Are there pre-built alerting rules included?

Yes, it includes PrometheusRule templates for high error rates, high latency, and expiring mesh certificates to ensure proactive maintenance.

How does this help with debugging service latency?

It provides distributed tracing templates and P99 latency queries that allow you to visualize the entire request path and identify specific service bottlenecks.

Does this skill support both Istio and Linkerd?

Yes, it includes specific configurations and CLI commands for both major service meshes: Istio (using Prometheus and Kiali) and Linkerd (using the viz extension).

What are the 'Golden Signals' monitored by this skill?

It tracks the four critical signals for service health: Latency (P50/P99), Traffic (Requests per second), Errors (5xx rates), and Saturation (resource utilization).

Can I integrate this with OpenTelemetry?

Absolutely. The skill includes templates for setting up OpenTelemetry Collectors to receive and export traces and metrics from your mesh.

Service Mesh Observability

Name: Service Mesh Observability
Author: EngineerWithAI

byEngineerWithAI

Analytics & Monitoring

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

About

This skill provides a complete guide and automated templates for establishing robust observability patterns within service mesh deployments. It enables developers and SREs to implement the 'Three Pillars of Observability'—metrics, traces, and logs—while specifically monitoring 'Golden Signals' like latency, traffic, errors, and saturation. By leveraging pre-configured templates for Prometheus, Grafana, Jaeger, Kiali, and OpenTelemetry, the skill streamlines the process of debugging microservice latency, visualizing complex service dependencies, and implementing Service Level Objectives (SLOs) across cloud-native infrastructures.

Key Features

Distributed tracing integration with Jaeger and OpenTelemetry
Pre-defined PromQL queries for request rates, error percentages, and P99 latency
Service topology visualization via Kiali and Grafana dashboard JSONs
Proactive alerting rules for high error rates and mesh certificate expirations
0 GitHub stars
Automated Istio and Linkerd observability configuration templates

Use Cases

Setting up centralized dashboards to monitor the health and performance of an Istio mesh
Implementing distributed tracing to visualize request flow and identify bottlenecks across service boundaries
Troubleshooting high latency or intermittent errors in a complex microservices architecture

About

Key Features

Distributed tracing integration with Jaeger and OpenTelemetry
Pre-defined PromQL queries for request rates, error percentages, and P99 latency
Service topology visualization via Kiali and Grafana dashboard JSONs
Proactive alerting rules for high error rates and mesh certificate expirations
0 GitHub stars
Automated Istio and Linkerd observability configuration templates

Use Cases

Setting up centralized dashboards to monitor the health and performance of an Istio mesh
Implementing distributed tracing to visualize request flow and identify bottlenecks across service boundaries
Troubleshooting high latency or intermittent errors in a complex microservices architecture