service-mesh-observability

Implement full-stack observability for service mesh deployments with metrics, traces, and logs.

20|3|Updated Jul 26, 2025

Search Tags:#dashboards #metrics #observability #tracing #service-mesh #jaeger #kiali

Ready to run

npx skills add https://github.com/thc1006/nephoran-intent-operator --skill service-mesh-observability

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: service-mesh-observability
Source: https://github.com/thc1006/nephoran-intent-operator/tree/main/.claude/skills/service-mesh-observability
Command: npx skills add https://github.com/thc1006/nephoran-intent-operator --skill service-mesh-observability

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides comprehensive observability for service meshes, enabling end-to-end visibility across metrics, traces, logs, and health of mesh deployments.

Core Features & Use Cases

Distributed tracing across mesh traffic to identify latency sources and dependencies.
Metrics collection and dashboards for golden signals (latency, traffic, errors, saturation) with tools like Prometheus, Grafana, Kiali, or Jaeger.
Debugging workflows and SLO definitions to surface bottlenecks and dependencies for remediation.
Use Case: When debugging an intermittent service latency, deploy the observability stack to collect traces, surface latency hotspots, and visualize service interactions.

Quick Start

Configure and run the observability stack for your mesh by enabling tracing, metrics collection, and dashboards in your environment.

Frequently Asked Questions about service-mesh-observability

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I set up observability for a service mesh to collect metrics, traces, and logs?▼

Service mesh observability requires deploying distributed tracing, metrics collection, and dashboard visualization across your mesh. You enable tools like Jaeger for tracing, Prometheus for metrics, and Grafana or Kiali dashboards to visualize mesh health and surface dependencies.

What's the best way to debug intermittent latency in distributed services using Istio or Linkerd?▼

Debugging intermittent latency in distributed services uses distributed tracing to identify latency sources and service dependencies. By deploying an observability stack with Jaeger or OpenTelemetry, you surface latency hotspots and visualize service interactions for remediation.

Does this observability approach work with both Istio and Linkerd platforms?▼

Yes, full-stack observability applies across Istio, Linkerd, or similar service mesh platforms. It collects metrics, traces, and logs across distributed services in development, testing, and production environments regardless of the specific mesh implementation.

Can I use OpenTelemetry and Jaeger for distributed tracing across mesh traffic?▼

Yes, OpenTelemetry and Jaeger are core requirements for distributed tracing across mesh traffic. They identify latency sources and map service dependencies to provide end-to-end visibility into mesh health.

How do I build dashboards for golden signals like latency, traffic, errors, and saturation?▼

Building dashboards for golden signals uses Prometheus for metrics collection and Grafana or Kiali for visualization. These tools surface latency, traffic, errors, and saturation data to monitor mesh health and define SLO-based alerts.

Do I need Prometheus and Grafana to visualize service mesh health?▼

Yes, Prometheus for metrics and Grafana or Kiali for dashboards are required to visualize service mesh health. They enable SLO definitions and debugging workflows to surface bottlenecks across distributed services.