Does this skill support both Istio and Linkerd?

Yes, it includes specific configurations, dashboard templates, and CLI patterns for both Istio and Linkerd environments.

Is OpenTelemetry supported?

Yes, the skill includes patterns for integrating the OpenTelemetry Collector with service mesh telemetry for vendor-neutral data collection.

How does this help with debugging service latency?

It provides P99 latency queries and distributed tracing templates to identify exactly which service hop or sidecar proxy is causing delays.

Can I use this for SLO (Service Level Objective) management?

Absolutely. It includes templates for defining and alerting on the four Golden Signals: Latency, Traffic, Errors, and Saturation.

Service Mesh Observability

Name: Service Mesh Observability
Author: GaitanS

byGaitanS

Analíticas y Monitorización

Implements comprehensive monitoring, distributed tracing, and visualization for Istio and Linkerd service mesh environments.

Acerca de

This skill provides a complete framework for monitoring and debugging service mesh deployments. It offers standardized patterns for implementing the three pillars of observability—metrics, traces, and logs—specifically tailored for microservices communication. Whether you are setting up Prometheus and Grafana dashboards, configuring Jaeger for distributed tracing, or defining Service Level Objectives (SLOs), this skill guides developers through complex configurations for Istio and Linkerd to ensure system reliability and performance visibility.

Características Principales

Automated alerting rules for critical service mesh health thresholds
0 GitHub stars
Standardized templates for Istio, Linkerd, and OpenTelemetry integration
Pre-configured PromQL queries for tracking Golden Signals like latency and error rates
Service dependency visualization patterns using Kiali and Grafana dashboards
Distributed tracing setup using Jaeger and Zipkin for cross-service visibility

Casos de Uso

Setting up real-time monitoring dashboards and SLO alerts for microservices
Debugging cross-service latency and connectivity issues in Kubernetes clusters
Implementing distributed tracing to track request flows across complex architectures

Acerca de

Características Principales

Automated alerting rules for critical service mesh health thresholds
0 GitHub stars
Standardized templates for Istio, Linkerd, and OpenTelemetry integration
Pre-configured PromQL queries for tracking Golden Signals like latency and error rates
Service dependency visualization patterns using Kiali and Grafana dashboards
Distributed tracing setup using Jaeger and Zipkin for cross-service visibility

Casos de Uso

Setting up real-time monitoring dashboards and SLO alerts for microservices
Debugging cross-service latency and connectivity issues in Kubernetes clusters
Implementing distributed tracing to track request flows across complex architectures