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Overview

This page defines the metrics you’ll see across the dashboard and the Analytics API, and how to interpret them. Every metric is available at daily, weekly and monthly granularity as a pre-computed aggregation.

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Core Metrics

Definition: successful executions ÷ total executions, as a percentage.Watch for: sudden drops, or a slow decline that never quite triggers a hard failure. A workflow at 92% that used to sit at 99% is quietly losing one run in twelve.Metric types: daily_success_rate, weekly_success_rate, monthly_success_rate.
Definition: mean execution time over the period.Watch for: upward drift (often a growing dataset or a slow upstream API) and spikes that line up with failures.Metric types: daily_avg_duration, weekly_avg_duration, monthly_avg_duration.
Definition: count of executions over the period.Watch for: volume dropping to zero (a workflow that stopped triggering) and unexpected surges (a runaway trigger or retry storm).Metric types: daily_executions, weekly_executions, monthly_executions.
Definition: share of health checks where the connected platform responded successfully.Metric types: daily_availability, weekly_availability, monthly_availability. See Availability Monitoring.
Definition: rolled-up AI token spend for OpenClaw connections.Metric type: monthly_openclaw_cost. See OpenClaw setup.
Best for real-time operations and catching today’s incident. Highest resolution, shortest history.

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Querying Metrics

Pull any metric over a time range via the API:
Results use cursor pagination — see Cursor Pagination.

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Beyond Averages: Anomalies

Averages hide short spikes. Opsmatic also runs statistical anomaly detection over response times, failure rates and OpenClaw spend against a rolling 7-day baseline (3σ / 5σ thresholds), opening an incident when something deviates sharply.

Workflow Analytics

Per-workflow execution detail

Health Monitoring

Real-time status on your dashboard