
Service Mesh Observability
- 8.1k installs
- 38.3k repo stars
- Updated July 22, 2026
- wshobson/agents
service-mesh-observability is an agent skill that Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debuggi.
About
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 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 Re.
- Service Mesh Observability
- Setting up distributed tracing across services
- Implementing service mesh metrics and dashboards
- Debugging latency and error issues
- Defining SLOs for service communication
Service Mesh Observability by the numbers
- 8,051 all-time installs (skills.sh)
- +152 installs in the week ending Jul 28, 2026 (Skillselion tracking)
- Ranked #92 of 1,041 Cloud & Infrastructure skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Jul 28, 2026 (Skillselion catalog sync)
service-mesh-observability capabilities & compatibility
- Capabilities
- service mesh observability · setting up distributed tracing across services · implementing service mesh metrics and dashboards · debugging latency and error issues · defining slos for service communication
- Use cases
- documentation
What service-mesh-observability says it does
--- 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.
Read that file when you need the concrete templates.
npx skills add https://github.com/wshobson/agents --skill service-mesh-observabilityAdd your badge
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| Installs | 8.1k |
|---|---|
| repo stars | ★ 38.3k |
| Security audit | 3 / 3 scanners passed |
| Last updated | July 22, 2026 |
| Repository | wshobson/agents ↗ |
What problem does service-mesh-observability solve for developers using this skill?
Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs
Who is it for?
Developers who need service-mesh-observability patterns described in the cached skill documentation.
Skip if: Skip when docs are empty or the task is outside the skill's documented scope.
When should I use this skill?
Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs
What you get
Actionable workflows and conventions from SKILL.md for service-mesh-observability.
- tracing configuration
- mesh metrics dashboards
- dependency visualization
Files
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
service-mesh-observability — templates and worked examples
Templates
Template 1: Istio with Prometheus & Grafana
# Install Prometheus
apiVersion: v1
kind: ConfigMap
metadata:
name: prometheus
namespace: istio-system
data:
prometheus.yml: |
global:
scrape_interval: 15s
scrape_configs:
- job_name: 'istio-mesh'
kubernetes_sd_configs:
- role: endpoints
namespaces:
names:
- istio-system
relabel_configs:
- source_labels: [__meta_kubernetes_service_name]
action: keep
regex: istio-telemetry
---
# ServiceMonitor for Prometheus Operator
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
name: istio-mesh
namespace: istio-system
spec:
selector:
matchLabels:
app: istiod
endpoints:
- port: http-monitoring
interval: 15sTemplate 2: Key Istio Metrics Queries
# Request rate by service
sum(rate(istio_requests_total{reporter="destination"}[5m])) by (destination_service_name)
# Error rate (5xx)
sum(rate(istio_requests_total{reporter="destination", response_code=~"5.."}[5m]))
/ sum(rate(istio_requests_total{reporter="destination"}[5m])) * 100
# P99 latency
histogram_quantile(0.99,
sum(rate(istio_request_duration_milliseconds_bucket{reporter="destination"}[5m]))
by (le, destination_service_name))
# TCP connections
sum(istio_tcp_connections_opened_total{reporter="destination"}) by (destination_service_name)
# Request size
histogram_quantile(0.99,
sum(rate(istio_request_bytes_bucket{reporter="destination"}[5m]))
by (le, destination_service_name))Template 3: Jaeger Distributed Tracing
# Jaeger installation for Istio
apiVersion: install.istio.io/v1alpha1
kind: IstioOperator
spec:
meshConfig:
enableTracing: true
defaultConfig:
tracing:
sampling: 100.0 # 100% in dev, lower in prod
zipkin:
address: jaeger-collector.istio-system:9411
---
# Jaeger deployment
apiVersion: apps/v1
kind: Deployment
metadata:
name: jaeger
namespace: istio-system
spec:
selector:
matchLabels:
app: jaeger
template:
metadata:
labels:
app: jaeger
spec:
containers:
- name: jaeger
image: jaegertracing/all-in-one:1.50
ports:
- containerPort: 5775 # UDP
- containerPort: 6831 # Thrift
- containerPort: 6832 # Thrift
- containerPort: 5778 # Config
- containerPort: 16686 # UI
- containerPort: 14268 # HTTP
- containerPort: 14250 # gRPC
- containerPort: 9411 # Zipkin
env:
- name: COLLECTOR_ZIPKIN_HOST_PORT
value: ":9411"Template 4: Linkerd Viz Dashboard
# Install Linkerd viz extension
linkerd viz install | kubectl apply -f -
# Access dashboard
linkerd viz dashboard
# CLI commands for observability
# Top requests
linkerd viz top deploy/my-app
# Per-route metrics
linkerd viz routes deploy/my-app --to deploy/backend
# Live traffic inspection
linkerd viz tap deploy/my-app --to deploy/backend
# Service edges (dependencies)
linkerd viz edges deployment -n my-namespaceTemplate 5: Grafana Dashboard JSON
{
"dashboard": {
"title": "Service Mesh Overview",
"panels": [
{
"title": "Request Rate",
"type": "graph",
"targets": [
{
"expr": "sum(rate(istio_requests_total{reporter=\"destination\"}[5m])) by (destination_service_name)",
"legendFormat": "{{destination_service_name}}"
}
]
},
{
"title": "Error Rate",
"type": "gauge",
"targets": [
{
"expr": "sum(rate(istio_requests_total{response_code=~\"5..\"}[5m])) / sum(rate(istio_requests_total[5m])) * 100"
}
],
"fieldConfig": {
"defaults": {
"thresholds": {
"steps": [
{ "value": 0, "color": "green" },
{ "value": 1, "color": "yellow" },
{ "value": 5, "color": "red" }
]
}
}
}
},
{
"title": "P99 Latency",
"type": "graph",
"targets": [
{
"expr": "histogram_quantile(0.99, sum(rate(istio_request_duration_milliseconds_bucket{reporter=\"destination\"}[5m])) by (le, destination_service_name))",
"legendFormat": "{{destination_service_name}}"
}
]
},
{
"title": "Service Topology",
"type": "nodeGraph",
"targets": [
{
"expr": "sum(rate(istio_requests_total{reporter=\"destination\"}[5m])) by (source_workload, destination_service_name)"
}
]
}
]
}
}Template 6: Kiali Service Mesh Visualization
# Kiali installation
apiVersion: kiali.io/v1alpha1
kind: Kiali
metadata:
name: kiali
namespace: istio-system
spec:
auth:
strategy: anonymous # or openid, token
deployment:
accessible_namespaces:
- "**"
external_services:
prometheus:
url: http://prometheus.istio-system:9090
tracing:
url: http://jaeger-query.istio-system:16686
grafana:
url: http://grafana.istio-system:3000Template 7: OpenTelemetry Integration
# OpenTelemetry Collector for mesh
apiVersion: v1
kind: ConfigMap
metadata:
name: otel-collector-config
data:
config.yaml: |
receivers:
otlp:
protocols:
grpc:
endpoint: 0.0.0.0:4317
http:
endpoint: 0.0.0.0:4318
zipkin:
endpoint: 0.0.0.0:9411
processors:
batch:
timeout: 10s
exporters:
jaeger:
endpoint: jaeger-collector:14250
tls:
insecure: true
prometheus:
endpoint: 0.0.0.0:8889
service:
pipelines:
traces:
receivers: [otlp, zipkin]
processors: [batch]
exporters: [jaeger]
metrics:
receivers: [otlp]
processors: [batch]
exporters: [prometheus]
---
# Istio Telemetry v2 with OTel
apiVersion: telemetry.istio.io/v1alpha1
kind: Telemetry
metadata:
name: mesh-default
namespace: istio-system
spec:
tracing:
- providers:
- name: otel
randomSamplingPercentage: 10Alerting Rules
apiVersion: monitoring.coreos.com/v1
kind: PrometheusRule
metadata:
name: mesh-alerts
namespace: istio-system
spec:
groups:
- name: mesh.rules
rules:
- alert: HighErrorRate
expr: |
sum(rate(istio_requests_total{response_code=~"5.."}[5m])) by (destination_service_name)
/ sum(rate(istio_requests_total[5m])) by (destination_service_name) > 0.05
for: 5m
labels:
severity: critical
annotations:
summary: "High error rate for {{ $labels.destination_service_name }}"
- alert: HighLatency
expr: |
histogram_quantile(0.99, sum(rate(istio_request_duration_milliseconds_bucket[5m]))
by (le, destination_service_name)) > 1000
for: 5m
labels:
severity: warning
annotations:
summary: "High P99 latency for {{ $labels.destination_service_name }}"
- alert: MeshCertExpiring
expr: |
(certmanager_certificate_expiration_timestamp_seconds - time()) / 86400 < 7
labels:
severity: warning
annotations:
summary: "Mesh certificate expiring in less than 7 days"Related skills
FAQ
What does service-mesh-observability do?
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 communic
When should I use 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 communic
Is service-mesh-observability safe to install?
Review the Security Audits panel on this page before installing in production.