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Deploy & cloud (DevOps)48k · #4148

service-mesh-observability

Guides your agent in configuring observability for service meshes like Istio and Linkerd.

What it does

This tool helps you understand how your software services are communicating. It collects information about performance, errors, and dependencies between them, using tools like Istio and Linkerd.

When to use it

  • ✓When you want to see how services connect.
  • ✓When investigating why a service is slow or has errors.
  • ✓To set up alerts about service performance.

Example of what to ask your AI

“How can I set up latency monitoring for my services using Istio?”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/service-mesh-observability/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/service-mesh-observability/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

It uses 'observability' patterns to collect metrics, trace requests, and analyze logs. This allows you to visualize data flow and identify problems.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add sickn33/agentic-awesome-skills --skill service-mesh-observability

Or download just the file:

curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/service-mesh-observability/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

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

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: 15s

Template 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

…
FAQ

What are 'metrics', 'traces', and 'logs'?

Metrics are numbers about performance (e.g., request counts). Traces show a request's path between services. Logs are detailed messages about events.

What are 'Golden Signals'?

These are the 4 most important metrics for monitoring services: Latency, Traffic, Errors, and Saturation (resource usage).

What are Istio and Linkerd?

These are tools called 'service mesh' that help manage and observe communication between services in complex systems.

Details

Original description by the author

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

repo: sickn33/agentic-awesome-skills

Popularity

GitHub stars
48k
Ranking position
#4148
License
MIT
Updated
10/15/2026

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