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Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | prometheus-configuration |
| description | Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems. |
Complete guide to Prometheus setup, metric collection, scrape configuration, and recording rules.
Configure Prometheus for comprehensive metric collection, alerting, and monitoring of infrastructure and applications.
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
Check scrape targets:
curl http://localhost:9090/api/v1/targets
Check configuration:
curl http://localhost:9090/api/v1/status/config
Test query:
curl 'http://localhost:9090/api/v1/query?query=up'
grafana-dashboards - For visualizationslo-implementation - For SLO monitoringdistributed-tracing - For request tracingUse when preparing the narrative, sources, and design context for a new editable PPTX deck.
Use when validating or repairing an editable PPTX deck for geometry, accessibility, native editability, source lineage, and OOXML package integrity.
Use when analyzing a reference PPTX for read-only structure, theme, typography, layout rhythm, diagnostics, derived template catalogs, or safe OOXML package inspection.
Use when authoring or repairing a coordinate-explicit JSON specification for an editable PPTX deck.
Use when selecting and placing approved supporting icons, images, SVGs, diagrams, or infographics in an editable PPTX deck.
Set up a working ML training/inference environment on NVIDIA DGX Spark (GB10, aarch64, CUDA 13). Use when installing PyTorch/Unsloth/TRL/vLLM on DGX Spark, hitting libcudart or wheel-ABI errors on aarch64, or choosing between NGC containers and bare pip installs.