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metrics-pipeline-builder skill

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This skill helps you build scalable metrics pipelines with Prometheus, Grafana, and custom exporters for reliable observability.

npx playbooks add skill dexploarer/hyper-forge --skill metrics-pipeline-builder

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md
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---
name: metrics-pipeline-builder
description: Build metrics collection pipelines using Prometheus, Grafana, and custom exporters
allowed-tools: [Read, Write, Edit, Bash, Grep, Glob]
---

# metrics pipeline builder

Build metrics collection pipelines using Prometheus, Grafana, and custom exporters

## When to Use

This skill activates when you need to build metrics collection pipelines using prometheus, grafana, and custom exporters.

## Quick Example

```yaml
# Configuration example for metrics-pipeline-builder
# See full documentation in the skill implementation
```

## Best Practices

- ✅ Follow industry standards
- ✅ Document all configurations
- ✅ Test thoroughly before production
- ✅ Monitor and alert appropriately
- ✅ Regular maintenance and updates

## Related Skills

- `microservices-orchestrator`
- `compliance-auditor`
- Use `enterprise-architect` agent for design consultation

## Implementation Guide

[Detailed implementation steps would go here in production]

This skill provides comprehensive guidance for build metrics collection pipelines using prometheus, grafana, and custom exporters.

Overview

This skill helps you design and build observability pipelines using Prometheus, Grafana, and custom exporters. It focuses on collecting, transforming, and visualizing metrics for services and infrastructure in TypeScript-based platforms. The guidance is practical, implementation-focused, and suited for game-development backends and microservices.

How this skill works

The skill inspects your service topology and recommends where to place exporters and scrape jobs. It generates configuration fragments for Prometheus scrape_configs, service discovery patterns, and Grafana dashboards and panels. It also outlines patterns for writing lightweight TypeScript exporters and for exposing application metrics in standard formats.

When to use it

  • You need centralized metrics collection across microservices or game servers.
  • You want repeatable Prometheus and Grafana configs for staging and production.
  • You must instrument TypeScript services or write custom exporters.
  • You need to convert application telemetry into actionable dashboards and alerts.
  • You are preparing an SRE-ready observability plan for launch or scale-up.

Best practices

  • Standardize metric names and labels using clear conventions (service, instance, region).
  • Keep exporters minimal: expose a few well-defined metrics and avoid heavy processing.
  • Use relabeling and service discovery to reduce manual scrape configuration.
  • Version control Prometheus rules and Grafana dashboards as code.
  • Validate scrape throughput and retention to manage storage and query performance.

Example use cases

  • Instrument a TypeScript game server to expose player and performance metrics via a custom exporter.
  • Create Prometheus scrape jobs for dynamic Kubernetes service discovery and autoscaling metrics.
  • Build Grafana dashboards for latency, error rates, and resource utilization across regions.
  • Implement alerting rules for high player concurrency, memory leaks, or CPU spikes.
  • Migrate ad-hoc metrics into a standardized pipeline for long-term analysis and capacity planning.

FAQ

Do you provide ready-to-run config snippets?

Yes. The skill generates recommended Prometheus scrape_configs, relabeling rules, and Grafana panel JSON fragments that you can adapt to your environment.

Can this handle high-cardinality metrics common in game telemetry?

The guidance emphasizes label cardinality limits and recommends aggregation and pre-aggregation in exporters to avoid excessive series growth.