observability-specialist

Collect logs, metrics, and traces to monitor system health.

2|Updated Feb 3, 2026

Search Tags:#dashboards #logging #metrics #observability #tracing #alerting #opentelemetry

Ready to run

npx skills add https://github.com/k1lgor/virtual-company --skill observability-specialist

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: observability-specialist
Source: https://github.com/k1lgor/virtual-company/tree/main/skills/19-observability-specialist
Command: npx skills add https://github.com/k1lgor/virtual-company --skill observability-specialist

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Modern distributed systems often become opaque, making it hard to diagnose issues, measure performance, and maintain reliability. This skill standardizes observability through structured logging, metrics, and tracing to provide clear, actionable visibility.

Core Features & Use Cases

Structured Logging: enforce JSON logs with essential fields to enable traceability and debugging.
Metrics & Dashboards: collect latency, traffic, errors, and saturation metrics and visualize them in dashboards.
Distributed Tracing: propagate trace context across services and provide end-to-end visibility of request flows.
Use Case: Monitor microservices, detect latency spikes, and quickly identify failure modes in production.

Quick Start

Instrument your services with structured logging, metrics, and tracing to begin gaining visibility.

Frequently Asked Questions about observability-specialist

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

FAQPage Schema

How do I set up observability for microservices to debug production issues?▼

Observability for microservices is achieved by collecting structured logs, metrics, and distributed traces to monitor system health. This approach provides end-to-end visibility of request flows, enabling you to detect latency spikes and quickly identify failure modes across distributed environments.

What are the golden signals for monitoring system health and building dashboards?▼

The golden signals for metrics collection are latency, traffic, errors, and saturation. Gathering these metrics allows you to visualize system performance in dashboards and configure alerting to detect latency spikes and maintain reliability across your infrastructure.

Does OpenTelemetry work for distributed tracing across multiple services?▼

OpenTelemetry facilitates distributed tracing by propagating trace context across services, providing end-to-end visibility of request flows. It satisfies tracing requirements in distributed environments, allowing you to track requests as they move through multiple microservices.

Why do I need structured logging for application traceability?▼

Structured logging is needed because it enforces JSON logs with essential fields to enable traceability and debugging. By standardizing log formats, you can easily correlate log entries with metrics and traces to effectively diagnose issues across distributed systems.

Can I use this approach to alert on latency spikes in production?▼

You can alert on latency spikes by collecting latency and traffic metrics, then configuring alerting rules based on threshold changes. This allows you to detect performance issues early and maintain system reliability across your distributed production environments.