monitoring-observability

Integrate metrics, logs, and traces with OpenTelemetry and Prometheus.

3|Updated Feb 6, 2026

Search Tags:#monitoring #logging #metrics #observability #tracing #grafana #prometheus

Ready to run

npx skills add https://github.com/1Mangesh1/dev-skills-collection --skill monitoring-observability-1mangesh1

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: monitoring-observability
Source: https://github.com/1Mangesh1/dev-skills-collection/tree/main/skills/monitoring-observability
Command: npx skills add https://github.com/1Mangesh1/dev-skills-collection --skill monitoring-observability-1mangesh1

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires psutil, jq, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Observability patterns and best practices to help teams implement structured logging, metrics collection, tracing, alerting, and dashboard visibility across distributed systems.

Core Features & Use Cases

Three Pillars of Observability: Metrics, Logs, and Traces, with guidance on instrumentation and tooling (Prometheus, Grafana, Jaeger, OpenTelemetry).
Best practices for alerting, dashboards, runbooks, and incident response across cloud-native architectures.
Proven patterns for instrumenting applications, correlating traces with logs and metrics, and enabling rapid root-cause analysis across services.

Quick Start

Configure your system to collect metrics, logs, and traces using standard OpenTelemetry instrumentation and Prometheus dashboards.

Frequently Asked Questions about monitoring-observability

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

FAQPage Schema

How do I implement observability across distributed systems using metrics, logs, and traces?▼

Observability across distributed systems requires integrating metrics, logs, and traces via standard OpenTelemetry instrumentation. You collect data from microservices and cloud-native architectures to enable real-time dashboards, alerting, and rapid root-cause analysis across services.

What's the best way to correlate traces with logs and metrics for root-cause analysis?▼

Correlating traces with logs and metrics requires proven instrumentation patterns that link telemetry data across services. By applying OpenTelemetry standards, you can trace requests through microservices and match them with corresponding log entries and metric anomalies for rapid root-cause analysis.

How do I set up Prometheus metrics and Grafana dashboards for cloud-native applications?▼

Setting up Prometheus metrics and Grafana dashboards involves configuring Prometheus-compatible metrics collection and building real-time visualizations. You instrument your cloud-native applications to expose metrics, then query and display them in Grafana to monitor system health and performance.

Do I need OpenTelemetry instrumentation to enable tracing and structured logging in microservices?▼

OpenTelemetry instrumentation is required to standardize tracing and structured logging across microservices. It provides the framework to collect and export telemetry data, ensuring your distributed traces and logs are correlated and compatible with tools like Jaeger and Prometheus.

Can I use this observability approach for event-driven applications needing real-time alerting?▼

This observability approach supports event-driven applications needing real-time alerting by defining clear alerting rules and runbooks. It applies to modern cloud-native architectures, enabling dashboards and incident response workflows for event-driven microservices.

What are the limitations of using Prometheus and Grafana without distributed tracing?▼

Using Prometheus and Grafana without distributed tracing limits your ability to perform rapid root-cause analysis across services. While metrics and dashboards show system anomalies, traces are required to follow requests through microservices and pinpoint the exact failure point.