dashboard-builder
Build monitoring dashboards that answer real operator questions for Grafana, SigNoz, and similar platforms. Use when turning metrics into a working dashboard instead of a vanity board.
소스 정보
- 저장소
- affaan-m/ECC
- 최근 소스 활동
- 2026년 8월 12일 03:58
- 감지된 SKILL.md 언어
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소스 파일 검토
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SKILL.md 표시 중
SKILL.md
소스 지침 · 읽기 전용 미리보기- name
- dashboard-builder
- description
- Build monitoring dashboards that answer real operator questions for Grafana, SigNoz, and similar platforms. Use when turning metrics into a working dashboard instead of a vanity board.
- metadata
- {"version":"1.0.0","origin":"ECC direct-port adaptation"}
# Dashboard Builder
Use this when the task is to build a dashboard people can operate from.
The goal is not "show every metric." The goal is to answer:
- is it healthy?
- where is the bottleneck?
- what changed?
- what action should someone take?
## When to Use
- "Build a Kafka monitoring dashboard"
- "Create a Grafana dashboard for Elasticsearch"
- "Make a SigNoz dashboard for this service"
- "Turn this metrics list into a real operational dashboard"
## Guardrails
- do not start from visual layout; start from operator questions
- do not include every available metric just because it exists
- do not mix health, throughput, and resource panels without structure
- do not ship panels without titles, units, and sane thresholds
## Workflow
### 1. Define the operating questions
Organize around:
- health / availability
- latency / performance
- throughput / volume
- saturation / resources
- service-specific risk
### 2. Study the target platform schema
Inspect existing dashboards first:
- JSON structure
- query language
- variables
- threshold styling
- section layout
### 3. Build the minimum useful board
Recommended structure:
1. overview
2. performance
3. resources
4. service-specific section
### 4. Cut vanity panels
Every panel should answer a real question. If it does not, remove it.
## Example Panel Sets
### Elasticsearch
- cluster health
- shard allocation
- search latency
- indexing rate
- JVM heap / GC
### Kafka
- broker count
- under-replicated partitions
- messages in / out
- consumer lag
- disk and network pressure
### API gateway / ingress
- request rate
- p50 / p95 / p99 latency
- error rate
- upstream health
- active connections
## Quality Checklist
- [ ] valid dashboard JSON
- [ ] clear section grouping
- [ ] titles and units are present
- [ ] thresholds/status colors are meaningful
- [ ] variables exist for common filters
- [ ] default time range and refresh are sensible
- [ ] no vanity panels with no operator value
## Related Skills
- `research-ops`
- `backend-patterns`
- `terminal-ops`
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