Architecture
How ResolveOps AI ingests operational signals and stores them as queryable incident events.
Processing pipeline
From raw operational events to resolved incidents.
1. Ingest
Normalize events from PagerDuty, Datadog, CloudWatch, Slack, Jira, and Zendesk into a unified schema.
2. Correlate
Store and query incident signals in Amazon DynamoDB using incidentId and eventTimestamp keys.
3. Analyze
AI ranks root-cause hypotheses, scores recurrence risk, and cites evidence from the timeline.
4. Resolve
Generate postmortems and prevention action items, tracked to closure across owners and services.
DynamoDB event model
Core incident and event records stored in Amazon DynamoDB table resolveops-ai-events. Incidents connect services, timelines, responders, root causes, postmortems, and action items.
| Table | Purpose | Columns |
|---|---|---|
| organizations | Tenant accounts and plan metadata | 7 |
| users | Responders, owners, and commanders | 9 |
| services | Tracked services and health state | 11 |
| incidents | Core incident records | 14 |
| incident_services | Many-to-many incident ↔ service join | 4 |
| incident_timeline_events | Detection → resolution event log | 8 |
| incident_responders | Responder roles per incident | 6 |
| postmortems | Structured postmortem documents | 12 |
| root_causes | Root cause + confidence per incident | 7 |
| action_items | Follow-up actions and prevention | 11 |
| external_events | Ingested events from data sources | 9 |
| ai_recommendations | AI summaries and recommendations | 8 |
| audit_logs | Immutable change history | 7 |
Connected data sources
Signals feeding the external_events table.
PagerDutyAlerting
connectedSlackCollaboration
connectedJiraTicketing
connectedAWS CloudWatchMonitoring
connectedDatadogMonitoring
simulatedZendeskSupport
simulatedTech stack
The foundation ResolveOps AI is built on.
Next.js App RouterAmazon DynamoDBServer ComponentsAI root-cause analysisEvent correlation engineRole-based incident command