Skills

Service Mesh Observability

Implement comprehensive observability for service meshes including distributed tracing...

Install

npx skills add wshobson/agents --skill service-mesh-observability -g -a claude-code -y
Repository
wshobson/agents42.1k
Category
Testing
Updated
5d ago
License
MIT
Context cost
Lightabout 536 tokens
Runs scripts
No, instructions only

What it does

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

SignalDescriptionAlert Threshold
LatencyRequest duration P50, P99P99 > 500ms
TrafficRequests per secondAnomaly detection
Errors5xx error rate> 1%
SaturationResource 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

Read the whole SKILL.md on GitHub

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