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grafana-monitoring

Query Grafana Cloud logs, metrics, traces, dashboards, alerts, and incidents for troubleshooting.

3|Updated Mar 22, 2026
Search Tags:#monitoring#observability#grafana#prometheus#incidents#loki#tempo
One-click install
npx skills add https://github.com/CodeAlive-AI/ceo-ai-os --skill grafana-monitoring
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: grafana-monitoring
Source: https://github.com/CodeAlive-AI/ceo-ai-os/tree/main/skills/grafana-monitoring
Command: npx skills add https://github.com/CodeAlive-AI/ceo-ai-os --skill grafana-monitoring

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill turns Grafana Cloud data into fast answers for production troubleshooting, replacing manual log digging, metric hunting, and trace chasing with a guided observability workflow.

Core Features & Use Cases

  • Logs, metrics, and traces: Inspect Loki logs, Prometheus metrics, and Tempo traces from one operational playbook.
  • Alerts, incidents, and on-call: Check firing alerts, open incidents, and current on-call coverage before escalating.
  • Practical examples: Use it to diagnose slow APIs, production errors, job failures, LLM cost spikes, and repository indexing problems.

Quick Start

Ask the skill to investigate the affected service in Grafana Cloud and summarize the most likely root cause, supporting evidence, and next action.

Frequently Asked Questions about grafana-monitoring

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

FAQPage Schema
How do I troubleshoot slow API responses using Grafana Cloud logs and metrics?▼

Query aggregated Prometheus metrics for latency and Tempo traces to identify bottlenecks across your service. This workflow inspects Loki logs and dashboards to pinpoint the root cause of slow API responses.

Can I investigate production errors and alert incidents directly from Grafana Cloud?▼

Yes, investigate production errors by reviewing firing alerts, open incidents, and on-call coverage. Sift-assisted error pattern detection helps identify the root cause and next action before escalating.

What is the best way to analyze LLM cost spikes in Grafana observability data?▼

Analyze LLM cost spikes by querying service-scoped Loki logs and aggregated Prometheus metrics. This workflow reviews dashboard data to summarize the most likely root cause and supporting evidence.

Do I need Prometheus and Loki configured to diagnose production issues with this workflow?▼

Yes, this workflow requires Prometheus, Loki, and Tempo configured in Grafana Cloud. It queries service-scoped logs, aggregated metrics, and traces to troubleshoot infrastructure and application observability problems.

Why are my repository indexing checks failing in Grafana dashboards?▼

Repository indexing checks fail due to job failures or infrastructure issues. Query Loki logs and Prometheus metrics to review job failure patterns and dashboard data to find the root cause.

Does Grafana Sift work with Tempo traces to detect error patterns?▼

Yes, Sift works with Tempo traces and Loki logs to detect error patterns. This workflow analyzes traces and service-scoped logs to summarize the most likely root cause and next action for production issues.

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