Does it include visualization tools?

Yes, it provides configuration templates for Kiali service graphs, Linkerd Viz dashboards, and specialized Grafana JSON definitions.

Which service meshes does this skill support?

This skill provides specialized templates and best practices for both Istio and Linkerd, as well as general OpenTelemetry integration for other mesh architectures.

Can this skill help with distributed tracing?

Yes, it includes detailed implementation patterns for Jaeger and OpenTelemetry collectors to track request flow across distributed microservices.

What metrics are prioritized by this skill?

The skill focuses on the four 'Golden Signals': Latency, Traffic, Errors, and Saturation, providing specific PromQL queries to monitor each.

Service Mesh Observability

Name: Service Mesh Observability
Author: wshobson

bywshobson

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23,194

Analíticas y Monitorización

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

Acerca de

This skill provides a complete framework for instrumenting service meshes with deep visibility into microservice interactions. It offers standardized templates for deploying observability stacks including Prometheus, Grafana, Jaeger, and Kiali, while focusing on the 'Golden Signals' of latency, traffic, errors, and saturation. Whether you are debugging complex network bottlenecks, defining Service Level Objectives (SLOs), or visualizing service dependencies, this skill streamlines the configuration of telemetry and alerting within Kubernetes environments to ensure robust production reliability.

Características Principales

PromQL snippets for calculating P99 latency and error rates
Automated Kiali and Grafana dashboard configurations
Distributed tracing setup using Jaeger and OpenTelemetry
23,194 GitHub stars
Pre-configured Istio and Linkerd monitoring templates
Standardized alerting rules for mesh health and certificate expiry

Casos de Uso

Debugging high latency and connectivity issues across microservices
Implementing automated SLO tracking for service-to-service communication
Visualizing real-time service dependencies and traffic topology

Acerca de

Características Principales

PromQL snippets for calculating P99 latency and error rates
Automated Kiali and Grafana dashboard configurations
Distributed tracing setup using Jaeger and OpenTelemetry
23,194 GitHub stars
Pre-configured Istio and Linkerd monitoring templates
Standardized alerting rules for mesh health and certificate expiry

Casos de Uso

Debugging high latency and connectivity issues across microservices
Implementing automated SLO tracking for service-to-service communication
Visualizing real-time service dependencies and traffic topology