/service-mesh-observability
Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs for service communication.
Claude Code
$ npx -y skills add wshobson/agents --skill service-mesh-observability --agent claude-code
Codex
$ npx skills add wshobson/agents --skill service-mesh-observability -a codex -y
Cursor
$ npx skills add wshobson/agents --skill service-mesh-observability -a cursor -y
Gemini CLI
$ npx skills add wshobson/agents --skill service-mesh-observability -a gemini-cli -y
GitHub Copilot
$ npx skills add wshobson/agents --skill service-mesh-observability -a github-copilot -y
OpenCode
$ npx skills add wshobson/agents --skill service-mesh-observability -a opencode -y
Windsurf
$ npx skills add wshobson/agents --skill service-mesh-observability -a windsurf -y
SKILL.md
service-mesh-observability.SKILL.mdname: service-mesh-observability
description: Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs for service communication.
Service Mesh Observability
Complete guide to observability patterns for Istio, Linkerd, and service mesh deployments.
When to Use This Skill
- Setting up distributed tracing across services
- Implementing service mesh metrics and dashboards
- Debugging latency and error issues
- Defining SLOs for service communication
- Visualizing service dependencies
- Troubleshooting mesh connectivity
Core Concepts
1. Three Pillars of Observability
┌─────────────────────────────────────────────────────┐
│ Observability │
├─────────────────┬─────────────────┬─────────────────┤
│ Metrics │ Traces │ Logs │
│ │ │ │
│ • Request rate │ • Span context │ • Access logs │
│ • Error rate │ • Latency │ • Error details │
│ • Latency P50 │ • Dependencies │ • Debug info │
│ • Saturation │ • Bottlenecks │ • Audit trail │
└─────────────────┴─────────────────┴─────────────────┘
2. Golden Signals for Mesh
| Signal | Description | Alert Threshold | | -------------- | ------------------------- | ----------------- | | **Latency** | Request duration P50, P99 | P99 > 500ms | | **Traffic** | Requests per second | Anomaly detection | | **Errors** | 5xx error rate | > 1% | | **Saturation** | Resource utilization | > 80% |
Templates and detailed worked examples
Full template library and detailed worked examples live in `references/details.md`. Read that file when you need the concrete templates.
Best Practices
Do's
- **Sample appropriately** - 100% in dev, 1-10% in prod
- **Use trace context** - Propagate headers consistently
- **Set up alerts** - For golden signals
- **Correlate metrics/traces** - Use exemplars
- **Retain strategically** - Hot/cold storage tiers
Don'ts
- **Don't over-sample** - Storage costs add up
- **Don't ignore cardinality** - Limit label values
- **Don't skip dashboards** - Visualize dependencies
- **Don't forget costs** - Monitor observability costs
Read more
name: service-mesh-observability description: Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs for service communication.
Service Mesh Observability
Complete guide to observability patterns for Istio, Linkerd, and service mesh deployments.
When to Use This Skill
- Setting up distributed tracing across services
- Implementing service mesh metrics and dashboards
- Debugging latency and error issues
- Defining SLOs for service communication
- Visualizing service dependencies
- Troubleshooting mesh connectivity
Core Concepts
1. Three Pillars of Observability
┌─────────────────────────────────────────────────────┐ │ Observability │ ├─────────────────┬─────────────────┬─────────────────┤ │ Metrics │ Traces │ Logs │ │ │ │ │ │ • Request rate │ • Span context │ • Access logs │ │ • Error rate │ • Latency │ • Error details │ │ • Latency P50 │ • Dependencies │ • Debug info │ │ • Saturation │ • Bottlenecks │ • Audit trail │ └─────────────────┴─────────────────┴─────────────────┘
2. Golden Signals for Mesh
| Signal | Description | Alert Threshold | | -------------- | ------------------------- | ----------------- | | **Latency** | Request duration P50, P99 | P99 > 500ms | | **Traffic** | Requests per second | Anomaly detection | | **Errors** | 5xx error rate | > 1% | | **Saturation** | Resource utilization | > 80% |
Templates and detailed worked examples
Full template library and detailed worked examples live in `references/details.md`. Read that file when you need the concrete templates.
Best Practices
Do's
- **Sample appropriately** - 100% in dev, 1-10% in prod
- **Use trace context** - Propagate headers consistently
- **Set up alerts** - For golden signals
- **Correlate metrics/traces** - Use exemplars
- **Retain strategically** - Hot/cold storage tiers
Don'ts
- **Don't over-sample** - Storage costs add up
- **Don't ignore cardinality** - Limit label values
- **Don't skip dashboards** - Visualize dependencies
- **Don't forget costs** - Monitor observability costs
Use one collection of plugins, agents, skills, and commands across Claude Code, OpenAI Codex CLI, Cursor, OpenCode, Antigravity CLI, GitHub Copilot, and Pi. A harness is the coding tool that loads and runs the components.
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Questions about service-mesh-observability.
- Which coding agents can use service-mesh-observability?
- service-mesh-observability installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

