dashboard-builder
Builds actionable monitoring dashboards, focusing on health status, bottleneck identification, change analysis, and actionable recommendations, rather than just piling up metrics.
npx skills add affaan-m/everything-claude-code --skill dashboard-builderBefore / After Comparison
1 组Manually switching between multiple tools to view logs, metrics, and traces, making it difficult to correlate events and requiring additional time to pinpoint the root cause after an issue is found.
A single dashboard displays key health metrics, highlights anomalies, and shows pending actions, automatically correlating relevant logs and traces, allowing issues to be located within 5 minutes.
dashboard-builder
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:
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is it healthy?
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where is the bottleneck?
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what changed?
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what action should someone take?
When to Use
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"Build a Kafka monitoring dashboard"
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"Create a Grafana dashboard for Elasticsearch"
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"Make a SigNoz dashboard for this service"
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"Turn this metrics list into a real operational dashboard"
Guardrails
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do not start from visual layout; start from operator questions
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do not include every available metric just because it exists
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do not mix health, throughput, and resource panels without structure
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do not ship panels without titles, units, and sane thresholds
Workflow
1. Define the operating questions
Organize around:
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health / availability
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latency / performance
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throughput / volume
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saturation / resources
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service-specific risk
2. Study the target platform schema
Inspect existing dashboards first:
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JSON structure
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query language
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variables
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threshold styling
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section layout
3. Build the minimum useful board
Recommended structure:
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overview
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performance
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resources
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service-specific section
4. Cut vanity panels
Every panel should answer a real question. If it does not, remove it.
Example Panel Sets
Elasticsearch
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cluster health
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shard allocation
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search latency
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indexing rate
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JVM heap / GC
Kafka
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broker count
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under-replicated partitions
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messages in / out
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consumer lag
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disk and network pressure
API gateway / ingress
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request rate
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p50 / p95 / p99 latency
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error rate
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upstream health
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active connections
Quality Checklist
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valid dashboard JSON
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clear section grouping
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titles and units are present
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thresholds/status colors are meaningful
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variables exist for common filters
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default time range and refresh are sensible
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no vanity panels with no operator value
Related Skills
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research-ops -
backend-patterns -
terminal-ops
Weekly Installs509Repositoryaffaan-m/everyt…ude-codeGitHub Stars156.2KFirst Seen9 days agoSecurity AuditsGen Agent Trust HubPassSocketPassSnykPassInstalled oncodex478opencode463gemini-cli460github-copilot459amp459cline459
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