Dashboard Overview
The ActiveMotion monitoring dashboard provides real-time visibility into agent performance across four dimensions: throughput, latency, quality, and cost. The throughput panel shows request volume, autonomous resolution rate, and escalation frequency over configurable time windows. The latency panel displays response time percentiles for agent processing, tool calls, and end-to-end resolution. The quality panel tracks reasoning chain accuracy, user satisfaction signals, and error categorization. The cost panel monitors token consumption, tool call volume, and infrastructure utilization. All panels support filtering by agent instance, workflow type, time range, and outcome category.
Alerting and Incident Response
Alerts are defined using a threshold-based rule engine that evaluates metrics against configurable baselines. Standard alert rules are provided for common degradation patterns: resolution rate drops below the historical baseline by more than ten percent, average latency exceeds the SLA threshold, error rate spikes above one percent, or token consumption exceeds the projected budget. Alerts route to configurable channels including Slack, PagerDuty, email, and webhook endpoints. Each alert includes context about the triggering condition, affected agent instances, and suggested diagnostic steps. For critical alerts, automated mitigation actions can be configured such as circuit-breaking a degraded integration or routing traffic to a fallback agent instance.
Trace-Level Logging
Every agent interaction produces a distributed trace that captures the complete execution path from request receipt through reasoning, tool invocation, verification, and response delivery. Traces include structured metadata for each span: the operation type, duration, input and output summaries, and any errors or retries. Traces can be viewed in the built-in trace explorer or exported to external tracing platforms such as Jaeger, Zipkin, or Datadog APM. The trace explorer supports searching by request attributes, filtering by duration or error status, and comparing traces across different agent versions to validate performance improvements.
SLA Tracking and Reporting
SLA definitions are configurable per workflow type and specify target metrics for resolution time, autonomous resolution rate, accuracy, and availability. The SLA tracking engine continuously evaluates actual performance against targets and maintains running compliance percentages. Weekly and monthly SLA reports are generated automatically and can be distributed to stakeholders. When SLA compliance trends downward, early warning alerts trigger before the target is actually breached, giving operations teams time to investigate and remediate. Historical SLA data is retained for trend analysis and capacity planning, helping organizations anticipate when additional agent capacity or workflow optimization is needed.