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/log-aggregation

Implement centralized logging with ELK Stack, Loki, or Splunk for log collection, parsing, storage, and analysis across infrastructure.

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useful-ai-prompts
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Install
$ npx -y skills add aj-geddes/useful-ai-prompts --skill log-aggregation --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/log-aggregation

Context preview

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Implement centralized logging with ELK Stack, Loki, or Splunk for log collection, parsing, storage, and analysis across infrastructure.

SKILL.md

log-aggregation.SKILL.md
name: log-aggregation
description: >
  Implement centralized logging with ELK Stack, Loki, or Splunk for log
  collection, parsing, storage, and analysis across infrastructure.

Log Aggregation

Table of Contents

  • [Overview](#overview)
  • [When to Use](#when-to-use)
  • [Quick Start](#quick-start)
  • [Reference Guides](#reference-guides)
  • [Best Practices](#best-practices)

Overview

Build comprehensive log aggregation systems to collect, parse, and analyze logs from multiple sources, enabling centralized monitoring, debugging, and compliance auditing.

When to Use

  • Centralized log collection
  • Distributed system debugging
  • Compliance and audit logging
  • Security event monitoring
  • Application performance analysis
  • Error tracking and alerting
  • Historical log retention
  • Real-time log searching

Quick Start

Minimal working example:

# docker-compose.yml - ELK Stack setup
version: "3.8"

services:
  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:8.5.0
    environment:
      - discovery.type=single-node
      - xpack.security.enabled=false
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
    ports:
      - "9200:9200"
    volumes:
      - elasticsearch_data:/usr/share/elasticsearch/data
    healthcheck:
      test: curl -s http://localhost:9200 >/dev/null || exit 1
      interval: 10s
      timeout: 5s
      retries: 5

  logstash:
    image: docker.elastic.co/logstash/logstash:8.5.0
    volumes:
      - ./logstash.conf:/usr/share/logstash/pipeline/logstash.conf
    ports:
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the `references/` directory:

| Guide | Contents | |---|---| | [ELK Stack Configuration](references/elk-stack-configuration.md) | ELK Stack Configuration | | [Logstash Pipeline Configuration](references/logstash-pipeline-configuration.md) | Logstash Pipeline Configuration | | [Filebeat Configuration](references/filebeat-configuration.md) | Filebeat Configuration | | [Kibana Dashboard and Alerts](references/kibana-dashboard-and-alerts.md) | Kibana Dashboard and Alerts | | [Loki Configuration (Kubernetes)](references/loki-configuration-kubernetes.md) | Loki Configuration (Kubernetes) | | [Log Aggregation Deployment Script](references/log-aggregation-deployment-script.md) | Log Aggregation Deployment Script |

Best Practices

✅ DO

  • Parse and structure log data
  • Use appropriate log levels
  • Add contextual information
  • Implement log retention policies
  • Set up log-based alerting
  • Index important fields
  • Use consistent timestamp formats
  • Implement access controls

❌ DON'T

  • Store sensitive data in logs
  • Log at DEBUG level in production
  • Send raw unstructured logs
  • Ignore storage costs
  • Skip log parsing
  • Lack monitoring of log systems
  • Store logs forever
  • Log PII without encryption
Read more
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