sickn33/antigravity-awesome-skills/service-mesh-observability

Name: service-mesh-observability
Author: sickn33

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By sickn33
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sickn33/antigravity-awesome-skills
skills/service-mesh-observability/SKILL.md
Updated 9 May 2026
Version 1.0.0

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Complete guide to observability patterns for Istio, Linkerd, and service mesh deployments.

Install

npx vskill@latest install sickn33/antigravity-awesome-skills/service-mesh-observability

SKILL.md

Service Mesh Observability

Complete guide to observability patterns for Istio, Linkerd, and service mesh deployments.

Do not use this skill when

The task is unrelated to service mesh observability
You need a different domain or tool outside this scope

Instructions

Clarify goals, constraints, and required inputs.
Apply relevant best practices and validate outcomes.
Provide actionable steps and verification.

Use this skill when

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

These are version-specific fragments, not a complete deployable stack. Pin mesh/collector/operator versions, export or render the supported schema and review manifests before applying. Supply Services, RBAC and receiver/provider wiring separately; a ServiceMonitor for istiod does not by itself scrape every workload proxy. Thresholds are examples requiring service-specific SLOs.

Keep tracing/tap output inside authorized environments, redact sensitive attributes and restrict access. The anonymous Kiali example is for isolated trusted development only; configure authenticated access and narrow namespace/RBAC scope before shared use; see Kiali authentication.

Template 1: Istio with Prometheus & Grafana

yaml

# 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: 15s

Template 2: Key Istio Metrics Queries

promql

# 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

yaml

# 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

bash

# 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-namespace

Template 5: Grafana Dashboard JSON

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

yaml

# 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:3000

Template 7: OpenTelemetry Integration

Use OTLP to a Jaeger OTLP-enabled receiver and expose its 4317 Service port. The native Jaeger Collector exporter was removed from standard distributions; see OpenTelemetry migration. Plaintext insecure: true below is an isolated-network example; use authenticated TLS for untrusted links. Configure the referenced Istio otel extension provider separately.

yaml

# 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:
      otlp/jaeger:
        endpoint: jaeger-collector:4317
        tls:
          insecure: true
      prometheus:
        endpoint: 0.0.0.0:8889
 
    service:
      pipelines:
        traces:
          receivers: [otlp, zipkin]
          processors: [batch]
          exporters: [otlp/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: 10

Alerting Rules

yaml

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"

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

Resources

Limitations

Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Security

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Source

SKILL.md in the repositoryCheckingskills/service-mesh-observability/SKILL.md

Popularity

Repository stars: 36,907
Repository forks: 6,036
Repository npm downloads, 7 days: 6,426
7-day trend score: 73

Stars and forks are for the whole GitHub repository, not this skill alone. Downloads are for the repository's npm package. Refreshed 9 May 2026, 5 months ago.

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