observability

Correlate logs, metrics, and traces to debug production system behavior.

Updated Jun 5, 2026

Search Tags:#logging #metrics #observability #tracing #opentelemetry #sre #system-design

Ready to run

npx skills add https://github.com/hung-phan/system-skills --skill observability-hung-phan

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: observability
Source: https://github.com/hung-phan/system-skills/tree/main/skills/system-review/references/reliability/observability
Command: npx skills add https://github.com/hung-phan/system-skills --skill observability-hung-phan

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps debug production systems by allowing arbitrary questions about system behavior, identifying unknown-unknowns, and correlating events across logs, metrics, and traces.

Core Features & Use Cases

Causal Analysis: Trace the path of requests across services to identify bottlenecks and failures.
Root Cause Debugging: Analyze metrics, logs, and traces for anomalies affecting specific users, deployments, or features.
Observability Strategy: Design and implement robust monitoring using OpenTelemetry, structured logging, and the RED/USE methods.
Use Case: When a specific user experiences a slow API response, use this Skill to correlate traces, logs, and metrics to pinpoint the root cause, whether it's a specific service, deployment, or rare code path.

Quick Start

Use the observability skill to analyze a trace for a latency spike impacting user ID 1234.

Frequently Asked Questions about observability

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

FAQPage Schema

How do I debug latency spikes and cascading failures using logs, metrics, and traces?▼

Debug latency spikes by correlating logs, metrics, and traces using OpenTelemetry and structured data models. This approach traces request paths across services to identify bottlenecks, pinpoint failures, and investigate specific user issues or rare code paths.

What is the best way to design an observability strategy for production systems?▼

Design an observability strategy by implementing robust monitoring using OpenTelemetry, structured logging, and the RED/USE methods. This allows you to investigate production system behavior by asking arbitrary questions to identify unknown-unknowns and correlate events.

Can I use OpenTelemetry to investigate user-specific bugs in production?▼

Yes, you can use OpenTelemetry to investigate user-specific bugs in production. By correlating traces, logs, and metrics, you can analyze anomalies affecting specific users, deployments, or features to pinpoint the exact root cause of an issue.

How does tracing request paths across services help with root cause debugging?▼

Tracing request paths across services enables root cause debugging by visually mapping the journey of a request. This causal analysis identifies exactly which service, deployment, or rare code path caused a failure or latency spike.

Do I need knowledge of system design principles to set up effective monitoring?▼

Yes, designing and implementing robust monitoring requires knowledge of system design principles and observability best practices. This foundational knowledge is necessary to effectively correlate events and investigate arbitrary production system behavior questions.

When should I not use a single observability signal instead of correlating logs, metrics, and traces?▼

You should not rely on a single signal when investigating complex production behavior like cascading failures. Correlating logs, metrics, and traces is necessary to identify unknown-unknowns and pinpoint root causes across distributed services accurately.