Executive Dashboard
Dashboard Overview
The Executive Dashboard provides a concise, high-level view of IT operations health for senior leadership. It aggregates the most important ITSM and cloud metrics into a single page designed for executive consumption — no technical detail, just clear indicators of how IT is performing against SLAs and business objectives.
- Role: Executive dashboard requires
super_admin,itsm_manager, orcloud_adminJWT claim - Aurora: At least 30 days of incident and SLA data for meaningful trend analysis
- DynamoDB:
StackFlow_KPItable with configured KPI targets for variance calculation - Redis: Executive metrics cached with TTL 900s (15 minutes) under
sf:dash:executive:{tenantId}
KPI Tiles
| KPI | Description | Calculation |
|---|---|---|
| Overall SLA Compliance | % of incidents resolved within SLA | 30-day rolling average |
| MTTR (All Priorities) | Mean time to resolution | 30-day rolling average, in hours |
| P1 MTTR | Mean time to resolve critical incidents | 30-day rolling average, in minutes |
| Open Incidents | Count of open incidents by priority | Real-time snapshot |
| Major Incidents (30d) | Count of P1 incidents in last 30 days | Rolling 30-day count |
| Change Success Rate | % of changes implemented without incident | 30-day rolling average |
Trend Charts
The executive view includes 90-day trend charts for incident volume, SLA compliance, and MTTR. Charts show week-over-week comparison to highlight improving or degrading trends. Significant anomalies (e.g., a spike in P1 incidents) are annotated with the root cause where known (linked to the resolved Problem record).
SLA Compliance
The SLA compliance section shows compliance rates broken down by priority tier and by month. A compliance rate below the target threshold is highlighted in red. Click any cell in the SLA compliance table to drill down to the individual incidents that missed SLA within that priority/month combination.
AI-Generated Insights
The bottom section of the Executive Dashboard includes AI-generated narrative insights updated every 4 hours. The AI analyzes the current metrics, compares to historical patterns, and generates 3-5 bullet points summarizing: what's going well, what needs attention, and any emerging trends worth monitoring. These insights use the Bedrock Claude model and are generated by the StackFlowCacheWarmer Lambda on a schedule.