service-mesh-observability
Guidance for setting up metrics, logs, and traces to monitor service mesh performance and reliability.
Install
mkdir -p .claude/skills/service-mesh-observability && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/449" && unzip -o skill.zip -d .claude/skills/service-mesh-observability && rm skill.zipInstalls to .claude/skills/service-mesh-observability
Activation
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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.Key capabilities
- →Implement distributed tracing across services
- →Define and monitor service mesh golden signals
- →Configure observability dashboards
- →Troubleshoot latency and connectivity issues
- →Set up alerting thresholds for error rates
How it works
The skill provides patterns for collecting metrics, traces, and logs from service mesh components. It uses golden signals to define health and performance benchmarks.
Inputs & outputs
When to use service-mesh-observability
- →Set up distributed tracing
- →Define service mesh SLOs
- →Debug high latency in mesh services
- →Configure observability dashboards
About this skill
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
When not to use it
- →When the application is not deployed on a service mesh
- →When the environment lacks sufficient resource budget for observability overhead
Prerequisites
Limitations
- →Observability data collection can impact system performance
- →Requires consistent header propagation across all services
How it compares
It focuses on mesh-specific observability, correlating metrics and traces to identify bottlenecks that are invisible to standard application monitoring.
Compared to similar skills
service-mesh-observability side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| service-mesh-observability (this skill) | 5 | 2mo | No flags | Advanced |
| devops-troubleshooter | 1 | 4mo | No flags | Advanced |
| observability-engineer | 12 | 4mo | No flags | Advanced |
| observability-monitoring-monitor-setup | 1 | 4mo | No flags | Intermediate |
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