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.
Install with the open skills CLI (global, non-interactive — available in every Claude Code session):
npx skills add wshobson/agents --skill "service-mesh-observability" -g -a claude-code -yOr manually — clone and copy the skill directory (SKILL.md + companion files):
git clone --depth 1 https://github.com/wshobson/agents /tmp/agents && cp -r /tmp/agents/plugins/cloud-infrastructure/skills/service-mesh-observability ~/.claude/skills/service-mesh-observability-wshobsonThis skill is a directory: SKILL.md is the entry point; the files below ship with it.
---
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 when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when implementing any feature or bugfix, before writing implementation code