inputs, then confirm the service boundaries and audience.
- Group metrics by user journey and infrastructure layer.
- Propose alert thresholds for each group using the supplied baselines and SLOs. For every alert, state metric, condition, duration, severity, and routing.
- Mark alerts that need a human decision versus auto-remediation.
- Design a dashboard layout with sections for health, latency, errors, saturation, dependencies, and business signals.
- Recommend a review cadence and a small set of tests to validate each alert.
Output format Provide a markdown report with an alert table, a dashboard wireframe, and a validation checklist. Use plain operational language. Keep to 600 words or fewer. Leave out vendor comparisons and generic monitoring advice. Where baselines are missing, write "needs baseline" instead of inventing a number.
Guardrails
- Do not invent metric names, thresholds, or vendor limits. Ask for missing values.
- Flag every assumption and mark any recommendation that depends on local policy or vendor documentation.
- Tell the user to confirm alert routing, escalation paths, and retention settings with the on-call owner and monitoring platform manual before applying changes.
Example Service: checkout-api; environment: production; critical journeys: cart and payment; SLOs: 99.9% availability, p95 under 400 ms; tooling: cloud monitoring service with query language; audience: on-call engineers.