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SKILL.md
Managing Bigpanda
ASecurityUse when working with Bigpanda — bigPanda AIOps platform management covering event correlation, root cause analysis, incident management, alert enrichment, topology-based correlation, environment management, and analytics. Use when configuring BigPanda correlation patterns, investigating correlated incidents, tuning noise reduction, or analyzing alert topology and root cause indicators.
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- Added September 8, 2026
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[](https://www.skillsdirectory.com/skills/cloudthinker-ai-managing-bigpanda)---
name: managing-bigpanda
description: |
Use when working with Bigpanda — bigPanda AIOps platform management covering
event correlation, root cause analysis, incident management, alert enrichment,
topology-based correlation, environment management, and analytics. Use when
configuring BigPanda correlation patterns, investigating correlated incidents,
tuning noise reduction, or analyzing alert topology and root cause indicators.
connection_type: bigpanda
preload: false
---
# BigPanda AIOps Management Skill
Manage BigPanda event correlation, root cause analysis, incident management, and alert enrichment.
## API Conventions
### Authentication
All API calls use the `Authorization: Bearer XXXXXX` header — injected automatically. Never hardcode tokens.
### Base URL
`https://api.bigpanda.io`
### Core Helper Function
```bash
#!/bin/bash
bp_api() {
local method="$1"
local endpoint="$2"
local data="${3:-}"
if [ -n "$data" ]; then
curl -s -X "$method" \
-H "Authorization: Bearer $BIGPANDA_API_TOKEN" \
-H "Content-Type: application/json" \
"https://api.bigpanda.io${endpoint}" \
-d "$data"
else
curl -s -X "$method" \
-H "Authorization: Bearer $BIGPANDA_API_TOKEN" \
"https://api.bigpanda.io${endpoint}"
fi
}
```
## Output Rules
- **TOKEN EFFICIENCY**: Extract only needed fields with `jq`
- Target ≤50 lines per script output
## Incident Management
### Get Active Incidents
```bash
bp_api GET "/resources/v2.0/incidents?status=active&sort=-startedAt&limit=25" | jq '[.items[] | {
id, title, status, severity,
startedAt, alertCount,
assignee, environment
}]'
```
### Get Incident Details with Correlated Alerts
```bash
bp_api GET "/resources/v2.0/incidents/INCIDENT_ID/alerts" | jq '[.items[] | {
alertId, status, severity,
host, check, description,
source_system, timestamp
}]'
```
## Correlation and Root Cause
### Get Correlation Patterns
```bash
bp_api GET "/resources/v2.0/correlation-patterns" | jq '[.items[] | {
id, name, active,
correlationType,
conditions
}]'
```
### Review Root Cause Analysis
```bash
bp_api GET "/resources/v2.0/incidents/INCIDENT_ID/rca" | jq '{
rootCause: .rootCause,
confidence: .confidence,
relatedChanges: [.changes[] | {type, description, timestamp}],
topology: .topologyPath
}'
```
## Alert Enrichment
### Get Enrichment Tags
```bash
bp_api GET "/resources/v2.0/enrichment/tags" | jq '[.items[] | {name, type, source, active}]'
```
### Create Enrichment Mapping
```bash
bp_api POST "/resources/v2.0/enrichment/tags" '{
"name": "service_tier",
"type": "mapping",
"source": "host",
"active": true,
"mapping": {"web-prod-*": "tier-1", "api-prod-*": "tier-1", "batch-*": "tier-3"}
}'
```
## Environment Management
### List Environments
```bash
bp_api GET "/resources/v2.0/environments" | jq '[.items[] | {id, name, alertCount, incidentCount}]'
```
## Analytics
### Get Incident Analytics
```bash
bp_api GET "/resources/v2.0/analytics/incidents?period=30d" | jq '{
totalIncidents: .total,
mttr: .meanTimeToResolve,
noiseReduction: .noiseReductionPercentage,
topSources: [.bySource[] | {source: .name, count: .value}][:5]
}'
```
## Common Tasks
1. **Review correlated incidents** — understand how BigPanda groups related alerts
2. **Tune correlation patterns** — adjust topology and tag-based correlation rules
3. **Analyze root cause** — review RCA recommendations and associated change events
4. **Optimize enrichment** — add metadata tags for better alert context and routing
5. **Monitor noise reduction** — track correlation efficiency and alert-to-incident ratios
## Output Format
Present results as a structured report:
```
Managing Bigpanda Report
════════════════════════
Resources discovered: [count]
Resource Status Key Metric Issues
──────────────────────────────────────────────
[name] [ok/warn] [value] [findings]
Summary: [total] resources | [ok] healthy | [warn] warnings | [crit] critical
Action Items: [list of prioritized findings]
```
Target ≤50 lines of output. Use tables for multi-resource comparisons.
## Anti-Hallucination Rules
1. **NEVER assume resource names** — always discover via CLI/API in Phase 1 before referencing in Phase 2.
2. **NEVER fabricate metric names or dimensions** — verify against the service documentation or `--help` output.
3. **NEVER mix CLI commands between service versions** — confirm which version/API you are targeting.
4. **ALWAYS use the discovery → verify → analyze chain** — every resource referenced must have been discovered first.
5. **ALWAYS handle empty results gracefully** — an empty response is valid data, not an error to retry.
## Counter-Rationalizations
| Shortcut | Counter | Why |
|----------|---------|-----|
| "I'll skip discovery and check known resources" | Always run Phase 1 discovery first | Resource names change, new resources appear — assumed names cause errors |
| "The user only asked for a quick check" | Follow the full discovery → analysis flow | Quick checks miss critical issues; structured analysis catches silent failures |
| "Default configuration is probably fine" | Audit configuration explicitly | Defaults often leave logging, security, and optimization features disabled |
| "Metrics aren't needed for this" | Always check relevant metrics when available | API/CLI responses show current state; metrics reveal trends and intermittent issues |
| "I don't have access to that" | Try the command and report the actual error | Assumed permission failures prevent useful investigation; actual errors are informative |
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