service-mesh-observability
- Use it when:
- You run Istio or Linkerd on Kubernetes and need request metrics, traces across services, a dependency map or alerts on mesh traffic.
- It does:
- Frames mesh monitoring around the golden signals, latency, traffic, errors and saturation, with starting alert thresholds such as P99 over 500 ms or errors over 1%.
- You get:
- YAML and commands that wire Prometheus, Jaeger, Kiali and an OpenTelemetry collector into Istio, PromQL queries, a Grafana dashboard and alert rules.
- Sampling:
- Trace every request in development and 1–10% in production.
TL;DR
Observability for the traffic between services in an Istio or Linkerd mesh. The SKILL.md sets out the three pillars, metrics, traces and logs, and the four golden signals with suggested thresholds, plus rules: sample appropriately, propagate trace headers consistently, alert on the golden signals, link metrics to traces with exemplars and tier storage; don't over-sample, let label cardinality grow, skip dependency dashboards or forget what observability costs. Its reference file is mostly Istio: a Prometheus scrape config and a Prometheus Operator ServiceMonitor; PromQL for request rate, 5xx rate, P99 latency, TCP connections and request size; Jaeger with Istio tracing turned on; a Grafana dashboard with request rate, error rate, P99 latency and service topology panels; Kiali to visualize the mesh; and an OpenTelemetry collector feeding Jaeger and Prometheus, with Istio sampling 10% of traces. For Linkerd it gives linkerd viz commands for top requests, per-route metrics, live traffic and service edges. Prometheus alert rules fire on errors above 5%, P99 latency over one second and mesh certificates expiring within a week.
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SKILL.md
From wshobson/agents at 4bde316. Checked daily, last changed Nov 6, 2026.
Frontmatter
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