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alloy

Configure Grafana Alloy pipelines for Kubernetes telemetry collection and forwarding.

1|Updated May 21, 2026
Search Tags:#logs#metrics#traces#otel collector#grafana alloy#kubernetes discovery#telemetry pipeline
One-click install
npx skills add https://github.com/1k-off/umbraco-observability-playground --skill alloy-1k-off
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: alloy
Source: https://github.com/1k-off/umbraco-observability-playground/tree/main/.agents/skills/alloy
Command: npx skills add https://github.com/1k-off/umbraco-observability-playground --skill alloy-1k-off

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Grafana Alloy configuration needs a consistent way to collect, transform, and forward metrics, logs, traces, and profiles while supporting Kubernetes discovery and remote backends without manual wiring for each signal type.

Core Features & Use Cases

  • Define multi-signal pipelines: Configure collection for metrics, logs, traces, and profiles in one Alloy config.
  • Scrape and discovery-driven routing: Use Kubernetes discovery and relabeling to target the right pods and enrich/export safely.
  • Export to Grafana Cloud and compatible endpoints: Send telemetry via Prometheus remote_write, Loki push, and OTLP exporters with required auth.
  • Troubleshoot and standardize collection: Apply processing steps (batching, relabeling, log parsing/labeling) and use known component patterns to reduce configuration drift.

Quick Start

Use the alloy skill to generate or validate a config.alloy that scrapes Kubernetes pods and forwards metrics to Prometheus remote write, logs to Loki, and traces to Tempo by referencing the relevant component blocks in your Alloy file.

Frequently Asked Questions about alloy

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

FAQPage Schema
How do I configure Grafana Alloy to collect metrics, logs, and traces in one pipeline?▼

Build a multi-signal telemetry pipeline in Alloy by wiring component blocks for scraping, file/kubernetes log sources, and OTLP receivers to collect and forward metrics, logs, and traces together.

How do I use Kubernetes discovery to scrape pods and forward telemetry to remote backends?▼

Use Kubernetes discovery and relabeling rules in Alloy to target the right pods and enrich telemetry, then export safely via Prometheus remote_write, Loki push, and OTLP exporters with required authentication.

Can I send telemetry from Alloy to Grafana Cloud using Prometheus remote_write and Loki push?▼

Yes, you can send telemetry to Grafana Cloud by configuring authenticated remote write and push endpoints, using Prometheus remote_write for metrics, Loki push for logs, and OTLP exporters for traces.

How do I parse and relabel logs in an Alloy telemetry pipeline?▼

Apply processing stages in your Alloy configuration to parse and label logs, using relabeling and batching steps to transform telemetry and reduce configuration drift before exporting.

Does Grafana Alloy support clustering and Fleet remote config for telemetry collection?▼

Yes, Alloy supports optional clustering and Fleet remote config to distribute and manage telemetry collection across environments, ensuring reliable pipeline operation at scale.

What is the best way to troubleshoot configuration drift in Alloy telemetry pipelines?▼

Troubleshoot and standardize collection by applying known component patterns, relabeling rules, and processing stages in your Alloy config to reduce configuration drift and ensure consistent telemetry forwarding.

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