Which service meshes does this skill support?

This skill provides specialized guidance and templates for Istio and Linkerd, as well as general patterns for OpenTelemetry and Jaeger.

Does it help with setting up alerts?

Absolutely. It provides PrometheusRule templates for critical signals like high P99 latency, 5xx error rates, and expiring mesh certificates.

How does this improve microservices debugging?

By implementing distributed tracing and service topology visualization, it allows you to trace requests across service boundaries and identify the exact source of failures.

Can I use these templates for production environments?

Yes, the skill includes production-grade best practices for sampling rates, resource utilization, and storage management to ensure stability and cost-efficiency.

Service Mesh Observability

Name: Service Mesh Observability
Author: as4584

byas4584

分析と監視

Implements comprehensive monitoring, distributed tracing, and visualization for microservice architectures using Istio, Linkerd, and OpenTelemetry.

概要

This skill provides production-ready patterns and templates for monitoring microservices communication within a service mesh. It offers automated configurations for Prometheus metrics, Jaeger tracing, and Grafana dashboards, enabling developers to debug latency, visualize service dependencies, and establish Service Level Objectives (SLOs). Whether you are troubleshooting mesh connectivity or implementing the Three Pillars of Observability, this skill streamlines the complex setup of telemetry and alerting across Kubernetes environments.

主な機能

Pre-configured Prometheus queries for monitoring Golden Signals (Latency, Traffic, Errors, Saturation)
Service topology visualization using Kiali and Linkerd Viz patterns
Ready-to-use Grafana dashboard JSON templates for service mesh health
Distributed tracing configuration for Jaeger and OpenTelemetry integration
Automated alerting rules for high error rates, latency spikes, and certificate expirations
0 GitHub stars

ユースケース

Debugging complex latency issues and bottlenecks in microservices communication
Visualizing service dependencies and traffic flow in large-scale Kubernetes deployments
Implementing automated SLO monitoring and alerting for service-to-service traffic

概要

主な機能

Pre-configured Prometheus queries for monitoring Golden Signals (Latency, Traffic, Errors, Saturation)
Service topology visualization using Kiali and Linkerd Viz patterns
Ready-to-use Grafana dashboard JSON templates for service mesh health
Distributed tracing configuration for Jaeger and OpenTelemetry integration
Automated alerting rules for high error rates, latency spikes, and certificate expirations
0 GitHub stars

ユースケース

Debugging complex latency issues and bottlenecks in microservices communication
Visualizing service dependencies and traffic flow in large-scale Kubernetes deployments
Implementing automated SLO monitoring and alerting for service-to-service traffic