Correlate PagerDuty incidents with Jira tickets and recent ArgoCD deployments to accelerate root cause analysis. Orchestrates multiple agents to build a timeline of events. Use when investigating active incidents, performing post-mortems, or correlating alerts with changes.
Installation
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Correlate PagerDuty incidents with Jira tickets and recent ArgoCD deployments to accelerate root cause analysis. Orchestrates multiple agents to build a timeline of events. Use when investigating active incidents, performing post-mortems, or correlating alerts with changes.
Incident Investigation
Perform multi-agent investigation by correlating PagerDuty incidents, Jira tickets, and ArgoCD deployment history to identify root cause and impacted systems.
Instructions
Phase 1: Gather Incident Data (PagerDuty Agent)
Fetch active incidents - list all triggered and acknowledged incidents
For each incident, collect:
Incident ID, title, urgency, and status
Service affected and escalation policy
Triggered timestamp and duration
Assigned responders and acknowledgment status
Alert details and monitoring source
Phase 2: Correlate with Tickets (Jira Agent)
Search for related Jira tickets using:
Incident ID or service name in ticket descriptions
Recent tickets with labels like `incident`, `outage`, `p0`, `p1`
Tickets linked to the affected service or component
For each related ticket, collect:
Ticket key, summary, status, assignee
Priority and labels
Comments with recent updates
Phase 3: Check Recent Deployments (ArgoCD Agent)
Search for recent deployments in the last 24 hours:
Applications related to the affected service
Any applications with recent sync operations
Failed syncs or rollbacks
For each deployment, collect:
Application name and sync status
Deployment timestamp
Revision/commit that was deployed
Sync result (success, failed, pruned resources)
Phase 4: Build Incident Timeline
Merge all events into a chronological timeline:
Deployments -> Alerts triggered -> Incident created -> Responses
Identify correlations:
Did a deployment happen shortly before the incident?
Are multiple services affected (blast radius)?
Is there a pattern (recurring incident)?
Assess impact:
Which services/teams are impacted?
Customer-facing or internal only?
Estimated time to resolution
Output Format
```markdown
Incident Investigation Report
Active Incidents
Incident
Service
Urgency
Duration
Status
INC-1234
payment-api
High
45m
Acknowledged
Timeline
Time (UTC)
Event
Source
14:00
ArgoCD sync: payment-api v2.3.1 deployed
ArgoCD
14:12
Alert: payment-api error rate >5%
PagerDuty
14:15
Incident INC-1234 created (High urgency)
PagerDuty
14:18
Acknowledged by @oncall-engineer
PagerDuty
Probable Root Cause
Deployment of payment-api v2.3.1 at 14:00 UTC introduced a regression.
Recommended Actions
Immediate: Rollback payment-api to v2.3.0 via ArgoCD
Short-term: Review commit diff between v2.3.0 and v2.3.1
Follow-up: Create post-mortem Jira ticket
```
Examples
"Show me active PagerDuty incidents and find related Jira tickets"
"Investigate the current outage - what changed recently?"
"Correlate the payment-api incident with recent deployments"
"Build a timeline for incident INC-1234"
Guidelines
Always start with PagerDuty for the source of truth on active incidents
Look at the 24-hour window before the incident for deployment correlation
If no incidents are active, report that clearly and suggest checking resolved incidents
When multiple incidents exist, group by service to identify blast radius
Include direct links to PagerDuty incidents and Jira tickets in the output
For recurring incidents, note the frequency and link to previous occurrences
Never suggest changes that could make the situation worse (e.g., deploying during an active incident)