ipIterPrompt

Service Mesh Observability

Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, o

wshobson · agentsUpdated 2026-06-03944 copies

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. Imported from wshobson/agents (MIT).

SKILL.md

---
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

Run this skill on a real model without leaving the page. Every run is saved to your history for this skill.

How to use

  1. 1Save the content below as SKILL.md in your agent's skills directory (e.g. .claude/skills/<name>/SKILL.md).
  2. 2Or paste it directly into the conversation as context before asking the agent to do the task.
  3. 3Adjust any project-specific paths or conventions mentioned in the skill to match your setup.

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